An electrical heat integrated energy system advanced scheduling method, system and medium

Abstract

The application provides an electric heat integrated energy system advanced scheduling method and system and a medium. The application couples a heat and power cogeneration unit and an electric-to-gas device to construct an electric heat integrated energy system model; obtains new energy predicted output and future load conditions of the system through a long short-term memory artificial neural network; sequentially constructs system backup constraints, generator set operation constraints, wind farm operation constraints, power network constraints, heat system operation constraints, gas source point constraints, pipeline constraints and node supply and demand balance constraints to establish coupling device constraints; constructs an electric heat system target model and a natural gas system target model of the electric heat integrated energy system; and obtains variables of the electric heat integrated energy system at multiple predicted time points through an alternating iterative optimization method to realize electric heat integrated energy system advanced scheduling. The model has high accuracy, saves computing resources, has fast sub-problem solving speed and good convergence performance.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of electrical heat integrated energy system scheduling, and particularly relates to an electrical heat integrated energy system advanced scheduling method and a computer readable medium. BACKGROUND

[0002] The inherent volatility and uncertainty of wind and light renewable energy generation output bring great challenges to power system operation, and the problem of wind and light curtailment is highlighted. With the concept of energy internet being proposed, the current method of constructing an electrical heat interconnected integrated system by coupling devices, i.e. combined heat and power (CHP) and power to gas (P2G), and improving system operation flexibility is a feasible solution to improve the level of renewable energy consumption.

[0003] Considering that centralized scheduling needs to occupy a large amount of computing resources of the upper scheduling center, and that there may be data privacy requirements of the subsystem, the advanced scheduling of the electrical heat integrated energy system is a more reasonable mode. The current advanced scheduling mode of the electrical heat integrated energy system has the risk of non-convergence of the calculation process, and the number of iterations is also relatively large, so that the time cost and communication cost are high.

[0004] The present application is based on the concept of alternating direction method of multipliers (ADMM) and combined with analytical target cascading (ATC), and proposes an efficient advanced scheduling method based on ATC-ADMM for the electrical heat integrated energy system, which realizes the fast solution of the advanced scheduling of the electrical heat integrated energy system on the basis of guaranteeing the data privacy requirements of the subsystem. SUMMARY

[0005] In order to solve the problems existing in the prior art, the present application proposes an electrical heat integrated energy system advanced scheduling method, system and medium, which realizes the fast solution of the advanced scheduling of the electrical heat integrated energy system and can be applied to various electrical heat integrated energy system advanced scheduling.

[0006] The technical scheme of the method of the present application is an electrical heat integrated energy system advanced scheduling method, which specifically comprises the following steps:

[0007] Step 1: build a power transmission system model, a heat supply system model, and a natural gas system model, obtain the electric load of each power node in the power transmission system model at multiple historical time points, the output of each wind farm in the power transmission system model at multiple historical time points, the heat load of each heat supply node in the heat supply system model at multiple historical time points, and the gas load of each natural gas node in the natural gas system model at multiple historical time points, respectively couple the power transmission system model and the heat supply system model through an electric-thermal coupling device, couple the power transmission system model and the electric-thermal system model through an electrical coupling device, build an electric-thermal system model, and build an electrical and thermal integrated energy system model;

[0008] Step 2: obtain the predicted electric load of each power node in the power transmission system model at multiple future time points by predicting the electric load of each power node in the power transmission system model at multiple historical time points through a long short-term memory artificial neural network, obtain the active predicted power of each wind farm in the power transmission system model at multiple future time points according to the output of each wind farm in the power transmission system model at multiple historical time points, obtain the predicted heat load of each heat supply node in the heat supply system model at multiple future time points by predicting the heat load of each heat supply node in the heat supply system model at multiple historical time points through a long short-term memory artificial neural network, and obtain the predicted gas load of each natural gas node in the natural gas system model at multiple future time points by predicting the gas load of each natural gas node in the natural gas system model at multiple future time points through a long short-term memory artificial neural network;

[0009] Step 3: combine the active predicted power of each wind farm in the power transmission system model at multiple future time points and the predicted electric load of each power node at multiple future time points to sequentially build system reserve constraints, generator set operation constraints, wind farm operation constraints, and power network constraints, combine the predicted heat load of each heat supply node in the heat supply system model at multiple future time points to build heat supply system operation constraints, combine the predicted gas load of each natural gas node in the natural gas system model at multiple future time points to sequentially build gas source point constraints, pipeline constraints, and node supply-demand balance constraints, and establish coupling device constraints;

[0010] Step 4: build an electric-thermal system target model of the electrical and thermal integrated energy system and a natural gas system target model of the electrical and thermal integrated energy system;

[0011] Step 5: build coupling device constraints, take the electric heat system target model of the electric heat integrated energy system and the natural gas system target model of the electric heat integrated energy system as optimization objectives, build the electric heat system target model of the electric heat integrated energy system for alternating optimization iteration, build the natural gas system target model of the electric heat integrated energy system for alternating optimization iteration, and perform optimization solving through the alternating iterative optimization method to obtain the solved variables of the electric heat integrated energy system at multiple prediction times, and realize advanced scheduling of the electric heat integrated energy system through the solved variables of the electric heat integrated energy system at multiple prediction times.

[0012] Preferably, the number of power nodes in the power transmission system model of step 1 is N;

[0013] The number of wind farms in the power transmission system model of step 1 is W;

[0014] The number of heat nodes in the heat system model of step 1 is H;

[0015] The number of natural gas nodes in the natural gas system model of step 1 is S;

[0016] Preferably, the number of future times in step 2 is T;

[0017] The predicted electric load of each power node in the power transmission system model at multiple future times in step 2 is specifically defined as follows:

[0018] P n,t load

[0019] n∈[1,N],t∈[1,T]

[0020] Wherein, N represents the number of power nodes in the power transmission system model, T represents the number of future times, P n,t load represents the predicted electric load of the nth power node in the power transmission system model at the tth future time;

[0021] The active predicted power of each wind farm in the power transmission system model at multiple future times in step 2 is specifically defined as follows:

[0022] P w,t 0

[0023] w∈[1,W],t∈[1,T]

[0024] Wherein, W represents the number of wind farms in the power transmission system model, T represents the number of future times, P w,t 0 represents the predicted active power of the wth wind farm in the power transmission system model at the tth future time.

[0025] The predicted heat load of each heat node in the heat system model at multiple future time points is defined as follows:

[0026] H h,t load

[0027] h∈[1,H],t∈[1,T]

[0028] Wherein, H represents the number of heat nodes in the heat system model, T represents the number of future time points, H h,t load represents the predicted heat load of the hth heat node in the heat system model at the tth future time point.

[0029] The predicted gas load of each natural gas node in the natural gas system model at multiple future time points is defined as follows:

[0030] F s,t load

[0031] s∈[1,S],t∈[1,T]

[0032] Wherein, S represents the number of natural gas nodes in the natural gas system model, T represents the number of future time points, F s,t load represents the predicted heat load of the sth natural gas node in the natural gas system model at the tth future time point.

[0033] As a preferred, the system backup constraint in step 3 is defined as follows:

[0034]

[0035]

[0036] Wherein, x g,t gen represents the 0 / 1 indication variable of the gth generator in the power transmission system model connected to the grid at the tth future time point, x i,t CHP represents the 0 / 1 indication variable of the ith CHP in the electric-thermal coupling device connected to the grid at the tth future time point, P g gen,max and P g gen,min are the maximum technical output and the minimum technical output of the gth generator in the power transmission system model, P g CHP,max and P g CHP,min represents the maximum technical output and the minimum technical output of the ith CHP in the electric-thermal coupling device, Pw,t wind Pw,t represents the active power output of the wth wind farm at the tth future time in the power transmission system model, r load Pw,t represents the active power output of the wth wind farm at the tth future time in the power transmission system model, r wind Pw,t represents the active power output of the wth wind farm at the tth future time in the power transmission system model, r n,t load Pn,t represents the predicted electric load of the nth electric load node at the tth future time in the power transmission system model, G represents the number of generators in the power transmission system model, W represents the number of wind farms in the power transmission system model, N CHP Pn,t represents the predicted electric load of the nth electric load node at the tth future time in the power transmission system model, G represents the number of generators in the power transmission system model, W represents the number of wind farms in the power transmission system model, N Each number in the interval satisfies the range constraint.

[0037] The generator set operation constraint in step 3 is specifically defined as follows:

[0038]

[0039]

[0040]

[0041]

[0042]

[0043] wherein x g,t gen xg,t represents a 0 / 1 indication variable of the gth generator being connected to the grid at the tth future time in the power transmission system model, x g,t-1 gen xg,t represents a 0 / 1 indication variable of the gth generator being connected to the grid at the tth future time in the power transmission system model, x g,w gen xg,t represents a 0 / 1 indication variable of the gth generator being connected to the grid at the tth future time in the power transmission system model, T g gen,st and T g gen,sd Pmin and Pmax represent the minimum start-up time and the minimum shutdown time of the gth generator in the power transmission system model, respectively, P g gen,max Pmin and Pmax represent the minimum start-up time and the minimum shutdown time of the gth generator in the power transmission system model, respectively, P g gen,min Pmin and Pmax represent the maximum technical output and the minimum technical output of the gth generator in the power transmission system model, respectively, P g,t gen Pmin and Pmax represent the maximum technical output and the minimum technical output of the gth generator in the power transmission system model, respectively, Pg,t-1 gen represents the active output power of the g-th generator at the t-1th future moment in the transmission system model, Q g,t gen represents the reactive output power of the g-th generator at the t-th future moment in the transmission system model, and They represent the lower and upper limits of the grid-connected power factor angle of each generator in the transmission system model, r g gen,up and r g gen,dn They represent the upper and lower climbing limits of the g-th generator in the transmission system model, respectively. ||·||2 represents the mathematical 2-norm calculation formula. G represents the number of generators in the transmission system model. T represents the number of generators in the future time. Indicates that every number in the interval satisfies the range constraint;

[0044] Preferably, the wind farm operation constraints in step 3 are specifically defined as follows:

[0045]

[0046] Among them, P w,t wind represents the active output power of the w-th wind farm at the t-th future moment in the transmission system model, P w,t 0 represents the predicted active power of the w-th wind farm at the t-th future moment in the transmission system model, Q w,t wind represents the reactive output power of the w-th wind farm at the t-th future moment in the transmission system model, Indicates the lower limit of the grid-connected power factor angle of each wind farm in the transmission system model, arccos indicates the cosine angle calculation, tan indicates the sine angle calculation, W indicates the number of wind farms in the transmission system model, and T indicates the number at the future time. Indicates that every number in the interval satisfies the range constraint;

[0047] The power network constraints described in step 3 are specifically defined as follows:

[0048]

[0049]

[0050] 0≤Q n,t com ≤Q n com,max ,n∈[1,N]

[0051]

[0052]

[0053]

[0054]

[0055]

[0056]

[0057]

[0058] where P i,t CHP and Q i,t CHP denote the output active power and output reactive power of the ith CHP at the tth future time in the electrically coupled device, respectively, P i,t P2G denote the input active power of the ith P2G at the tth future time in the electrically coupled device, P g,t gen and Q g,t gen denote the output active power and output reactive power of the gth generator at the tth future time in the power system model, respectively, P w,t wind and Q w,t wind denote the output active power and output reactive power of the wth wind farm at the tth future time in the power system model, respectively, P l,t line and Q l,t line denote the sending-end active power and sending-end reactive power of the lth transmission line at the tth future time in the power system model, △P l,t line and △Q l,t line denote the active power loss and reactive power loss of the lth transmission line at the tth future time in the power system model, P n,t load denote the predicted electric load of the nth electric power node at the tth future time in the power system model, Q denote the power factor angle of the nth electric power node at the tth future time in the power system model, Q n,t com denote the reactive compensation power of the nth electric power node at the tth future time in the power system model, Q n com,max denote the maximum reactive compensation power of the nth electric power node in the power system model, u l,t+ and θ l,t + respectively represent the voltage amplitude square and phase angle of the sending end of the lth transmission line at the tth future time in the transmission system model, u l,t + and θ l,t + respectively represent the voltage amplitude square and phase angle of the receiving end of the lth transmission line at the tth future time in the transmission system model, G l and B l respectively represent the conductance and susceptance of the lth transmission line in the transmission system model, S l,max represent the rated transmission capacity of the lth transmission line in the transmission system model, θ n,t represent the voltage phase angle of the nth power node at the tth future time in the transmission system model, v n min and v n max respectively represent the minimum value and maximum value of the voltage amplitude of the nth power node in the transmission system model, θ l,slack t represent the relaxation amount of the square of the phase angle difference △θ l,t of the lth transmission line at the tth future time in the transmission system model, △θ l max represent the maximum value of the absolute value of the phase angle difference between the sending end and the receiving end of the lth transmission line in the transmission system model, sl l,t,i represent the slope of the i th segment of the square of the phase angle difference △θ l,t of the lth transmission line at the tth future time in the transmission system model, N sl represent the number of segments of the square of the phase angle difference of each transmission line at each future time in the transmission system model, TC l,t,i represent the value of the i th segment point of the square of the phase angle difference △θ l,t of the lth transmission line at the tth future time in the transmission system model, N n CHP represent the number of CHPs connected to the nth power node in the transmission system model, N n P2G represent the number of P2Gs connected to the nth power node in the transmission system model, N n G represent the number of generators connected to the nth power node in the transmission system model, N n W represent the number of wind farms connected to the nth power node in the transmission system model, N n l(+) represent the number of transmission lines with the nth power node as the sending end in the transmission system model, N n l(-)L ele N is the number of power nodes in the power transmission system model, T represents the number of future time, ||·||2 represents the mathematical 2-norm calculation formula, It is indicated that each number in the interval satisfies the range constraint.

[0059] The thermal system model operation constraint in step 3 is defined as follows:

[0060]

[0061]

[0062]

[0063]

[0064] Wherein, H h,t load H i,t CHP C P The specific heat capacity of water quality in the heat supply system model, m h,t q The injection flow rate of water quality of the hth heat supply node of the heat supply system model at the tth future time, T h,t s The supply water temperature of the hth heat supply node of the heat supply system model at the tth future time, T h,t r The return water temperature of the hth heat supply node of the heat supply system model at the tth future time, T h s,min And T h s,max The lower limit and upper limit of the supply water temperature of the hth heat supply node of the heat supply system model, respectively, T h r,min And T h r,max The lower limit and upper limit of the return water temperature of the hth heat supply node of the heat supply system model, respectively, T l,t - And T l,t + The temperature of the tth future time of the lth heat supply pipeline of the heat supply system model, e represents the base number of natural logarithm function, m l,t The water quality flow rate of the lth heat supply pipeline of the heat supply system model at the tth future time, λ lheat represents the heat transfer coefficient of the lth heating pipe in the heat supply system model, T t a represents the ambient temperature of the tth future time of the heat supply system model, len l represents the length of the lth heating pipe in the heat supply system model, H h l(+) represents the number of heating pipes with the n th heat supply node as the sending end in the heat supply system model, H h l(-) represents the number of heating pipes with the n th heat supply node as the receiving end in the heat supply system model, H h CHP represents the number of CHPs connected to the n th heat supply node in the heat supply system model, L heat represents the number of heating pipes in the heat supply system model, H represents the number of heat supply nodes in the heat supply system model, and T represents the number of future times, represents that each number in the interval satisfies the range constraint;

[0065] The gas source point constraint in step 3 is specifically defined as follows:

[0066]

[0067] Wherein, F w,t sup represents the output gas flow of the wth gas source at the tth future time in the gas system model, F w sup ,min and F w sup,max respectively represent the minimum and maximum values of the output gas flow of the wth gas source in the gas system model, W sup represents the number of gas source points in the gas system model, and T represents the number of future times;

[0068] The pipe constraint in step 3 is specifically defined as follows:

[0069]

[0070]

[0071]

[0072]

[0073]

[0074]

[0075]

[0076] wherein the symbol | · | represents a mathematical absolute value calculation formula, || · ||2 represents a mathematical 2-norm calculation formula, F l,t line represents the gas flow rate of the lth gas supply pipeline at the tth future time in the natural gas system model, k l line represents the transmission coefficient of the lth gas supply pipeline in the natural gas system model, pg l,t + and pg l,t - respectively represent the sending end and receiving end gas pressure of the lth gas supply pipeline at the tth future time in the natural gas system model, F l line,max represents the maximum allowable gas flow rate of the lth gas supply pipeline in the natural gas system model, pg l +,min and pg l +,max respectively represent the lower limit and upper limit of the sending end gas pressure of the lth gas supply pipeline in the natural gas system model, pg l -,min and pg l -,max respectively represent the lower limit and upper limit of the receiving end gas pressure of the lth gas supply pipeline in the natural gas system model, x l,t + and x l,t -- respectively represent the water quality positive flow direction and negative flow direction indication 0 / 1 variable of the lth gas supply pipeline at the tth future time in the natural gas system model, represents the water quality flow direction judgment auxiliary constant of the lth gas supply pipeline at each time in the natural gas system model, α l,t i represents the first water quality flow direction judgment auxiliary variable of the lth gas supply pipeline at the tth future time in the natural gas system model, represents the second water quality flow direction judgment auxiliary variable of the lth gas supply pipeline at the tth future time in the natural gas system model, β l,t i represents the third water quality flow direction judgment auxiliary variable of the lth gas supply pipeline at the tth future time in the natural gas system model, represents the fourth water quality flow direction judgment auxiliary variable of the lth gas supply pipeline at the tth future time in the natural gas system model, M represents an auxiliary constant in the natural gas system model, L gas represents the number of gas supply pipelines in the natural gas system model, T represents the number of future times, represents that each number in the interval satisfies the range constraint;

[0077] The node supply and demand balance constraint in step 3 is specifically defined as follows:

[0078]

[0079] where F w,t sup represents the output gas flow of the wth gas source at the tth future time in the natural gas system model, F l,t line represents the gas flow of the lth gas supply pipeline at the tth future time in the natural gas system model, F i,t P2G represents the gas flow of the ith P2G at the tth future time in the coupling device model, F i,t CHP represents the gas flow of the ith CHP at the tth future time in the coupling device model, F s,t load represents the predicted heat load of the s th natural gas node at the tth future time in the natural gas system model, S s sup represents the number of gas sources connected to the s th natural gas node in the natural gas system model, S s l(+) represents the number of gas supply pipelines with the s th natural gas node as the sending end in the natural gas system model, S s l(-) represents the number of gas supply pipelines with the s th natural gas node as the receiving end in the natural gas system model, S s P2G represents the number of P2Gs connected to the s th natural gas node in the natural gas system model, S s CHP represents the number of CHPs connected to the s th natural gas node in the natural gas system model, S represents the number of natural gas nodes in the natural gas system model, represents that each number in the interval satisfies the range constraint;

[0080] The coupling device constraint in step 3 is specifically defined as follows:

[0081]

[0082]

[0083]

[0084]

[0085]

[0086]

[0087] where P i,tCHP , Q i,t CHP 、F i,t CHP and H i,t CHP They represent the output active power, output reactive power, input gas flow and output thermal power of the i-th CHP in the electrothermal coupling device at the t-th future moment, respectively. g Represents the calorific value of natural gas in the coupled equipment model, RHE i CHP represents the thermoelectric ratio of the i-th CHP in the electrothermal coupling device at each future moment; η i CHP represents the energy conversion efficiency of the i-th CHP in the electrothermal coupling device at each future moment, P i,t-1 CHP represents the output active power of the ith CHP in the electrothermal coupling device at the t-1th future moment, x i,t CHP represents the 0 / 1 indicator variable for the grid-connected operation of the ith CHP in the electrothermal coupling device at the tth future moment, x i,t-1 CHP represents the 0 / 1 indicator variable for the grid-connected operation of the ith CHP in the electrothermal coupling device at the t-1th future time, x i,w CHP T represents the 0 / 1 indicator variable indicating the grid connection operation of the i-th CHP in the electric-thermal coupling device at the w-th future time. i CHP ,st and T i CHP,sd They represent the minimum start-up time and minimum shutdown time of the i-th CHP in the electrothermal coupling equipment, P i CHP,max and P i CHP,min denote the maximum and minimum technical outputs of the ith CHP in the electrothermal coupling device, and They represent the lower and upper limits of the grid-connected power factor angle of each CHP in the electrothermal coupling equipment, r i CHP,up and r i CHP,dn They represent the upper and lower climbing limits of the i-th CHP in the electrothermal coupling device, ||·||2 represents the mathematical 2-norm calculation formula, and N CHP represents the number of CHPs in the electrothermal coupling device, T represents the number at a future time, Indicates that every number in the interval satisfies the range constraint;

[0088]

[0089] where P i,t P2G , F i,t P2G represent the input active power of the ith P2G at the tth future time in the electrically coupled device, the output gas flow, HV g represents the heat value of natural gas in the coupled device, η i P2G represents the energy conversion efficiency of the ith P2G at each future time in the coupled device model, N P2G represents the number of P2Gs in the electrically coupled device, and T represents the number of future times, represent that each number in the interval satisfies the range constraint;

[0090] As preferred, the electrical heat comprehensive energy system target model of step 4 is specifically defined as follows:

[0091]

[0092] where f1 represents the total operation cost of the electrical heat comprehensive energy system, C1 represents the sum of the generator start-up cost and the CHP start-up cost of the electrical heat comprehensive energy system, C2 represents the sum of the variable cost of the generator and the variable cost of the CHP of the electrical heat comprehensive energy system, C3 represents the wind curtailment penalty cost of the electrical heat comprehensive energy system, C g gen,st represents the single start-up cost of the gth generator of the electrical heat comprehensive energy system, C i CHP,st represents the single start-up cost of the ith CHP of the electrical heat comprehensive energy system, a g gen , b g gen and c g gen represent the first-order term, the second-order term and the constant term coefficient of the variable cost of the gth generator of the electrical heat comprehensive energy system, a i CHP , b i CHP and c i CHP represent the first-order term, the second-order term and the constant term coefficient of the variable cost of the ith CHP of the electrical heat comprehensive energy system, x g,t gen represents the 0 / 1 indication variable of the gth generator in the power transmission system model connected to the grid at the tth future time, x g,t-1 gen represents the 0 / 1 indication variable of the gth generator in the power transmission system model connected to the grid at the t-1th future time, xi,t CHP represents the 0 / 1 indicator variable of the i-th CHP operating in grid-connected mode at the t-th future time in the electrical-thermal coupled device, x i,t-1 CHP represents the 0 / 1 indicator variable of the i-th CHP operating in grid-connected mode at the t-1-th future time in the electrical-thermal coupled device, P g,t gen represents the active power output and the reactive power output of the g-th generator at the t-th future time in the power transmission system model, P i,t CHP represents the active power output of the i-th CHP at the t-th future time in the electrical-thermal coupled device, P w,t wind represents the active power output of the w-th wind farm at the t-th future time in the power transmission system model, P w,t 0 represents the wind power prediction active power of the w-th wind farm at the t-th future time in the power transmission system model, W punish represents the unit wind curtailment penalty cost in the power transmission system model, N CHP represents the number of CHPs in the electrical-thermal coupled device, G represents the number of generators in the power transmission system model, W represents the number of wind farms in the power transmission system model, and T represents the number of future times, represents that each number in the interval satisfies the range constraint;

[0093] The natural gas system target model of the electrical-thermal integrated energy system in step 4 is specifically defined as follows:

[0094]

[0095] wherein f2 represents the total operation cost of the natural gas system of the electrical-thermal integrated energy system, C N1 represents the total gas source operation cost of the natural gas system of the electrical-thermal integrated energy system, C N2 represents the total P2G operation cost of the natural gas system of the electrical-thermal integrated energy system, c w sup represents the unit operation cost of the w-th gas source of the natural gas system of the electrical-thermal integrated energy system at each future time, c i P2G represents the unit operation cost of the i-th P2G of the natural gas system of the electrical-thermal integrated energy system at each future time, F w,t sup represents the output gas flow of the w-th gas source at the t-th future time in the natural gas system model, F i,t P2G represents the output gas flow of the i-th P2G at the t-th future time in the electrical-thermal coupled device, W sup represents the number of gas source points in the natural gas system model, NP2G denotes the number of P2G in the electrical coupling device, T denotes the number of future time, denotes that each number in the interval satisfies the range constraint;

[0096] As preferred, the step 5 of establishing the electrical-thermal system objective model of the electrical-thermal integrated energy system for the alternating optimization iteration is specifically defined as follows:

[0097]

[0098] wherein, f1 denotes the total operation cost of the electrical-thermal integrated energy system, λ i,t CHP,1 denotes the Lagrange dual multiplier of the i-th CHP of the electrical-thermal integrated energy system in the t-th future time period of the electrical-thermal system, λ i,t P2G,1 denotes the Lagrange dual multiplier of the i-th P2G of the electrical-thermal integrated energy system in the t-th future time period of the electrical-thermal system, h i,t CHP,1 denotes the Lagrange penalty term coefficient of the i-th CHP of the electrical-thermal integrated energy system in the t-th future time period of the electrical-thermal system, h i,t P2G,1 denotes the Lagrange penalty term coefficient of the i-th P2G of the electrical-thermal integrated energy system in the t-th future time period of the electrical-thermal system, P i,t CHP,1 denotes the output active power of the i-th CHP in the t-th future time of the electrical coupling device obtained by solving the electrical-thermal system objective model of the electrical-thermal integrated energy system for the alternating optimization iteration, P i,t CHP,2 denotes the output active power of the i-th CHP in the t-th future time of the electrical coupling device obtained by solving the natural gas system objective model of the electrical-thermal integrated energy system for the alternating optimization iteration, P i,t P2G,1 denotes the output active power of the i-th P2G in the t-th future time of the electrical coupling device obtained by solving the electrical-thermal system objective model of the electrical-thermal integrated energy system for the alternating optimization iteration, P i,t CHP,2 denotes the output active power of the i-th P2G in the t-th future time of the electrical coupling device obtained by solving the natural gas system objective model of the electrical-thermal integrated energy system for the alternating optimization iteration, N P2G denotes the number of P2G in the electrical coupling device, N CHP denotes the number of CHP in the electrical-thermal coupling device, T denotes the number of future time;

[0099] The step 5 of establishing the electrical-thermal system objective model of the electrical-thermal integrated energy system for the alternating optimization iteration is specifically defined as follows:

[0100]

[0101] wherein f2 represents the total operation cost of the natural gas system of the electrical-thermal integrated energy system, λ i,t CHP,2 represents the Lagrange dual multiplier of the ith CHP of the natural gas system of the electrical-thermal integrated energy system in the tth future time period, λ i,t P2G,2 represents the Lagrange dual multiplier of the ith P2G of the natural gas system of the electrical-thermal integrated energy system in the tth future time period, h i,t CHP,2 represents the Lagrange penalty term coefficient of the ith CHP of the natural gas system of the electrical-thermal integrated energy system in the tth future time period, h i,t P2G,2 represents the Lagrange penalty term coefficient of the ith P2G of the natural gas system of the electrical-thermal integrated energy system in the tth future time period, P i,t CHP,1 represents the output active power of the ith CHP in the tth future time of the electrical-thermal coupled device obtained by solving the electrical-thermal system target model of the electrical-thermal integrated energy system for the alternating optimization iteration, P i,t CHP,2 represents the output active power of the ith CHP in the tth future time of the electrical-thermal coupled device obtained by solving the natural gas system target model of the electrical-thermal integrated energy system for the alternating optimization iteration, P i,t P2G,1 represents the output active power of the ith P2G in the tth future time of the electrical-thermal coupled device obtained by solving the electrical-thermal system target model of the electrical-thermal integrated energy system for the alternating optimization iteration, P i,t CHP,2 represents the output active power of the ith P2G in the tth future time of the electrical-thermal coupled device obtained by solving the natural gas system target model of the electrical-thermal integrated energy system for the alternating optimization iteration, N P2G represents the number of P2Gs in the electrical coupled device, N CHP represents the number of CHPs in the electrical-thermal coupled device, and T represents the number of future times;

[0102] Step 5, the optimization solution is obtained by the alternating iteration optimization method, and the solved variables of the electrical-thermal integrated energy system in multiple prediction time periods are obtained, and the specific process is as follows:

[0103] Step 5.1, initializing the iteration number k = 1, and initializing the Lagrange dual multiplier λ i,t,k CHP,1, initialize the Lagrange dual multiplier λ of the electric heat integrated energy system's electric heat system for the i-th P2G in the t-th future period of the k-th iteration i,t,k P2G,1 , initialize the Lagrange penalty term coefficient h of the electric heat integrated energy system's electric heat system for the i-th CHP in the t-th future period of the k-th iteration i,t,k CHP,1 , initialize the Lagrange penalty term coefficient h of the electric heat integrated energy system's electric heat system for the i-th P2G in the t-th future period of the k-th iteration i,t,k P2G,1 , initialize the Lagrange dual multiplier λ of the electric heat integrated energy system's natural gas system for the i-th CHP in the t-th future period of the k-th iteration i,t,k CHP,2 , initialize the Lagrange dual multiplier λ of the electric heat integrated energy system's natural gas system for the i-th P2G in the t-th future period of the k-th iteration i,t,k P2G,2 , initialize the Lagrange penalty term coefficient h of the electric heat integrated energy system's natural gas system for the i-th CHP in the t-th future period of the k-th iteration i,t,k CHP,2 , initialize the Lagrange penalty term coefficient h of the electric heat integrated energy system's natural gas system for the i-th P2G in the t-th future period of the k-th iteration i,t,k P2G,2 , initialize the output active power P of the i-th CHP in the t-th future time of the electric heat coupled device obtained by solving the electric heat system target model of the electric heat integrated energy system for the k-th iteration of the alternating optimization iteration i,t,k CHP,1 , initialize the output active power P of the i-th CHP in the t-th future time of the electric heat coupled device obtained by solving the natural gas system target model of the electric heat integrated energy system for the k-th iteration of the alternating optimization iteration i,t,k CHP,2 , initialize the output active power P of the i-th P2G in the t-th future time of the electric coupled device obtained by solving the electric heat system target model of the electric heat integrated energy system for the k-th iteration of the alternating optimization iteration i,t,k P2G,1 , initialize the output active power P of the i-th P2G in the t-th future time of the electric heat coupled device obtained by solving the natural gas system target model of the electric heat integrated energy system for the k-th iteration of the alternating optimization iteration i,t,k CHP,2 , initialize the iteration calculation convergence threshold ε of the electric heat integrated energy system;

[0104] Step 5.2, the electric heating system dispatching center solves the electric heating system target model of the electric-thermal integrated energy system for the alternating optimization iteration based on the electric heating system target model of the electric-thermal integrated energy system for the alternating optimization iteration and system backup constraints, generator set operation constraints, wind farm operation constraints, power network constraints, and heating system operation constraints, to obtain the output active power P of the i-th CHP in the electric-thermal coupling device at the t-th future time of the k-th iteration of the electric heating system target model of the electric-thermal integrated energy system for the alternating optimization iteration by the interior point method i,t,k CHP,1 , and the output active power P of the i-th P2G in the electric coupling device at the t-th future time of the k-th iteration of the electric heating system target model of the electric-thermal integrated energy system for the alternating optimization iteration i,t,k P2G,1 , wherein N P2G represents the number of P2Gs in the electric coupling device, N CHP represents the number of CHPs in the electric-thermal coupling device, and T represents the number of future times, is the expression of "all" in mathematics, indicating that each number in the interval satisfies the constraint;

[0105] Step 5.3, the natural gas system dispatching center solves the natural gas system target model of the electric-thermal integrated energy system for the alternating optimization iteration based on the natural gas system target model of the electric-thermal integrated energy system for the alternating optimization iteration and gas source point constraints, pipeline constraints, and node supply-demand balance constraints, to obtain the output active power P of the i-th CHP in the electric-thermal coupling device at the t-th future time of the k-th iteration of the natural gas system target model of the electric-thermal integrated energy system for the alternating optimization iteration by the interior point method i,t,k CHP,2 , and the output active power P of the i-th P2G in the electric coupling device at the t-th future time of the k-th iteration of the natural gas system target model of the electric-thermal integrated energy system for the alternating optimization iteration i,t,k P2G,2 , wherein N P2G represents the number of P2Gs in the electric coupling device, N CHP represents the number of CHPs in the electric-thermal coupling device, and T represents the number of future times, is the expression of "all" in mathematics, indicating that each number in the interval satisfies the constraint;

[0106] Step 5.4, the upper-level dispatching center determines whether the iteration process converges according to the convergence criterion, and if the iteration process converges, the upper-level dispatching center issues a converged signal, and the algorithm stops to obtain the solved variables of the electric-thermal integrated energy system at multiple prediction times. If the iteration process does not converge, let k = k + 1, the upper-level dispatching center updates the operator according to the operator update model and issues it, and then returns to step 5.2;

[0107] The convergence criterion described in step 5.4 is defined as follows:

[0108]

[0109] where the symbol |·| represents the mathematical absolute value calculation formula, P i,t,k CHP,1 represents the output active power of the ith CHP at the tth future time in the electrical-thermal coupled device obtained by the kth iteration solution of the electrical-thermal system target model of the electrical-thermal integrated energy system for the alternative optimization iteration, i,t,k CHP,2 represents the output active power of the ith CHP at the tth future time in the electrical-thermal coupled device obtained by the kth iteration solution of the natural gas system target model of the electrical-thermal integrated energy system for the alternative optimization iteration, i,t,k P2G,1 represents the output active power of the ith P2G at the tth future time in the electrical-thermal coupled device obtained by the kth iteration solution of the electrical-thermal system target model of the electrical-thermal integrated energy system for the alternative optimization iteration, i,t,k CHP,2 represents the output active power of the ith P2G at the tth future time in the electrical-thermal coupled device obtained by the kth iteration solution of the natural gas system target model of the electrical-thermal integrated energy system for the alternative optimization iteration, P2G represents the number of P2Gs in the electrical coupled device, CHP represents the number of CHPs in the electrical-thermal coupled device, and T represents the number of future time, is the expression of "all" in mathematics, which means that each number in the interval satisfies the constraint;

[0110] update the Lagrange dual multiplier λ of the electrical-thermal system of the electrical-thermal integrated energy system for the ith CHP at the tth future period of the kth iteration by updating the model i,t,k CHP,1 , the Lagrange dual multiplier λ of the electrical-thermal system of the electrical-thermal integrated energy system for the ith P2G at the tth future period of the kth iteration i,t,k P2G,1 , the Lagrange penalty term coefficient h of the electrical-thermal system of the electrical-thermal integrated energy system for the ith CHP at the tth future period of the kth iteration i,t,k CHP,1 , the Lagrange penalty term coefficient h of the electrical-thermal system of the electrical-thermal integrated energy system for the ith P2G at the tth future period of the kth iteration i,t,k P2G,1 , the Lagrange dual multiplier λ of the natural gas of the electrical-thermal integrated energy system for the ith CHP at the tth future period of the kth iteration i,t,k CHP,2the Lagrange dual multiplier of the electric heat integrated energy system's natural gas system in the kth iteration, the ith P2G, the tth future period i,t,k P2G,2 the Lagrange penalty term coefficient h of the electric heat integrated energy system's natural gas system in the kth iteration, the ith CHP, the tth future period i,t,k CHP,2 and the Lagrange penalty term coefficient h of the electric heat integrated energy system's natural gas system in the kth iteration, the ith P2G, the tth future period i,t,k P2G,2 , and the specific definitions are as follows:

[0111]

[0112]

[0113]

[0114]

[0115] Wherein, β represents the Lagrange penalty term coefficient update factor in the electric heat integrated energy system, λ i,t,k+1 CHP,1 represents the Lagrange dual multiplier of the electric heat system of the electric heat integrated energy system in the k+1th iteration, the ith CHP, the tth future period, λ i,t,k+1 P2G,1 represents the Lagrange dual multiplier of the electric heat system of the electric heat integrated energy system in the k+1th iteration, the ith P2G, the tth future period, h i,t,k+1 CHP,1 represents the Lagrange penalty term coefficient of the electric heat system of the electric heat integrated energy system in the k+1th iteration, the ith CHP, the tth future period, h i,t,k+1 P2G,1 represents the Lagrange penalty term coefficient of the electric heat system of the electric heat integrated energy system in the k+1th iteration, the ith P2G, the tth future period, λ i,t,k+1 CHP,2 represents the Lagrange dual multiplier of the natural gas of the electric heat integrated energy system in the k+1th iteration, the ith CHP, the tth future period, λ i,t,k+1 P2G,2 represents the Lagrange dual multiplier of the natural gas system of the electric heat integrated energy system in the k+1th iteration, the ith P2G, the tth future period, h i,t,k+1 CHP,2 represents the Lagrange penalty term coefficient of the natural gas system of the electric heat integrated energy system in the k+1th iteration, the ith CHP, the tth future period, h i,t,k+1 P2G,2λ represents the Lagrange multiplier term coefficient of the natural gas system of the electrical-thermal integrated energy system in the i-th P2G of the k+1-th iteration of the t-th future time period i,t,k CHP,1 λ represents the Lagrange dual multiplier of the electrical-thermal system of the electrical-thermal integrated energy system in the i-th CHP of the k-th iteration of the t-th future time period i,t,k P2G,1 h represents the Lagrange dual multiplier of the electrical-thermal system of the electrical-thermal integrated energy system in the i-th P2G of the k-th iteration of the t-th future time period i,t,k CHP,1 h represents the Lagrange multiplier term coefficient of the electrical-thermal system of the electrical-thermal integrated energy system in the i-th CHP of the k-th iteration of the t-th future time period i,t,k P2G,1 λ represents the Lagrange multiplier term coefficient of the electrical-thermal system of the electrical-thermal integrated energy system in the i-th P2G of the k-th iteration of the t-th future time period i,t,k CHP,2 λ represents the Lagrange dual multiplier of the natural gas of the electrical-thermal integrated energy system in the i-th CHP of the k-th iteration of the t-th future time period i,t,k P2G,2 h represents the Lagrange dual multiplier of the natural gas system of the electrical-thermal integrated energy system in the i-th P2G of the k-th iteration of the t-th future time period i,t,k CHP,2 h represents the Lagrange multiplier term coefficient of the natural gas system of the electrical-thermal integrated energy system in the i-th CHP of the k-th iteration of the t-th future time period i,t,k P2G,2 P represents the Lagrange multiplier term coefficient of the natural gas system of the electrical-thermal integrated energy system in the i-th P2G of the k-th iteration of the t-th future time period i,t,k CHP,1 P represents the output active power of the i-th CHP at the t-th future time in the electrical-thermal coupled device obtained by solving the electrical-thermal system target model of the electrical-thermal integrated energy system for the k-th iteration of the alternating optimization iteration i,t,k CHP,2 P represents the output active power of the i-th CHP at the t-th future time in the electrical-thermal coupled device obtained by solving the natural gas system target model of the electrical-thermal integrated energy system for the k-th iteration of the alternating optimization iteration i,t,k P2G,1 P represents the output active power of the i-th P2G at the t-th future time in the electrical-thermal coupled device obtained by solving the electrical-thermal system target model of the electrical-thermal integrated energy system for the k-th iteration of the alternating optimization iteration i,t,k CHP,2 N represents the output active power of the i-th P2G at the t-th future time in the electrical-thermal coupled device obtained by solving the natural gas system target model of the electrical-thermal integrated energy system for the k-th iteration of the alternating optimization iterationP2G N represents the number of P2G in the electrical coupling device CHP T represents the number of future time, N represents the number of CHP in the electrical-thermal coupling device is the expression of "all" in mathematics, which represents that each number in the interval satisfies the constraint;

[0116] Step 5 obtains the solved variables of the comprehensive energy system at multiple prediction times;

[0117] The solved variables of the comprehensive energy system at multiple prediction times include:

[0118] P represents the output active power of the gth generator at the tth future time in the power system model after the electrical-thermal comprehensive energy system model is solved g,t gen,* ,g∈[1,G],t∈[1,T];P represents the output reactive power of the gth generator at the tth future time in the power system model after the electrical-thermal comprehensive energy system model is solved g,t gen,* P represents the output active power of the wth wind farm at the tth future time in the power system model after the electrical-thermal comprehensive energy system model is solved w,t wind,* ,w∈[1,W],t∈[1,T];P represents the output reactive power of the wth wind farm at the tth future time in the power system model after the electrical-thermal comprehensive energy system model is solved w,t wind,* P represents the output active power of the ith CHP at the tth future time in the electrical-thermal coupling device after the electrical-thermal comprehensive energy system model is solved i,t CHP,* ,i∈[1,N CHP ],t∈[1,T];P represents the output reactive power of the ith CHP at the tth future time in the electrical-thermal coupling device after the electrical-thermal comprehensive energy system model is solved i,t CHP,* ,i∈[1,N CHP ],t∈[1,T];H represents the output heat power of the ith CHP at the tth future time in the electrical-thermal coupling device after the electrical-thermal comprehensive energy system model is solved i,t CHP,* ,i∈[1,N CHP ],t∈[1,T];F represents the input gas flow of the ith CHP at the tth future time in the electrical-thermal coupling device after the electrical-thermal comprehensive energy system model is solved i,t CHP,* ,i∈[1,N CHP ],t∈[1,T];P represents the input active power of the ith P2G at the tth future time in the electrical coupling device after the electrical-thermal comprehensive energy system model is solvedi,t P2G,* i∈[1,N P2G ],t∈[1,T];the output gas flow rate of the ith P2G in the electrical coupling device at the tth future time after the electrical heat integrated energy system model is solved i,t P2G,* i∈[1,N P2G ],t∈[1,T];the output gas flow rate of the wth gas source in the natural gas system model at the tth future time after the electrical heat integrated energy system model is solved w,t sup,* w∈[1,W sup ],t∈[1,T];the total operation cost f1 of the electrical heat system after the electrical heat integrated energy system model is solved * ; the total operation cost f2 of the natural gas system after the electrical heat integrated energy system model is solved * ; W represents the number of wind farms in the power transmission system model, G represents the number of generators in the power transmission system model, W sup represents the number of gas source points in the natural gas system model, N P2G represents the number of P2Gs in the electrical coupling device, N CHP represents the number of CHPs in the electrical heat coupling device, and T represents the number of future times.

[0119] The application also provides an advanced scheduling system for an electrical heat integrated energy system, which comprises:

[0120] An electrical heat integrated energy system model construction module, which couples the power transmission system model and the heat supply system model through electrical heat coupling devices, and couples the power transmission system model and the electrical heat system model through electrical coupling devices;

[0121] A load prediction module, which predicts electrical loads, heat loads, and gas loads at multiple future times through long short-term memory artificial neural networks, respectively;

[0122] A constraint construction module, which constructs system backup constraints, generator set operation constraints, wind farm operation constraints, power network constraints, heat system operation constraints, gas source point constraints, pipeline constraints, and node supply-demand balance constraints, and establishes coupling device constraints;

[0123] A system optimization target construction module, which constructs an electrical heat system target model and a natural gas system target model of the electrical heat integrated energy system, respectively;

[0124] An alternating iterative optimization solving module, which performs optimization and solving through an alternating iterative optimization method to obtain solved variables of the electrical heat integrated energy system at multiple predicted times.

[0125] The application further provides a computer readable medium storing a computer program executed by an electronic device, which, when running on the electronic device, causes the electronic device to execute the steps of the device maintenance workshop scheduling optimization method.

[0126] The application has the following advantages:

[0127] The active power loss and the reactive power loss in the power system in the electrical thermal comprehensive energy system are considered, and the model has high accuracy;

[0128] The calculation resources of the upper dispatching center are saved, and the data privacy of the subsystem is ensured;

[0129] The electrical thermal system model and the natural gas system model are both converted into mixed integer linear programming problems, and the sub-problem solving speed is fast;

[0130] The convergence performance is good, and the time cost and the communication cost are low. BRIEF DESCRIPTION OF DRAWINGS

[0131] Figure 1 The method flowchart of the embodiment of the application. DETAILED DESCRIPTION

[0132] The technical solutions in the embodiments of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative work are within the protection scope of the application.

[0133] In the implementation, the method proposed in the technical solutions of the application can be automatically run by computer software technology, and the system device of the method, such as the computer readable storage medium storing the corresponding computer program of the technical solutions of the application and the computer device including the running corresponding computer program, should also be within the protection scope of the application.

[0134] The technical solutions of the method of the embodiments of the application are described below. Figure 1 The technical solutions of the method of the embodiments of the application are described below.

[0135] Step 1: build a power transmission system model, a heat supply system model, and a natural gas system model, obtain the electric load of each power node in the power transmission system model at multiple historical time points, the output of each wind farm in the power transmission system model at multiple historical time points, the heat load of each heat node in the heat supply system model at multiple historical time points, and the gas load of each natural gas node in the natural gas system model at multiple historical time points, respectively couple the power transmission system model and the heat supply system model through an electric-thermal coupling device, couple the power transmission system model and the electric-thermal system model through an electrical coupling device, build an electric-thermal system model, and build an electrical and thermal integrated energy system model;

[0136] The number of power nodes in the power transmission system model in step 1 is N = 24;

[0137] The number of wind farms in the power transmission system model in step 1 is W = 4;

[0138] The number of heat nodes in the heat supply system model in step 1 is H = 32;

[0139] The number of natural gas nodes in the natural gas system model in step 1 is S = 20;

[0140] Step 2: obtain the predicted electric load of each power node in the power transmission system model at multiple future time points by predicting the electric load of each power node in the power transmission system model at multiple historical time points through a long short-term memory artificial neural network, obtain the active predicted power of each wind farm in the power transmission system model at multiple future time points according to the output of each wind farm in the power transmission system model at multiple historical time points, obtain the predicted heat load of each heat node in the heat supply system model at multiple future time points by predicting the heat load of each heat node in the heat supply system model at multiple historical time points through a long short-term memory artificial neural network, and obtain the predicted gas load of each natural gas node in the natural gas system model at multiple future time points by predicting the gas load of each natural gas node in the natural gas system model at multiple future time points through a long short-term memory artificial neural network;

[0141] The number of future time points in step 2 is T;

[0142] The predicted electric load of each power node in the power transmission system model at multiple future time points in step 2 is specifically defined as follows:

[0143] P n,t load

[0144] n∈[1,N],t∈[1,T]

[0145] Wherein, N = 33 represents the number of power nodes in the power transmission system model, T represents the number of future time points, P n,t loadPn,t represents the predicted electrical load of the nth power node in the power transmission system model at the tth future time;

[0146] Pn,t represents the predicted electrical load of the nth power node in the power transmission system model at the tth future time;

[0147] Pn,t represents the predicted electrical load of the nth power node in the power transmission system model at the tth future time; w,t 0

[0148] w∈[1,W],t∈[1,T]

[0149] wherein W=4 represents the number of wind farms in the power transmission system model, T represents the number of future time, P w,t 0 Pw,t represents the predicted wind power of the wth wind farm in the power transmission system model at the tth future time;

[0150] Pn,t represents the predicted electrical load of the nth power node in the power transmission system model at the tth future time;

[0151] Pn,t represents the predicted electrical load of the nth power node in the power transmission system model at the tth future time; h,t load

[0152] h∈[1,H],t∈[1,T]

[0153] wherein H=32 represents the number of heat nodes in the heat system model, T represents the number of future time, H h,t load Ph,t represents the predicted heat load of the hth heat node in the heat system model at the tth future time;

[0154] Pn,t represents the predicted electrical load of the nth power node in the power transmission system model at the tth future time;

[0155] Pn,t represents the predicted electrical load of the nth power node in the power transmission system model at the tth future time; s,t load

[0156] s∈[1,S],t∈[1,T]

[0157] wherein S=20 represents the number of gas nodes in the gas system model, T represents the number of future time, F s,t load Ps,t represents the predicted heat load of the st gas node in the gas system model at the tth future time;

[0158] Step 3: sequentially build system reserve constraints, generator set operation constraints, wind farm operation constraints, and power network constraints in combination with the active predicted power of each wind farm at multiple future time points in the power transmission system model and the predicted electric load of each power node at multiple future time points, build thermal system operation constraints in combination with the predicted thermal load of each thermal node at multiple future time points in the thermal system model, sequentially build gas source point constraints, pipeline constraints, and node supply-demand balance constraints in combination with the predicted gas load of each gas node at multiple future time points in the natural gas system model, and establish coupling device constraints;

[0159] The system reserve constraints in step 3 are specifically defined as follows:

[0160]

[0161]

[0162] wherein x g,t gen represents a 0 / 1 indicator variable for the gth generator connected to the grid at the tth future time point in the power transmission system model, x i,t CHP represents a 0 / 1 indicator variable for the ith CHP connected to the grid at the tth future time point in the electric-thermal coupling device, P g gen,max and P g gen,min are the maximum technical output and the minimum technical output of the gth generator in the power transmission system model, P g CHP,max and P g CHP,min represent the maximum technical output and the minimum technical output of the ith CHP in the electric-thermal coupling device, P w,t wind represents the output active power of the wth wind farm at the tth future time point in the power transmission system model, r load represents the error of the electric load prediction of each power load node in the power transmission system model, r wind represents the error of the wind power prediction of each wind farm in the power transmission system model, P n,t load represents the predicted electric load of the nth power node at the tth future time point in the power transmission system model, G represents the number of generators in the power transmission system model, W represents the number of wind farms in the power transmission system model, N CHP represents the number of CHPs in the electric-thermal coupling device, N is the number of power nodes in the power transmission system model, and T represents the number of future time points, represents that each number in the interval satisfies the range constraint;

[0163] The generator set operation constraints in step 3 are specifically defined as follows:

[0164]

[0165]

[0166]

[0167]

[0168]

[0169] where x g,t gen x g,t-1 gen x g,w gen T g gen,st and T g gen,sd and P g gen,max and P g gen,min and P g,t gen P g,t-1 gen Q g,t gen Q and and r g gen,up and r g gen,dn and ||·||2denote the upper and lower ramping limits of the gth generator, respectively, ||·||2denotes the mathematical 2-norm calculation formula, G denotes the number of generators in the power system model, and T denotes the number of future time instants,

[0170] ​The wind farm operation constraints in step 3 are defined as follows:

[0171]

[0172] where P w,t wind represents the active output power of the wth wind farm at the tth future time in the power transmission system model, P w,t 0 represents the active prediction power of the wth wind farm at the tth future time in the power transmission system model, Q w,t wind represents the reactive output power of the wth wind farm at the tth future time in the power transmission system model, represents the lower limit of the grid-connected power factor angle of each wind farm in the power transmission system model, arccos represents the cosine angle calculation, tan represents the sine calculation, W represents the number of wind farms in the power transmission system model, and T represents the number of future times, represents that each number in the interval satisfies the range constraint;

[0173] The power network constraints in step 3 are defined as follows:

[0174]

[0175]

[0176] 0≤Q n,t com ≤Q n com,max ,n∈[1,N]

[0177]

[0178]

[0179]

[0180]

[0181]

[0182]

[0183]

[0184] where P i,t CHP , Q i,t CHP represent the output active power and the output reactive power of the ith CHP at the tth future time in the electric-thermal coupling device, P i,tP2G Pit(t) represents the input active power of the ith P2G at the tth future time in the electrical coupling device, g,t gen and Q g,t gen Pgt(t) and Qgt(t) represent the output active power and output reactive power of the gth generator at the tth future time in the power transmission system model, respectively, w,t wind and Q w,t wind Pwt(t) and Qwt(t) represent the output active power and output reactive power of the wth wind farm at the tth future time in the power transmission system model, respectively, l,t line and Q l,t line Pit(t) and Qit(t) represent the sending-end active power and sending-end reactive power of the ith transmission line at the tth future time in the power transmission system model, respectively, l,t line and Q l,t line Pit(t) and Qit(t) represent the active power loss and reactive power loss of the ith transmission line at the tth future time in the power transmission system model, respectively, n,t load Pn(t) represents the predicted electric load of the nth electric power node at the tth future time in the power transmission system model, Qn(t) represents the power factor angle of the nth electric power node at the tth future time in the power transmission system model, n,t com Qn(t) represents the reactive compensation power of the nth electric power node at the tth future time in the power transmission system model, n com,max Qn,max represents the maximum reactive compensation power of the nth electric power node in the power transmission system model, l,t + and Q l,t + and Q l,t + and Q l,t + and Q l and Q l and Q l,max S represents the rated transmission capacity of the ith transmission line in the power transmission system model, n,t Q represents the voltage phase angle of the nth electric power node at the tth future time in the power transmission system model, n min and Q n maxrespectively represent the minimum and maximum value of the voltage amplitude of the nth power node in the power transmission system model, θ l,slack t represent the phase angle difference △θ of the lth transmission line in the power transmission system model at the tth future time l,t the square of the relaxation amount, △θ l max represent the maximum value of the absolute value of the phase angle difference △θ of the lth transmission line in the power transmission system model l,t,i represent the phase angle difference △θ of the lth transmission line in the power transmission system model at the tth future time l,t the slope of the ith segment, N sl represent the number of segments of the square of the phase angle difference of each transmission line in the power transmission system model at each future time, TC l,t,i represent the phase angle difference △θ of the lth transmission line in the power transmission system model at the tth future time l,t the value of the ith segment point, N n CHP represent the number of CHPs connected to the nth power node in the power transmission system model, N n P2G represent the number of P2Gs connected to the nth power node in the power transmission system model, N n G represent the number of generators connected to the nth power node in the power transmission system model, N n W represent the number of wind farms connected to the nth power node in the power transmission system model, N n l(+) represent the number of transmission lines with the nth power node as the sending end in the power transmission system model, N n l(-) represent the number of transmission lines with the nth power node as the receiving end in the power transmission system model, L ele represent the number of transmission lines in the power transmission system model, N is the number of power nodes in the power transmission system model, T represents the number of future times, ||·||2 represents the mathematical 2-norm calculation formula, represent that each number in the interval satisfies the range constraint;

[0185] The thermal system model operation constraint in step 3 is specifically defined as follows:

[0186]

[0187]

[0188]

[0189]

[0190] Among them, H h,t load It represents the predicted heat load of the hth thermal node at the tth future moment in the thermal system model, H i,t CHP represents the output thermal power of the ith CHP at the tth future moment in the coupled equipment model, C P Represents the specific heat capacity of water in the thermal system model, m h,t q T represents the water quality injection rate of the hth thermal node in the thermal system model at the tth future moment, h,t s T represents the water supply temperature of the hth thermal node in the thermal system model at the tth future moment, h,t r represents the return water temperature of the hth thermal node in the thermal system model at the tth future moment, T h s,min and T h s,max The lower and upper limits of the water supply temperature of the hth thermal node in the thermal system model, T h r,min and T h r,max The lower and upper limits of the return water temperature of the hth thermal node in the thermal system model, T l,t - and T l,t + They represent the temperatures of the receiving and sending ends of the lth heating pipe in the thermal system model at the tth future moment, e represents the base of the natural logarithm function, m l,t represents the water mass flow rate of the lth heating pipe in the thermal system model at the tth future moment, λ l heat represents the heat transfer coefficient of the lth heating pipe in the thermal system model, T t a Indicates the ambient temperature of the thermal system model at the tth future moment, len l represents the length of the first heating pipe in the thermal system model, H h l(+) Indicates the number of heating pipes with the nth thermal node in the thermal system model as the sending end, H h l(-) Indicates the number of heating pipes with the nth thermal node in the thermal system model as the receiving end, H h CHP Indicates the number of CHPs connected to the nth thermal node in the thermal system model, L heat Represents the number of heating pipes in the thermal system model, H represents the number of thermal nodes in the thermal system model, and T represents the number at the future time. each number in the interval satisfies the range constraint;

[0191] The gas source point constraint in step 3 is specifically defined as follows:

[0192]

[0193] wherein F w,t sup represents the output gas flow of the wth gas source at the tth future time in the natural gas system model, F w sup ,min and F w sup,max respectively represent the minimum value and the maximum value of the output gas flow of the wth gas source in the natural gas system model, W sup represents the number of gas source points in the natural gas system model, and T represents the number of future times;

[0194] The pipeline constraint in step 3 is specifically defined as follows:

[0195]

[0196]

[0197]

[0198]

[0199]

[0200]

[0201]

[0202] wherein the symbol |·| represents a mathematical absolute value calculation formula, ||·||2 represents a mathematical 2-norm calculation formula, F l,t line represents the gas flow of the lth gas supply pipeline at the tth future time in the natural gas system model, k l line represents the transmission coefficient of the lth gas supply pipeline in the natural gas system model, pg l,t + and pg l,t - respectively represent the sending end and the receiving end gas pressure of the lth gas supply pipeline at the tth future time in the natural gas system model, F l line,max represents the maximum allowable gas flow of the lth gas supply pipeline in the natural gas system model, pg l +,min and pg l+,max They represent the lower and upper limits of the gas pressure at the delivery end of the lth gas supply pipeline in the natural gas system model, pg l -,min and pg l -,max They represent the lower and upper limits of the receiving pressure of the lth gas supply pipeline in the natural gas system model, respectively, and x l,t + and x l,t -- They represent the positive and negative flow direction indicators of the water quality at the tth future moment in the lth gas supply pipeline in the natural gas system model, respectively. Indicates the auxiliary constant for judging the water quality flow direction of the lth gas supply pipeline at each moment in the natural gas system model, It represents the auxiliary variable for judging the first water quality flow direction of the lth gas supply pipeline at the tth future moment in the natural gas system model. represents the auxiliary variable for judging the second water quality flow direction of the lth gas supply pipeline at the tth future moment in the natural gas system model, β l,t i It represents the third auxiliary variable for judging the water quality flow direction of the lth gas supply pipeline at the tth future moment in the natural gas system model. represents the fourth water quality flow direction judgment auxiliary variable of the lth gas supply pipeline at the tth future moment in the natural gas system model, M represents the auxiliary constant in the natural gas system model, L gas represents the number of gas supply pipelines in the natural gas system model, T represents the number at the future time, Indicates that every number in the interval satisfies the range constraint;

[0203] The node supply and demand balance constraint described in step 3 is specifically defined as follows:

[0204]

[0205] Among them, F w,t sup represents the output gas flow of the wth gas source at the tth future moment in the natural gas system model, F l,t line represents the gas flow of the lth gas supply pipeline at the tth future moment in the natural gas system model, F i,t P2G represents the gas flow of the tth future moment of the i-th P2G in the coupling device model, F i,t CHP represents the air flow of the ith CHP at the tth future moment in the coupled equipment model, F s,t load represents the predicted heat load of the sth natural gas node at the tth future moment in the weather gas system model, S s supS represents the number of gas sources connected to the s-th natural gas node in the natural gas system model s l(+) S represents the number of gas supply pipelines with the s-th natural gas node as the sending end in the natural gas system model s l(-) S represents the number of gas supply pipelines with the s-th natural gas node as the receiving end in the natural gas system model s P2G S represents the number of P2G connected to the s-th natural gas node in the natural gas system model s CHP S represents the number of CHP connected to the s-th natural gas node in the natural gas system model Each number in the interval satisfies the range constraint.

[0206] The coupling device constraint in step 3 is defined as follows:

[0207]

[0208]

[0209]

[0210]

[0211]

[0212]

[0213] wherein P i,t CHP , Q i,t CHP , F i,t CHP and H i,t CHP represent the output active power, output reactive power, input gas flow and output heat power of the i-th CHP at the t-th future time in the electro-thermal coupling device, HV g RHE i CHP represents the thermal-electric ratio of the i-th CHP at each future time in the electro-thermal coupling device; η i CHP represents the energy conversion efficiency of the i-th CHP at each future time in the electro-thermal coupling device, P i,t-1 CHP represents the output active power of the i-th CHP at the t-1-th future time in the electro-thermal coupling device, x i,t CHPx i,t-1 CHP x i,w CHP x i CHP,st and T i CHP,sd P i CHP ,max P i CHP,min P and r i CHP,up r i CHP,dn N CHP N Each number in the interval satisfies the range constraint.

[0214]

[0215] P i,t P2G F i,t P2G P g HV i η P2G N P2G N Each number in the interval satisfies the range constraint.

[0216] Step 4: Build the electrical-thermal system target model of the electrical-thermal integrated energy system, and the natural gas system target model of the electrical-thermal integrated energy system;

[0217] The electrical heat system target model of the electrical heat comprehensive energy system in step 4 is specifically defined as follows:

[0218]

[0219] Wherein, f1 represents the total operation cost of the electrical heat system of the electrical heat comprehensive energy system, C1 represents the sum of the generator start-up cost and the CHP start-up cost of the electrical heat system of the electrical heat comprehensive energy system, C2 represents the sum of the variable cost of the generator and the variable cost of the CHP of the electrical heat system of the electrical heat comprehensive energy system, C3 represents the abandoned wind penalty cost of the electrical heat system of the electrical heat comprehensive energy system, C g gen,st represents the single start-up cost of the gth generator of the electrical heat system of the electrical heat comprehensive energy system, C i CHP,st represents the single start-up cost of the ith CHP of the electrical heat system of the electrical heat comprehensive energy system, a g gen , b g gen and c g gen respectively represent the linear term, the quadratic term and the constant term coefficient of the variable cost of the gth generator of the electrical heat system of the electrical heat comprehensive energy system, a i CHP , b i CHP and c i CHP respectively represent the linear term, the quadratic term and the constant term coefficient of the variable cost of the ith CHP of the electrical heat system of the electrical heat comprehensive energy system, x g,t gen represents the 0 / 1 indication variable of the gth generator of the power transmission system model connected to the grid at the tth future time, x g,t-1 gen represents the 0 / 1 indication variable of the gth generator of the power transmission system model connected to the grid at the (t-1)th future time, x i,t CHP represents the 0 / 1 indication variable of the ith CHP of the electrical heat coupling device connected to the grid at the tth future time, x i,t-1 CHP represents the 0 / 1 indication variable of the ith CHP of the electrical heat coupling device connected to the grid at the (t-1)th future time, P g,t gen represents the active power output and the reactive power output of the gth generator of the power transmission system model at the tth future time, P i,t CHP represents the active power output of the ith CHP of the electrical heat coupling device at the tth future time, P w,t windPw,t represents the active power output of the wth wind farm at the tth future time in the power transmission system model w,t 0 Ww,t represents the predicted active power of the wth wind farm at the tth future time in the power transmission system model punish N represents the unit wind curtailment penalty cost in the power transmission system model CHP G represents the number of CHPs in the electrical-thermal coupled device, G represents the number of generators in the power transmission system model, W represents the number of wind farms in the power transmission system model, and T represents the number of future times Each number in the interval satisfies the range constraint

[0220] The natural gas system target model of the electrical-thermal comprehensive energy system in step 4 is specifically defined as follows:

[0221]

[0222] In the formula, f2 represents the total operation cost of the weather gas system of the electrical-thermal comprehensive energy system, C N1 C represents the total gas source operation cost of the natural gas system of the electrical-thermal comprehensive energy system N2 C represents the total P2G operation cost of the natural gas system of the electrical-thermal comprehensive energy system w sup Cw,t represents the unit operation cost of the wth gas source of the natural gas system of the electrical-thermal comprehensive energy system at each future time i P2G F represents the unit operation cost of the ith P2G of the natural gas system of the electrical-thermal comprehensive energy system at each future time w,t sup Fw,t represents the output gas flow of the wth gas source at the tth future time in the natural gas system model i,t P2G W represents the output gas flow of the ith P2G at the tth future time in the electrical-thermal coupled device sup N represents the number of gas source points in the natural gas system model P2G G represents the number of P2Gs in the electrical-thermal coupled device, and T represents the number of future times Each number in the interval satisfies the range constraint

[0223] Step 5: build the coupling device constraint, take the electrical heat system target model of the electrical heat integrated energy system and the natural gas system target model of the electrical heat integrated energy system as the optimization target, build the electrical heat system target model of the electrical heat integrated energy system for the alternating optimization iteration, build the natural gas system target model of the electrical heat integrated energy system for the alternating optimization iteration, and obtain the solved variables of the electrical heat integrated energy system at multiple prediction times through the alternating iterative optimization method, so as to realize the advanced scheduling of the electrical heat integrated energy system through the solved variables of the electrical heat integrated energy system at multiple prediction times.

[0224] Step 5: build the electrical heat system target model of the electrical heat integrated energy system for the alternating optimization iteration, and the specific definition is as follows:

[0225]

[0226] Wherein, f1 represents the total operation cost of the electrical heat system of the electrical heat integrated energy system, λ i,t CHP,1 represents the Lagrange dual multiplier of the ith CHP of the electrical heat system of the electrical heat integrated energy system at the tth future period, λ i,t P2G,1 represents the Lagrange dual multiplier of the ith P2G of the electrical heat system of the electrical heat integrated energy system at the tth future period, h i,t CHP,1 represents the Lagrange penalty term coefficient of the ith CHP of the electrical heat system of the electrical heat integrated energy system at the tth future period, h i,t P2G,1 represents the Lagrange penalty term coefficient of the ith P2G of the electrical heat system of the electrical heat integrated energy system at the tth future period, P i,t CHP,1 represents the output active power of the ith CHP of the electrical heat coupling device at the tth future time obtained by solving the electrical heat system target model of the electrical heat integrated energy system for the alternating optimization iteration, P i,t CHP,2 represents the output active power of the ith CHP of the electrical heat coupling device at the tth future time obtained by solving the natural gas system target model of the electrical heat integrated energy system for the alternating optimization iteration, P i,t P2G,1 represents the output active power of the ith P2G of the electrical heat coupling device at the tth future time obtained by solving the electrical heat system target model of the electrical heat integrated energy system for the alternating optimization iteration, P i,t CHP,2 represents the output active power of the ith P2G of the electrical heat coupling device at the tth future time obtained by solving the natural gas system target model of the electrical heat integrated energy system for the alternating optimization iteration, N P2GN represents the number of P2G in the electrical-thermal coupling device CHP N represents the number of CHP in the electrical-thermal coupling device, and T represents the number of future time periods

[0227] Step 5: Establishing an electrical-thermal system target model of the electrical-thermal integrated energy system for alternating optimization iteration, which is specifically defined as follows:

[0228]

[0229] wherein f2 represents the total operation cost of the natural gas system of the electrical-thermal integrated energy system, λ i,t CHP,2 λ represents the Lagrange dual multiplier of the ith CHP of the natural gas system of the electrical-thermal integrated energy system in the tth future time period i,t P2G,2 h represents the Lagrange dual multiplier of the ith P2G of the natural gas system of the electrical-thermal integrated energy system in the tth future time period i,t CHP,2 h represents the Lagrange penalty term coefficient of the ith CHP of the natural gas system of the electrical-thermal integrated energy system in the tth future time period i,t P2G,2 P represents the Lagrange penalty term coefficient of the ith P2G of the natural gas system of the electrical-thermal integrated energy system in the tth future time period i,t CHP,1 P represents the output active power of the ith CHP of the electrical-thermal coupling device in the tth future time period obtained by solving the electrical-thermal system target model of the electrical-thermal integrated energy system for alternating optimization iteration i,t CHP,2 P represents the output active power of the ith CHP of the electrical-thermal coupling device in the tth future time period obtained by solving the natural gas system target model of the electrical-thermal integrated energy system for alternating optimization iteration i,t P2G,1 P represents the output active power of the ith P2G of the electrical-thermal coupling device in the tth future time period obtained by solving the electrical-thermal system target model of the electrical-thermal integrated energy system for alternating optimization iteration i,t CHP,2 N represents the output active power of the ith P2G of the electrical-thermal coupling device in the tth future time period obtained by solving the natural gas system target model of the electrical-thermal integrated energy system for alternating optimization iteration P2G N represents the number of P2G in the electrical-thermal coupling device CHP N represents the number of CHP in the electrical-thermal coupling device, and T represents the number of future time periods

[0230] Step 5: Obtaining the solved variables of the electrical-thermal integrated energy system at multiple prediction time periods by optimization solving through the alternating iteration optimization method, and the specific process is as follows:

[0231] Step 5.1, initialize the iteration number k = 1, initialize the Lagrange dual multiplier λ of the electric heat system of the electric heat integrated energy system in the i-th CHP in the t-th future time period of the k-th iteration i,t,k CHP,1 , initialize the Lagrange dual multiplier λ of the electric heat system of the electric heat integrated energy system in the i-th P2G in the t-th future time period of the k-th iteration i,t,k P2G,1 , initialize the Lagrange penalty term coefficient h of the electric heat system of the electric heat integrated energy system in the i-th CHP in the t-th future time period of the k-th iteration i,t,k CHP,1 , initialize the Lagrange penalty term coefficient h of the electric heat system of the electric heat integrated energy system in the i-th P2G in the t-th future time period of the k-th iteration i,t,k P2G,1 , initialize the Lagrange dual multiplier λ of the natural gas system of the electric heat integrated energy system in the i-th CHP in the t-th future time period of the k-th iteration i,t,k CHP,2 , initialize the Lagrange dual multiplier λ of the natural gas system of the electric heat integrated energy system in the i-th P2G in the t-th future time period of the k-th iteration i,t,k P2G,2 , initialize the Lagrange penalty term coefficient h of the natural gas system of the electric heat integrated energy system in the i-th CHP in the t-th future time period of the k-th iteration i,t,k CHP,2 , initialize the Lagrange penalty term coefficient h of the natural gas system of the electric heat integrated energy system in the i-th P2G in the t-th future time period of the k-th iteration i,t,k P2G,2 , initialize the output active power P of the i-th CHP in the t-th future time in the electric heat coupling device obtained by solving the electric heat system target model of the electric heat integrated energy system for alternating optimization iteration in the k-th iteration i,t,k CHP,1 , initialize the output active power P of the i-th CHP in the t-th future time in the electric heat coupling device obtained by solving the natural gas system target model of the electric heat integrated energy system for alternating optimization iteration in the k-th iteration i,t,k CHP,2 , initialize the output active power P of the i-th P2G in the t-th future time in the electric coupling device obtained by solving the electric heat system target model of the electric heat integrated energy system for alternating optimization iteration in the k-th iteration i,t,k P2G,1 , initialize the output active power P of the i-th P2G in the t-th future time in the electric heat coupling device obtained by solving the natural gas system target model of the electric heat integrated energy system for alternating optimization iteration in the k-th iteration i,t,kCHP,2 , initialize the convergence threshold ε of the iterative calculation of the electrical-thermal integrated energy system;

[0232] Step 5.2, the electrical-thermal system scheduling center solves the electrical-thermal system target model of the electrical-thermal integrated energy system for the alternating optimization iteration based on the electrical-thermal system target model of the electrical-thermal integrated energy system for the alternating optimization iteration, and the system backup constraint, the generator set operation constraint, the wind farm operation constraint, the power network constraint, and the heating system operation constraint, to obtain the output active power P of the i-th CHP in the electrical-thermal coupled device at the t-th future time of the k-th iteration of the electrical-thermal system target model of the electrical-thermal integrated energy system for the alternating optimization iteration by solving by the interior point method. i,t,k CHP,1 , and the output active power P of the i-th P2G in the electrical-coupled device at the t-th future time of the k-th iteration of the electrical-thermal system target model of the electrical-thermal integrated energy system for the alternating optimization iteration. i,t,k P2G,1 , wherein N P2G represents the number of P2Gs in the electrical-coupled device, N CHP represents the number of CHPs in the electrical-thermal coupled device, and T represents the number of future times, is the expression of "all" in mathematics, indicating that each number in the interval satisfies the constraint;

[0233] Step 5.3, the natural gas system scheduling center solves the natural gas system target model of the electrical-thermal integrated energy system for the alternating optimization iteration based on the natural gas system target model of the electrical-thermal integrated energy system for the alternating optimization iteration, and the gas source point constraint, the pipeline constraint, and the node supply-demand balance constraint, to obtain the output active power P of the i-th CHP in the electrical-thermal coupled device at the t-th future time of the k-th iteration of the natural gas system target model of the electrical-thermal integrated energy system for the alternating optimization iteration by solving by the interior point method. i,t,k CHP,2 , and the output active power P of the i-th P2G in the electrical-coupled device at the t-th future time of the k-th iteration of the natural gas system target model of the electrical-thermal integrated energy system for the alternating optimization iteration. i,t,k P2G,2 , wherein N P2G represents the number of P2Gs in the electrical-coupled device, N CHP represents the number of CHPs in the electrical-thermal coupled device, and T represents the number of future times, is the expression of "all" in mathematics, indicating that each number in the interval satisfies the constraint;

[0234] Step 5.4, the upper scheduling center judges whether the iteration process converges according to the convergence criterion, if converges, the upper scheduling center issues a converged signal, the algorithm stops, and the solved variables of the electrical heat comprehensive energy system at multiple prediction times are obtained. If not converges, let k=k+1, the upper scheduling center updates the operator according to the operator updating model and issues it, and then transposes to step 5.2;

[0235] The convergence criterion in step 5.4 is specifically defined as follows:

[0236]

[0237] Wherein, the symbol |·| represents the mathematical absolute value calculation formula, P i,t,k CHP,1 represents the output active power of the i-th CHP at the t-th future time in the electrical heat coupled device obtained by the k-th iteration solution of the electrical heat system target model of the electrical heat comprehensive energy system for alternating optimization iteration, P i,t,k CHP,2 represents the output active power of the i-th CHP at the t-th future time in the electrical heat coupled device obtained by the k-th iteration solution of the natural gas system target model of the electrical heat comprehensive energy system for alternating optimization iteration, P i,t,k P2G , 1表 represents the output active power of the i-th P2G at the t-th future time in the electrical heat coupled device obtained by the k-th iteration solution of the electrical heat system target model of the electrical heat comprehensive energy system for alternating optimization iteration, P i,t,k CHP,2 represents the output active power of the i-th P2G at the t-th future time in the electrical heat coupled device obtained by the k-th iteration solution of the natural gas system target model of the electrical heat comprehensive energy system for alternating optimization iteration, N P2G represents the number of P2G in the electrical coupled device, N CHP represents the number of CHP in the electrical heat coupled device, and T represents the number of future times, is the expression of "all" in mathematics, which means that each number in the interval satisfies the constraint;

[0238] The Lagrange dual multiplier λ of the i-th CHP at the t-th future period in the k-th iteration of the electrical heat system of the electrical heat comprehensive energy system is updated through the operator updating model i,t,k CHP,1 , the Lagrange dual multiplier λ of the i-th P2G at the t-th future period in the k-th iteration of the electrical heat system of the electrical heat comprehensive energy system is updated through the operator updating model i,t,k P2G,1 , the Lagrange penalty coefficient h of the i-th CHP at the t-th future period in the k-th iteration of the electrical heat system of the electrical heat comprehensive energy system is updated through the operator updating model i,t,k CHP,1, Lagrange multiplier term coefficient h of the electric heating system of the electric heating integrated energy system in the i-th P2G in the t-th future period of the k-th iteration i,t,k P2G,1 , Lagrange dual multiplier λ of the natural gas system of the electric heating integrated energy system in the i-th CHP in the t-th future period of the k-th iteration i,t,k CHP,2 , Lagrange dual multiplier λ of the natural gas system of the electric heating integrated energy system in the i-th P2G in the t-th future period of the k-th iteration i,t,k P2G,2 , Lagrange multiplier term coefficient h of the natural gas system of the electric heating integrated energy system in the i-th CHP in the t-th future period of the k-th iteration i,t,k CHP,2 , Lagrange multiplier term coefficient h of the natural gas system of the electric heating integrated energy system in the i-th P2G in the t-th future period of the k-th iteration i,t,k P2G,2 , and the specific definitions are as follows:

[0239]

[0240]

[0241]

[0242]

[0243] Wherein, β represents the Lagrange multiplier term coefficient update factor in the electric heating integrated energy system, λ i,t,k+1 CHP,1 represents the Lagrange dual multiplier of the electric heating system of the electric heating integrated energy system in the i-th CHP in the t-th future period of the k+1-th iteration, λ i,t,k+1 P2G,1 represents the Lagrange dual multiplier of the electric heating system of the electric heating integrated energy system in the i-th P2G in the t-th future period of the k+1-th iteration, h i,t,k+1 CHP,1 represents the Lagrange multiplier term coefficient of the electric heating system of the electric heating integrated energy system in the i-th CHP in the t-th future period of the k+1-th iteration, h i,t,k+1 P2G,1 represents the Lagrange multiplier term coefficient of the electric heating system of the electric heating integrated energy system in the i-th P2G in the t-th future period of the k+1-th iteration, λ i,t,k+1 CHP,2 represents the Lagrange dual multiplier of the natural gas system of the electric heating integrated energy system in the i-th CHP in the t-th future period of the k+1-th iteration, λ i,t,k+1 P2G,2λk+1,i,t represents the Lagrange dual multiplier of the natural gas system of the electrical-thermal integrated energy system in the i-th P2G in the t-th future time period of the k+1-th iteration, h i,t,k+1 CHP,2 hk+1,i,t represents the Lagrange penalty term coefficient of the natural gas system of the electrical-thermal integrated energy system in the i-th CHP in the t-th future time period of the k+1-th iteration, h i,t,k+1 P2G,2 hk+1,i,t represents the Lagrange penalty term coefficient of the natural gas system of the electrical-thermal integrated energy system in the i-th P2G in the t-th future time period of the k+1-th iteration, λ i,t,k CHP,1 λk,i,t represents the Lagrange dual multiplier of the electrical-thermal system of the electrical-thermal integrated energy system in the i-th CHP in the t-th future time period of the k-th iteration, λ i,t,k P2G,1 hk,i,t represents the Lagrange dual multiplier of the electrical-thermal system of the electrical-thermal integrated energy system in the i-th P2G in the t-th future time period of the k-th iteration, h i,t,k CHP,1 hk,i,t represents the Lagrange penalty term coefficient of the electrical-thermal system of the electrical-thermal integrated energy system in the i-th CHP in the t-th future time period of the k-th iteration, h i,t,k P2G,1 hk,i,t represents the Lagrange penalty term coefficient of the electrical-thermal system of the electrical-thermal integrated energy system in the i-th P2G in the t-th future time period of the k-th iteration, λ i,t,k CHP,2 λk,i,t represents the Lagrange dual multiplier of the natural gas of the electrical-thermal integrated energy system in the i-th CHP in the t-th future time period of the k-th iteration, λ i,t,k P2G,2 hk,i,t represents the Lagrange dual multiplier of the natural gas system of the electrical-thermal integrated energy system in the i-th P2G in the t-th future time period of the k-th iteration, h i,t,k CHP,2 hk,i,t represents the Lagrange penalty term coefficient of the natural gas system of the electrical-thermal integrated energy system in the i-th CHP in the t-th future time period of the k-th iteration, h i,t,k P2G,2 hk,i,t represents the Lagrange penalty term coefficient of the natural gas system of the electrical-thermal integrated energy system in the i-th P2G in the t-th future time period of the k-th iteration, P i,t,k CHP,1 Pk,i,t represents the output active power of the i-th CHP in the t-th future time in the electrical-thermal coupled device obtained by solving the target model of the electrical-thermal system of the electrical-thermal integrated energy system for the k-th iteration of the alternating optimization iteration, P i,t,k CHP,2 Pk,i,t represents the output active power of the i-th CHP in the t-th future time in the electrical-thermal coupled device obtained by solving the target model of the natural gas system of the electrical-thermal integrated energy system for the k-th iteration of the alternating optimization iteration, P i,t,k P2G,1It represents the output active power of the i-th P2G in the electrothermal coupling device at the t-th future moment obtained by solving the k-th iteration of the electrothermal system target model of the electrothermal integrated energy system for alternating optimization iteration, P i,t,k CHP,2 It represents the output active power of the i-th P2G in the electric-thermal coupling device at the t-th future moment obtained by solving the k-th iteration of the natural gas system target model of the electric-thermal integrated energy system for alternating optimization iteration, N P2G Indicates the number of P2Gs in the electrical coupling device, N CHP represents the number of CHPs in the electrothermal coupling device, T represents the number at a future time, is the mathematical expression for "all", meaning that every number in the interval satisfies the constraint;

[0244] Step 5 obtains the solved variables of the integrated energy system at multiple prediction moments;

[0245] The solved variables of the integrated energy system at multiple prediction moments include:

[0246] After solving the electric and thermal integrated energy system model, the active power P output by the g-th generator in the transmission system model at the t-th future moment is g,t gen,* ,g∈[1,G],t∈[1,T];After solving the electric and thermal integrated energy system model, the reactive power Q output by the gth generator in the transmission system model at the tth future moment is g,t gen,* ,g∈[1,G],t∈[1,T];After solving the electric and thermal integrated energy system model, the active power P outputted by the w-th wind farm at the t-th future moment in the transmission system model is w,t wind,* ,w∈[1,W],t∈[1,T];After solving the electric and thermal integrated energy system model, the reactive power Q output by the w-th wind farm in the transmission system model at the t-th future time is w,t wind,* ,w∈[1,W],t∈[1,T];After solving the electric-thermal integrated energy system model, the output active power P of the i-th CHP in the electric-thermal coupling device at the t-th future moment is i,t CHP,* ,i∈[1,N CHP ], t∈[1,T]; after solving the electric-thermal integrated energy system model, the reactive power Q output by the i-th CHP in the electric-thermal coupling device at the t-th future moment is i,t CHP,* ,i∈[1,N CHP ], t∈[1,T]; after solving the electric-thermal integrated energy system model, the thermal power H output by the i-th CHP in the electric-thermal coupling device at the t-th future moment is i,t CHP,*i [1, N CHP ], t [1, T] ; the input gas flow F of the i th CHP at the t th future time in the electric heat integrated energy system model after solving i,t CHP,* i [1, N CHP ], t [1, T] ; the input active power P of the i th P2G at the t th future time in the electric heat integrated energy system model after solving i,t P2G,* i [1, N P2G ], t [1, T] ; the output gas flow F of the i th P2G at the t th future time in the electric heat integrated energy system model after solving i,t P2G,* i [1, N P2G ], t [1, T] ; the output gas flow F of the w th gas source at the t th future time in the natural gas system model after solving the electric heat integrated energy system model w,t sup,* w [1, W sup ], t [1, T] ; the total operation cost f1 of the electric heat system after solving the electric heat integrated energy system model * ; the total operation cost f2 of the natural gas system after solving the electric heat integrated energy system model * ; W represents the number of wind farms in the power transmission system model, G represents the number of generators in the power transmission system model, W sup represents the number of gas source points in the natural gas system model, N P2G represents the number of P2Gs in the electric coupling device, N CHP represents the number of CHPs in the electric heat coupling device, and T represents the number of future times.

[0247] The specific embodiments of the application also provide an electric heat integrated energy system advanced scheduling system, comprising:

[0248] An electric heat integrated energy system model construction module, which couples the power transmission system model and the heat supply system model through the electric heat coupling device, and couples the power transmission system model and the electric heat system model through the electric coupling device;

[0249] A load prediction module, which predicts the electric load, the heat load, and the gas load at multiple future times through a long short-term memory artificial neural network respectively;

[0250] A constraint construction module, which constructs system backup constraints, generator set operation constraints, wind farm operation constraints, power network constraints, heat system operation constraints, gas source point constraints, pipeline constraints, and node supply-demand balance constraints, and establishes coupling device constraints;

[0251] The system optimization target construction module respectively constructs an electric heating system target model and a natural gas system target model of the electric heating comprehensive energy system.

[0252] The alternating iterative optimization solving module obtains the solved variables of the electric heating comprehensive energy system at multiple prediction time points through an alternating iterative optimization method.

[0253] The electric heating comprehensive energy system model construction module, the load prediction module, the constraint construction module, the system optimization target construction module and the alternating iterative optimization solving module are all deployed on a server.

[0254] The specific embodiments of the present application also provide a computer readable medium.

[0255] The computer readable medium is a server workstation.

[0256] The server workstation stores a computer program executed by an electronic device, and when the computer program runs on the electronic device, the electronic device executes the steps of the electric heating comprehensive energy system advanced scheduling method of the embodiments of the present application.

[0257] It should be understood that the parts not elaborated in the specification are all prior art.

[0258] It should be understood that the above description of the preferred embodiments is more detailed, and therefore should not be considered as a limitation on the scope of patent protection of the present application. Those skilled in the art can make substitutions or modifications without departing from the scope of protection of the present application, and all fall within the scope of protection of the present application. The scope of protection of the present application should be subject to the appended claims.

Claims

1. A method for advanced scheduling of an electric and thermal integrated energy system, characterized in that: The following steps are involved: Step 1: Construct the transmission system model, thermal system model, and natural gas system model. Obtain the electric load of each power node in the transmission system model at multiple historical moments, the output of each wind farm in the transmission system model at multiple historical moments, the heat load of each thermal node in the thermal system model at multiple historical moments, and the gas load of each natural gas node in the natural gas system model at multiple historical moments. Combined with the electric and thermal system models, construct an electric and thermal integrated energy system model. Step 2: Using a long short-term memory artificial neural network, the predicted electric load at multiple future moments for each power node in the transmission system model, the predicted active power at multiple future moments for each wind farm in the transmission system model, the predicted thermal load at multiple future moments for each thermal node in the thermal system model, and the predicted gas load at multiple future moments for each natural gas node in the natural gas system model are predicted. Step 3: Combine the active power forecast and electric load forecast for each wind farm at multiple future times in the transmission system model to sequentially construct system reserve constraints, generator set operation constraints, wind farm operation constraints, and power network constraints. Combine the thermal load forecast for each thermal node at multiple future times in the thermal system model to construct thermal system operation constraints. Combine the gas load forecast for each natural gas node at multiple future times in the natural gas system model to sequentially construct gas source point constraints, pipeline constraints, and node supply and demand balance constraints, and establish coupled device constraints. Step 4: Construct the target model of the electric-thermal system and the target model of the natural gas system of the electric-thermal integrated energy system; Step 5: Construct coupling device constraints, take the electric-thermal system target model of the electric-thermal integrated energy system and the natural gas system target model of the electric-thermal integrated energy system as optimization targets, establish the electric-thermal system target model of the electric-thermal integrated energy system for alternating optimization iteration, and establish the natural gas system target model of the electric-thermal integrated energy system for alternating optimization iteration. Perform optimization and solution through the alternating iterative optimization method to obtain the solved variables of the electric-thermal integrated energy system at multiple prediction moments, and realize advanced scheduling of the electric-thermal integrated energy system through the solved variables of the electric-thermal integrated energy system at multiple prediction moments.

2. The method for advanced scheduling of an electric and thermal integrated energy system according to claim 1, characterized in that: The number of power nodes in the power transmission system model in step 1 is N; The number of wind farms in the transmission system model described in step 1 is W; The number of thermal nodes in the thermal system model in step 1 is H; The number of natural gas nodes in the natural gas system model in step 1 is S; In step 1, the electric-thermal integrated energy system model is constructed by combining the electric-thermal system model, as follows: The power transmission system model and the heating system model are coupled through the electrothermal coupling device, and the power transmission system model and the electrothermal system model are coupled through the electrical coupling device.

3. The method for advanced scheduling of an electric and thermal integrated energy system according to claim 2, characterized in that: The predictions in step 2 are made by the long and short-term memory artificial neural network as follows: The electric load of each power node in the transmission system model at multiple historical moments is predicted by a long short-term memory artificial neural network to obtain the predicted electric load of each power node in the transmission system model at multiple future moments. The output of each wind farm in the transmission system model at multiple historical moments is predicted by a long short-term memory artificial neural network to obtain the predicted active power of each wind farm in the transmission system model at multiple future moments. The heat load of each thermal node in the thermal system model at multiple historical moments is predicted by a long short-term memory artificial neural network to obtain the predicted heat load of each thermal node in the thermal system model at multiple future moments. The gas load of each natural gas node in the natural gas system model at multiple future moments is predicted by a long short-term memory artificial neural network to obtain the predicted gas load of each natural gas node in the natural gas system model at multiple future moments. The number of future moments in step 2 is T; The predicted electric load of each power node in the power transmission system model at multiple future moments in step 2 is specifically defined as follows: P n,t load n∈[1,N],t∈[1,T] Where N is the number of power nodes in the transmission system model, T is the number of future time points, and P n,t load represents the predicted electric load of the nth power node in the transmission system model at the tth future moment; The predicted active power of each wind farm at multiple future moments in the transmission system model described in step 2 is specifically defined as follows: P w,t 0 w∈[1,W],t∈[1,T] Where W represents the number of wind farms in the transmission system model, T represents the number of wind farms in the future, and P w,t 0 represents the predicted active power of wind power at the wth wind farm at the tth future moment in the transmission system model; The predicted heat load of each thermal node in the thermal system model at multiple future moments in step 2 is specifically defined as follows: H h,t load h∈[1,H],t∈[1,T] Among them, H represents the number of thermal nodes in the thermal system model, T represents the number of future moments, and H h,t load It represents the predicted heat load of the hth thermal node at the tth future moment in the thermal system model; The predicted gas load of each natural gas node at multiple future moments in the natural gas system model described in step 2 is specifically defined as follows: F s,t load s∈[1,S],t∈[1,T] Among them, S represents the number of natural gas nodes in the natural gas system model, T represents the number of future moments, and F s,t load Represents the predicted heat load of the sth natural gas node at the tth future moment in the natural gas system model.

4. The method for advanced scheduling of an electric and thermal integrated energy system according to claim 3, characterized in that: The system backup constraints described in step 3 are specifically defined as follows: Among them, x g,t gen represents the 0 / 1 indicator variable for the grid connection operation of the g-th generator at the t-th future time in the transmission system model, x i,t CHP It represents the 0 / 1 indicator variable of the grid-connected operation of the ith CHP in the electrothermal coupling device at the tth future moment, P g gen,max and P g gen ,min are the maximum technical output and minimum technical output of the g-th generator in the transmission system model, P g CHP,max and P g CHP,min represents the maximum and minimum technical output of the i-th CHP in the electrothermal coupling device, P w,t wind represents the active power output of the w-th wind farm at the t-th future moment in the transmission system model, r load represents the error of power load forecasting for each power load node in the transmission system model, r wind represents the wind power prediction error of each wind farm in the transmission system model, P n,t load represents the predicted electric load of the nth power node in the transmission system model at the tth future moment, G represents the number of generators in the transmission system model, W represents the number of wind farms in the transmission system model, N CHP represents the number of CHPs in the electrothermal coupling device, N represents the number of power nodes in the transmission system model, and T represents the number at the future time. Indicates that every number in the interval satisfies the range constraint; The generator set operation constraints described in step 3 are specifically defined as follows: Among them, x g,t gen represents the 0 / 1 indicator variable for the grid connection operation of the g-th generator at the t-th future time in the transmission system model, x g,t-1 gen represents the 0 / 1 indicator variable for the grid connection operation of the g-th generator at the t-1th future time in the transmission system model, x g,w gen T represents the 0 / 1 indicator variable indicating the grid connection operation of the gth generator in the electrothermal coupling device at the wth future moment, g gen,st and T g gen,sd They represent the minimum start-up time and minimum shutdown time of the g-th generator in the transmission system model, P g gen,max and P g gen,min They represent the maximum technical output and minimum technical output of the g-th generator in the transmission system model, P g,t gen represents the active output power of the gth generator at the tth future moment in the transmission system model, P g,t-1 gen represents the active output power of the g-th generator at the t-1th future moment in the transmission system model, Q g,t gen represents the reactive output power of the g-th generator at the t-th future moment in the transmission system model, and They represent the lower and upper limits of the grid-connected power factor angle of each generator in the transmission system model, r g gen,up and r g gen,dn They represent the upper and lower climbing limits of the g-th generator in the transmission system model, respectively. ||·||2 represents the mathematical 2-norm calculation formula. G represents the number of generators in the transmission system model. T represents the number of generators in the future time. Indicates that every number in the interval satisfies the range constraint; The wind farm operation constraints described in step 3 are specifically defined as follows: Among them, P w,t wind represents the active output power of the w-th wind farm at the t-th future moment in the transmission system model, P w,t 0 represents the predicted active power of the w-th wind farm at the t-th future moment in the transmission system model, Q w,t wind represents the reactive output power of the w-th wind farm at the t-th future moment in the transmission system model, Indicates the lower limit of the grid-connected power factor angle of each wind farm in the transmission system model, arccos indicates the cosine angle calculation, tan indicates the sine angle calculation, W indicates the number of wind farms in the transmission system model, and T indicates the number at the future time. Indicates that every number in the interval satisfies the range constraint; The power network constraints described in step 3 are specifically defined as follows: 0≤Q n,t com ≤Q n com,max ,n∈[1,N] Among them, P i,t CHP , Q i,t CHP They represent the output active power and output reactive power of the ith CHP in the electrothermal coupling device at the tth future moment, P i,t P2G represents the input active power of the ith P2G in the electrical coupling device at the tth future moment, P g,t gen and Q g,t gen They represent the output active power and reactive power of the g-th generator at the t-th future moment in the transmission system model, respectively. w,t wind and Q w,t wind They represent the output active power and reactive power of the w-th wind farm at the t-th future moment in the transmission system model, respectively. l,t line and Q l,t line They represent the sending end active power and the sending end reactive power of the lth transmission line at the tth future moment in the transmission system model, △P l,t line and △Q l,t line They represent the active power loss and reactive power loss of the lth transmission line at the tth future moment in the transmission system model, respectively. n,t load represents the predicted electric load of the nth power node in the transmission system model at the tth future moment, represents the power factor angle of the nth power node in the transmission system model at the tth future moment, Q n,t com It represents the reactive compensation power of the nth power node at the tth future moment in the transmission system model, Q n com,max Indicates the maximum reactive compensation power of the nth power node in the transmission system model, u l,t + and θ l,t + They represent the square of the voltage amplitude and phase angle at the sending end of the lth transmission line in the transmission system model at the tth future moment, u l,t + and θ l,t + They represent the square of the receiving voltage amplitude and phase angle of the lth transmission line at the tth future moment in the transmission system model, G l and B l are the conductance and susceptance of the lth transmission line in the transmission system model, S l,max represents the rated transmission capacity of the lth transmission line in the transmission system model, θ n,t represents the voltage phase angle of the nth power node in the transmission system model at the tth future moment, v n min and v n max They represent the minimum and maximum voltage amplitudes of the nth power node in the transmission system model, θ l,slack t Denotes the phase angle difference △θ of the lth transmission line at the tth future moment in the transmission system model l,t Squared relaxation, △θ l max It represents the maximum absolute value of the phase angle difference between the sending end and the receiving end of the lth transmission line in the transmission system model, sl l,t,i Denotes the phase angle difference △θ of the lth transmission line at the tth future moment in the transmission system model l,t The slope of the squared i-th segment, N sl The number of segments of the square of the phase angle difference of each transmission line at each future moment in the transmission system model, TC l,t,i Denotes the phase angle difference △θ of the lth transmission line at the tth future moment in the transmission system model l,t The value of the squared i-th segment point, N n CHP Indicates the number of CHPs connected to the nth power node in the transmission system model, N n P2G Indicates the number of P2Gs connected to the nth power node in the transmission system model, N n G N represents the number of generators connected to the nth power node in the transmission system model. n W Indicates the number of wind farms connected to the nth power node in the transmission system model, N n l(+) N represents the number of transmission lines with the nth power node as the sending end in the transmission system model. n l(-) represents the number of transmission lines with the nth power node as the receiving end in the transmission system model, L ele represents the number of transmission lines in the transmission system model, N represents the number of power nodes in the transmission system model, T represents the number of future moments, and ||·||2 represents the mathematical 2-norm calculation formula. Indicates that every number in the interval satisfies the range constraint; The operational constraints of the thermal system model described in step 3 are specifically defined as follows: Among them, H h,t load It represents the predicted heat load of the hth thermal node at the tth future moment in the thermal system model, H i,t CHP represents the output thermal power of the ith CHP at the tth future moment in the coupled equipment model, C P Represents the specific heat capacity of water in the thermal system model, m h,t q T represents the water quality injection rate of the hth thermal node in the thermal system model at the tth future moment, h,t s T represents the water supply temperature of the hth thermal node in the thermal system model at the tth future moment, h,t r represents the return water temperature of the hth thermal node in the thermal system model at the tth future moment, T h s,min and T h s,max The lower and upper limits of the water supply temperature of the hth thermal node in the thermal system model, T h r,min and T h r,max The lower and upper limits of the return water temperature of the hth thermal node in the thermal system model, T l,t - and T l,t + They represent the temperatures of the receiving and sending ends of the lth heating pipe in the thermal system model at the tth future moment, e represents the base of the natural logarithm function, m l,t represents the water mass flow rate of the lth heating pipe in the thermal system model at the tth future moment, λ l heat represents the heat transfer coefficient of the lth heating pipe in the thermal system model, T t a Indicates the ambient temperature of the thermal system model at the tth future moment, len l represents the length of the first heating pipe in the thermal system model, H h l(+) Indicates the number of heating pipes with the nth thermal node in the thermal system model as the sending end, H h l(-) Indicates the number of heating pipes with the nth thermal node in the thermal system model as the receiving end, H h CHP Indicates the number of CHPs connected to the nth thermal node in the thermal system model, L heat Represents the number of heating pipes in the thermal system model, H represents the number of thermal nodes in the thermal system model, and T represents the number at the future time. Indicates that every number in the interval satisfies the range constraint; The gas source point constraint described in step 3 is specifically defined as follows: Among them, F w,t su p represents the output gas flow of the wth gas source at the tth future time in the natural gas system model, F w su p,min and F w su p,max represent the minimum and maximum output flow of the w-th gas source in the natural gas system model, respectively. su p represents the number of gas source points in the natural gas system model, and T represents the number at a future time; The pipeline constraints described in step 3 are defined as follows: Among them, the symbol |·| represents the mathematical formula for taking the absolute value, ||·||2 represents the mathematical formula for calculating the 2 norm, and F l,t line represents the gas flow of the lth gas supply pipeline at the tth future moment in the natural gas system model, k l line represents the transmission coefficient of the lth gas supply pipeline in the natural gas system model, pg l,t + and pg l,t - They represent the gas pressure at the sending end and receiving end of the lth gas supply pipeline in the natural gas system model at the tth future moment, F l line,max represents the maximum allowable gas flow rate of the lth gas supply pipeline in the natural gas system model, pg l +,min and pg l +,max They represent the lower and upper limits of the gas pressure at the delivery end of the lth gas supply pipeline in the natural gas system model, pg l -,min and pg l -,max They represent the lower and upper limits of the receiving pressure of the lth gas supply pipeline in the natural gas system model, respectively, and x l,t + and x l,t -- They represent the positive and negative flow direction indicators of the water quality at the tth future moment in the lth gas supply pipeline in the natural gas system model, respectively. l gas represents the auxiliary constant for judging the water quality flow direction of the lth gas supply pipeline at each moment in the natural gas system model, α l,t i represents the auxiliary variable for judging the first water quality flow direction of the lth gas supply pipeline at the tth future moment in the natural gas system model, α l,t j represents the auxiliary variable for judging the second water quality flow direction of the lth gas supply pipeline at the tth future moment in the natural gas system model, β l,t i represents the third water quality flow direction judgment auxiliary variable of the lth gas supply pipeline at the tth future moment in the natural gas system model, β l,t j represents the fourth water quality flow direction judgment auxiliary variable of the lth gas supply pipeline at the tth future moment in the natural gas system model, M represents the auxiliary constant in the natural gas system model, L gas represents the number of gas supply pipelines in the natural gas system model, T represents the number at the future time, Indicates that every number in the interval satisfies the range constraint; The node supply and demand balance constraint described in step 3 is specifically defined as follows: Among them, F w,t su p represents the output gas flow of the wth gas source at the tth future time in the natural gas system model, F l,t line represents the gas flow of the lth gas supply pipeline at the tth future moment in the natural gas system model, F i,t P2G represents the gas flow of the tth future moment of the i-th P2G in the coupling device model, F i,t CHP represents the air flow of the ith CHP at the tth future moment in the coupled equipment model, F s,t load represents the predicted heat load of the sth natural gas node at the tth future moment in the weather gas system model, S s su p represents the number of gas sources connected to the sth natural gas node in the natural gas system model, S s l(+) represents the number of gas supply pipelines with the sth natural gas node as the sending end in the natural gas system model, S s l(-) represents the number of gas supply pipelines with the sth natural gas node as the receiving end in the natural gas system model, S s P2G Indicates the number of P2Gs connected to the sth natural gas node in the natural gas system model, S s CHP Indicates the number of CHPs connected to the sth natural gas node in the natural gas system model, S indicates the number of natural gas nodes in the natural gas system model, Indicates that every number in the interval satisfies the range constraint; The coupling device constraints described in step 3 are specifically defined as follows: Among them, P i,t CHP , Q i,t CHP 、F i,t CHP and H i,t CHP They represent the output active power, output reactive power, input gas flow rate and output thermal power of the i-th CHP in the electrothermal coupling device at the t-th future moment, respectively. g Represents the calorific value of natural gas in the coupled equipment model, RHE i CHP represents the thermoelectric ratio of the i-th CHP in the electrothermal coupling device at each future moment; η i CHP represents the energy conversion efficiency of the i-th CHP in the electrothermal coupling device at each future moment, P i,t-1 CHP represents the output active power of the ith CHP in the electrothermal coupling device at the t-1th future moment, x i,t CHP represents the 0 / 1 indicator variable for the grid-connected operation of the ith CHP in the electrothermal coupling device at the tth future moment, x i,t-1 CHP represents the 0 / 1 indicator variable for the grid-connected operation of the ith CHP in the electrothermal coupling device at the t-1th future time, x i,w CHP T represents the 0 / 1 indicator variable indicating the grid-connected operation of the i-th CHP in the electric-thermal coupling device at the w-th future moment, i CHP,st and T i CHP,sd They represent the minimum start-up time and minimum shutdown time of the i-th CHP in the electrothermal coupling equipment, P i CHP,max and P i CHP ,min denote the maximum and minimum technical outputs of the ith CHP in the electrothermal coupling device, and They represent the lower and upper limits of the grid-connected power factor angle of each CHP in the electrothermal coupling equipment, r i CHP,up and r i CHP,dn They represent the upper and lower climbing limits of the i-th CHP in the electrothermal coupling device, ||·||2 represents the mathematical 2-norm calculation formula, and N CHP represents the number of CHPs in the electrothermal coupling device, T represents the number at a future time, Indicates that every number in the interval satisfies the range constraint; Among them, P i,t P2G 、F i,t P2G They represent the input active power and output gas flow of the ith P2G in the electrical coupling device at the tth future moment, HV g Indicates the calorific value of natural gas in the coupled equipment, η i P2G represents the energy conversion efficiency of the i-th P2G in the coupled device model at each future moment, N P2G represents the number of P2Gs in the electrical coupling device, T represents the number at a future time, Indicates that every number in the interval satisfies the range constraint.

5. The method for advanced scheduling of an electric and thermal integrated energy system according to claim 4, characterized in that: The target model of the electric-thermal system of the electric-thermal integrated energy system described in step 4 is specifically defined as follows: Among them, f1 represents the total operating cost of the electric heating system of the electric heating integrated energy system, C1 represents the sum of the generator startup cost and the CHP startup cost of the electric heating system of the electric heating integrated energy system, C2 represents the sum of the variable cost of the electric heating system generator and the CHP variable cost of the electric heating system of the electric heating integrated energy system, C3 represents the penalty cost of wind curtailment of the electric heating system of the electric heating integrated energy system, and C g gen,st C represents the cost of starting the gth generator of the electric heating system of the electric heating integrated energy system. i CHP,st represents the single startup cost of the i-th CHP of the electric heating system of the electric heating integrated energy system, a g gen 、b g gen and c g gen They represent the coefficients of the variable cost of the first-order term, the second-order term and the constant term of the g-th generator in the electric-thermal system of the electric-thermal integrated energy system, respectively. i CHP 、b i CHP and c i CHP They represent the linear term, quadratic term and constant term coefficients of the i-th CHP variable cost of the electric-thermal system of the electric-thermal integrated energy system, respectively. g,t gen represents the 0 / 1 indicator variable for the grid connection operation of the g-th generator at the t-th future time in the transmission system model, x g,t-1gen represents the 0 / 1 indicator variable for the grid connection operation of the g-th generator at the t-1th future time in the transmission system model, x i,t CHP represents the 0 / 1 indicator variable for the grid-connected operation of the ith CHP in the electrothermal coupling device at the tth future moment, x i,t-1 CHP It represents the 0 / 1 indicator variable of the grid-connected operation of the ith CHP in the electrothermal coupling device at the t-1th future time, P g,t gen P represents the output active power and reactive power of the g-th generator at the t-th future moment in the transmission system model, i,t CHP represents the output active power of the ith CHP in the electrothermal coupling device at the tth future moment, P w,t wind P represents the active power output of the w-th wind farm at the t-th future moment in the transmission system model, w,t 0 It represents the predicted active power of wind power at the tth future moment in the wth wind farm in the transmission system model, W punish represents the penalty cost per unit of wind curtailment in the transmission system model, N CHP represents the number of CHPs in the electrothermal coupling device, G represents the number of generators in the transmission system model, W represents the number of wind farms in the transmission system model, T represents the number at the future time, Indicates that every number in the interval satisfies the range constraint.

6. The method for advanced scheduling of an electric and thermal integrated energy system according to claim 5, characterized in that: The target model of the natural gas system of the electric and thermal integrated energy system described in step 4 is specifically defined as follows: Among them, f2 represents the total operating cost of the weather system of the electric and thermal integrated energy system, C N1 C represents the total gas source operation cost of the natural gas system of the electric and thermal integrated energy system. N2 represents the total cost of P2G operation of the natural gas system in the electric and thermal integrated energy system, c w sup represents the unit operating cost of the w-th gas source of the natural gas system of the electric and thermal integrated energy system at each future moment, c i P2G F represents the unit operating cost of the i-th P2G of the natural gas system of the electric and thermal integrated energy system at each future moment. w,t sup represents the output gas flow of the wth gas source at the tth future moment in the natural gas system model, F i,t P2G represents the output gas flow of the i-th P2G in the electrical coupling device at the t-th future moment, W su p represents the number of gas source points in the natural gas system model, N P2G represents the number of P2Gs in the electrical coupling device, T represents the number at a future time, Indicates that every number in the interval satisfies the range constraint.

7. The method for advanced scheduling of an electric and thermal integrated energy system according to claim 6, characterized in that: Construct the coupled device constraints described in step 5 as follows: Combine system reserve constraints, generator set operation constraints, wind farm operation constraints, power network constraints, thermal system operation constraints, gas source point constraints, pipeline constraints, and node supply and demand balance constraints to build coupled equipment constraints; Step 5 describes the establishment of an electric-thermal system target model for the electric-thermal integrated energy system for alternating optimization iterations. The specific definition is as follows: Among them, f1 represents the total operating cost of the electric heating system of the electric heating integrated energy system, λ i,t CHP,1 represents the Lagrangian dual multiplier of the tth future period of the i-th CHP of the electric-thermal system of the electric-thermal integrated energy system, λ i,t P2G,1 represents the Lagrangian dual multiplier of the tth future period of the i-th P2G of the electric-thermal system of the electric-thermal integrated energy system, h i,t CHP,1 represents the Lagrangian penalty term coefficient of the tth future period of the i-th CHP of the electric-thermal system of the electric-thermal integrated energy system, h i,t P2G,1 represents the Lagrangian penalty term coefficient of the ith P2G in the tth future period of the electric-thermal system of the electric-thermal integrated energy system, P i,t CHP,1 It represents the output active power of the i-th CHP at the t-th future moment in the electrothermal coupling device obtained by solving the electrothermal system target model of the electrothermal integrated energy system for alternating optimization iteration, P i,t CHP,2 represents the output active power of the i-th CHP at the t-th future moment in the electric-thermal coupling device obtained by solving the natural gas system target model of the electric-thermal integrated energy system for alternating optimization iteration, P i,t P2G,1 represents the output active power of the i-th P2G in the electrothermal coupling device at the t-th future moment obtained by solving the electrothermal system target model of the electrothermal integrated energy system for alternating optimization iteration, P i,t CHP,2 The output active power of the i-th P2G in the electric-thermal coupling device at the t-th future moment obtained by solving the natural gas system target model of the electric-thermal integrated energy system for alternating optimization iterations, N P2G Indicates the number of P2Gs in the electrical coupling device, N CHP represents the number of CHPs in the electrothermal coupling device, and T represents the number at a future time; Step 5 establishes a natural gas system target model for the electric-thermal integrated energy system for alternating optimization iterations. The specific definitions are as follows: Where f2 represents the total operating cost of the natural gas system in the electric and thermal integrated energy system, λ i,t CHP,2 represents the Lagrangian dual multiplier of the tth future period of the i-th CHP of the natural gas system in the electric and thermal integrated energy system, λ i,t P2G,2 represents the Lagrangian dual multiplier of the natural gas system in the tth future period of the i-th P2G of the electric and thermal integrated energy system, h i,t CHP,2 h represents the Lagrangian penalty term coefficient of the tth future period of the i-th CHP of the natural gas system of the electric and thermal integrated energy system, i,t P2G,2 represents the Lagrangian penalty term coefficient of the natural gas system in the tth future period of the i-th P2G of the electric and thermal integrated energy system, P i,t CHP,1 It represents the output active power of the i-th CHP at the t-th future moment in the electrothermal coupling device obtained by solving the electrothermal system target model of the electrothermal integrated energy system for alternating optimization iteration, P i,t CHP,2 represents the output active power of the i-th CHP at the t-th future moment in the electric-thermal coupling device obtained by solving the natural gas system target model of the electric-thermal integrated energy system for alternating optimization iteration, P i,t P2G,1 represents the output active power of the i-th P2G in the electrothermal coupling device at the t-th future moment obtained by solving the electrothermal system target model of the electrothermal integrated energy system for alternating optimization iteration, P i,t CHP,2 The output active power of the i-th P2G in the electric-thermal coupling device at the t-th future moment obtained by solving the natural gas system target model of the electric-thermal integrated energy system for alternating optimization iterations, N P2G Indicates the number of P2Gs in the electrical coupling device, N CHP represents the number of CHPs in the electrothermal coupling device, and T represents the number at a future time.

8. The method for advanced scheduling of an electric and thermal integrated energy system according to claim 7, characterized in that: In step 5, the alternating iterative optimization method is used to optimize and solve the variables of the electric and thermal integrated energy system at multiple prediction moments. The specific process is as follows: Step 5.1, initialize the number of iterations k = 1, initialize the Lagrangian dual multiplier λ of the electric-thermal system of the electric-thermal integrated energy system for the kth iteration of the i-th CHP in the t-th future period i,t,k CHP,1 Initialize the Lagrangian dual multiplier λ of the electric-thermal system of the electric-thermal integrated energy system at the kth iteration of the i-th P2G in the t-th future period i,t,k P2G,1 Initialize the Lagrangian penalty term coefficient h of the kth iteration of the i-th CHP in the t-th future period of the electric-thermal integrated energy system i,t,k CHP,1 Initialize the Lagrangian penalty term coefficient h of the kth iteration of the i-th P2G of the electric-thermal integrated energy system in the t-th future period i,t,k P2G,1 , initialize the Lagrangian dual multiplier λ of the natural gas k-th iteration and the t-th future period of the i-th CHP of the electric and thermal integrated energy system i,t,k CHP,2 Initialize the Lagrangian dual multiplier λ of the natural gas system in the kth iteration of the i-th P2G of the t-th future period of the electric and thermal integrated energy system i,t,k P2G,2 Initialize the Lagrangian penalty term coefficient h of the natural gas system of the electric and thermal integrated energy system at the kth iteration of the i-th CHP in the t-th future period i,t,k CHP,2 Initialize the Lagrangian penalty term coefficient h of the natural gas system of the electric and thermal integrated energy system at the kth iteration of the i-th P2G in the t-th future period i,t,k P2G,2 Initialize the target model of the electric-thermal integrated energy system for alternating optimization iterations. The output active power P of the i-th CHP in the electric-thermal coupling device at the t-th future moment is obtained by solving the k-th iteration. i,t,k CHP,1 Initialize the natural gas system target model of the electric-thermal integrated energy system for alternating optimization iterations. The output active power P of the i-th CHP in the electric-thermal coupling device at the t-th future moment is obtained by solving the k-th iteration. i,t,k CHP,2 Initialize the target model of the electric-thermal integrated energy system for alternating optimization iterations. The output active power P of the i-th P2G in the electrical coupling device at the t-th future moment is obtained by solving the k-th iteration. i,t,k P2G,1 Initialize the natural gas system target model of the electric-thermal integrated energy system for alternating optimization iterations. The output active power P of the i-th P2G in the electric-thermal coupling device at the t-th future moment is obtained by solving the k-th iteration. i,t,k CHP,2 , initialize the iterative calculation convergence threshold ε of the electrical and thermal integrated energy system; In step 5.2, the electric-thermal system dispatching center obtains the output active power of the i-th CHP in the electric-thermal coupling device at the t-th future moment of the k-th iteration of the electric-thermal system target model of the electric-thermal integrated energy system for alternating optimization iterations by using the interior point method based on the electric-thermal system target model of the electric-thermal integrated energy system for alternating optimization iterations and the system backup constraints, generator set operation constraints, wind farm operation constraints, power network constraints, and heating system operation constraints. The output active power of the i-th P2G in the electrical coupling device at the t-th future moment in the k-th iteration of the electric-thermal system target model of the electric-thermal integrated energy system for alternating optimization iterations is Among them, N P2G Indicates the number of P2Gs in the electrical coupling device, N CHP represents the number of CHPs in the electrothermal coupling device, T represents the number at a future time, is the mathematical expression for "all", meaning that every number in the interval satisfies the constraint; In step 5.3, the natural gas system dispatching center uses the interior point method to solve the natural gas system target model of the electric-thermal integrated energy system for alternating optimization iterations, as well as the gas source point constraints, pipeline constraints, and node supply and demand balance constraints, to obtain the output active power of the i-th CHP in the electric-thermal coupling device at the t-th future time in the k-th iteration of the natural gas system target model of the electric-thermal integrated energy system for alternating optimization iterations. The output active power of the i-th P2G in the electrical coupling device at the t-th future moment in the k-th iteration of the natural gas system target model of the electrical and thermal integrated energy system for alternating optimization iterations Among them, N P2G Indicates the number of P2Gs in the electrical coupling device, N CHP represents the number of CHPs in the electrothermal coupling device, T represents the number at a future time, is the mathematical expression for "all", meaning that every number in the interval satisfies the constraint; In step 5.4, the upper-level dispatching center determines whether the iterative process has converged based on the convergence criterion. If converged, the upper-level dispatching center sends a convergence signal, the algorithm stops, and the solved variables of the electrical and thermal integrated energy system at multiple prediction moments are obtained; If it does not converge, set k = k + 1, and the upper scheduling center updates the operator according to the operator update model and sends it down, transposing step 5.2; The convergence criterion described in step 5.4 is specifically defined as follows: Among them, the symbol |·| represents the mathematical formula for taking the absolute value, P i,t,k CHP,1 It represents the output active power of the i-th CHP in the electrothermal coupling device at the t-th future moment obtained by solving the k-th iteration of the electrothermal system target model of the electrothermal integrated energy system for alternating optimization iteration, P i,t,k CHP,2 represents the output active power of the i-th CHP in the electric-thermal coupling device at the t-th future moment obtained by solving the k-th iteration of the natural gas system target model of the electric-thermal integrated energy system for alternating optimization iterations, P i,t,k P2G,1 It represents the output active power of the i-th P2G in the electrothermal coupling device at the t-th future moment obtained by solving the k-th iteration of the electrothermal system target model of the electrothermal integrated energy system for alternating optimization iteration, P i,t,k CHP,2 It represents the output active power of the i-th P2G in the electric-thermal coupling device at the t-th future moment obtained by solving the k-th iteration of the natural gas system target model of the electric-thermal integrated energy system for alternating optimization iteration, N P2G Indicates the number of P2Gs in the electrical coupling device, N CHP represents the number of CHPs in the electrothermal coupling device, T represents the number at a future time, is the mathematical expression for "all", meaning that every number in the interval satisfies the constraint; Update the Lagrangian dual multiplier λ of the k-th iteration of the i-th CHP in the t-th future period of the electric-thermal integrated energy system through the operator update model i,t,k CHP,1 , the Lagrangian dual multiplier λ of the kth iteration of the i-th P2G of the electric-thermal integrated energy system in the t-th future period i,t,k P2G,1 , the Lagrangian penalty term coefficient h of the kth iteration of the i-th CHP in the t-th future period of the electric-thermal integrated energy system i,t,k CHP,1 , the Lagrangian penalty term coefficient h of the kth iteration of the i-th P2G in the t-th future period of the electric-thermal integrated energy system i,t,k P2G,1 , the Lagrangian dual multiplier λ of the natural gas k-th iteration and the ith CHP in the t-th future period of the electric and thermal integrated energy system i,t,k CHP,2 , the Lagrangian dual multiplier λ of the natural gas system in the kth iteration of the i-th P2G in the t-th future period of the electric and thermal integrated energy system i,t,k P2G,2 , the Lagrangian penalty term coefficient h of the natural gas system in the kth iteration of the ith CHP in the tth future period of the electric and thermal integrated energy system i,t,k CHP,2 The Lagrangian penalty term coefficient h of the natural gas system in the kth iteration and the tth future period of the i-th P2G of the electric and thermal integrated energy system is i,t,k P2G,2 , specifically defined as follows: Where β represents the Lagrangian penalty term coefficient update factor in the electrical and thermal integrated energy system, λ i,t,k+1 CHP,1 represents the Lagrangian dual multiplier of the i-th CHP in the t-th future period of the electric-thermal system in the k+1th iteration of the electric-thermal integrated energy system, λ i,t,k+1 P2G,1 represents the Lagrangian dual multiplier of the ith P2G in the tth future period of the electric-thermal system in the k+1th iteration of the electric-thermal integrated energy system, h i,t,k+1 CHP,1 h represents the Lagrangian penalty term coefficient of the i-th CHP in the t-th future period of the electric-thermal system in the k+1th iteration of the electric-thermal integrated energy system, i,t,k+1 P2G,1 represents the Lagrangian penalty term coefficient of the ith P2G in the tth future period of the electric-thermal system in the k+1th iteration of the electric-thermal integrated energy system, λ i,t,k+1 CHP,2 represents the Lagrangian dual multiplier of the natural gas k+1th iteration and the ith CHP in the tth future period of the electric and thermal integrated energy system, λ i,t,k+1 P2G,2 represents the Lagrangian dual multiplier of the natural gas system in the k+1th iteration of the i-th P2G in the t-th future period of the electric and thermal integrated energy system, h i,t,k+1 CHP,2 h represents the Lagrangian penalty term coefficient of the natural gas system in the k+1th iteration of the i-th CHP in the t-th future period of the electric and thermal integrated energy system, i,t,k+1 P2G,2 represents the Lagrangian penalty term coefficient of the natural gas system in the k+1th iteration of the i-th P2G in the t-th future period, λ i,t,k CHP,1 represents the Lagrangian dual multiplier of the kth iteration of the ith CHP in the tth future period of the electric-thermal integrated energy system, λ i,t,k P2G,1 represents the Lagrangian dual multiplier of the kth iteration of the ith P2G in the tth future period of the electric-thermal integrated energy system, h i,t,k CHP,1 h represents the Lagrangian penalty term coefficient of the kth iteration of the i-th CHP in the t-th future period of the electric-thermal system of the electric-thermal integrated energy system, i,t,k P2G,1 represents the Lagrangian penalty term coefficient of the kth iteration of the i-th P2G in the t-th future period of the electric-thermal integrated energy system, λ i,t,k CHP,2 represents the Lagrangian dual multiplier of the natural gas k-th iteration and the ith CHP in the t-th future period of the electric and thermal integrated energy system, λ i,t,k P2G,2 represents the Lagrangian dual multiplier of the natural gas system in the kth iteration of the i-th P2G in the t-th future period of the electric and thermal integrated energy system, h i,t,k CHP,2 The Lagrangian penalty term coefficient of the kth iteration of the i-th CHP in the t-th future period of the natural gas system of the electric and thermal integrated energy system, h i,t,k P2G,2 represents the Lagrangian penalty term coefficient of the natural gas system in the kth iteration of the i-th P2G in the t-th future period of the electric and thermal integrated energy system, P i,t,k CHP,1 It represents the output active power of the i-th CHP in the electrothermal coupling device at the t-th future moment obtained by solving the k-th iteration of the electrothermal system target model of the electrothermal integrated energy system for alternating optimization iteration, P i,t,k CHP,2 represents the output active power of the i-th CHP in the electric-thermal coupling device at the t-th future moment obtained by solving the k-th iteration of the natural gas system target model of the electric-thermal integrated energy system for alternating optimization iterations, P i,t,k P2G,1 It represents the output active power of the i-th P2G in the electrothermal coupling device at the t-th future moment obtained by solving the k-th iteration of the electrothermal system target model of the electrothermal integrated energy system for alternating optimization iteration, P i,t,k CHP,2 It represents the output active power of the i-th P2G in the electric-thermal coupling device at the t-th future moment obtained by solving the k-th iteration of the natural gas system target model of the electric-thermal integrated energy system for alternating optimization iteration, N P2G Indicates the number of P2Gs in the electrical coupling device, N CHP represents the number of CHPs in the electrothermal coupling device, T represents the number at a future time, is the mathematical expression for "all", meaning that every number in the interval satisfies the constraint; The solved variables of the electrical and thermal integrated energy system at multiple prediction moments in step 5 are as follows: The solved variables of the electrical and thermal integrated energy system at multiple prediction moments include: After solving the electric and thermal integrated energy system model, the active power output of the g-th generator in the transmission system model at the t-th future moment After solving the electric and thermal integrated energy system model, the reactive power output of the gth generator in the transmission system model at the tth future moment is obtained. After solving the electric and thermal integrated energy system model, the active power P output by the w-th wind farm at the t-th future time in the transmission system model is w,t wind,* ,w∈[1,W],t∈[1,T];After solving the electric and thermal integrated energy system model, the reactive power Q output by the w-th wind farm in the transmission system model at the t-th future time is w,t wind,* ,w∈[1,W],t∈[1,T];After solving the electric-thermal integrated energy system model, the output active power P of the i-th CHP in the electric-thermal coupling device at the t-th future moment is i,t CHP,* ,i∈[1,N CHP ], t∈[1,T]; after solving the electric-thermal integrated energy system model, the reactive power Q output by the i-th CHP in the electric-thermal coupling device at the t-th future moment is i,t CHP ,* ,i∈[1,N CHP ], t∈[1,T]; after solving the electric-thermal integrated energy system model, the thermal power H output by the i-th CHP in the electric-thermal coupling device at the t-th future moment is i,t CHP,* ,i∈[1,N CHP ], t∈[1,T]; after solving the electric-thermal integrated energy system model, the input gas flow F of the i-th CHP in the electric-thermal coupling device at the t-th future moment i,t CHP,* ,i∈[1,N CHP ], t∈[1,T]; after solving the electrical and thermal integrated energy system model, the active power P input at the tth future moment of the i-th P2G in the electrical coupling device is i,t P2G,* ,i∈[1,N P2G ], t∈[1,T]; the output gas flow F of the i-th P2G in the electrical coupling device at the t-th future moment after solving the electrical and thermal integrated energy system model i,t P2G,* ,i∈[1,N P2G ], t∈[1,T]; the output gas flow of the wth gas source at the tth future time in the future gas system model is solved by the electric and thermal integrated energy system model The total operating cost f1 of the electric heating system after solving the electric heating integrated energy system model * ; Total operating cost of the natural gas system after solving the electric and thermal integrated energy system model f2 * ; W represents the number of wind farms in the transmission system model, G represents the number of generators in the transmission system model, and W su p represents the number of gas source points in the natural gas system model, N P2G Indicates the number of P2Gs in the electrical coupling device, N CHP represents the number of CHPs in the electrothermal coupling device, and T represents the number at a future time.

9. An advance scheduling system for an electric and thermal integrated energy system, used to execute the method according to any one of claims 1 to 8, characterized in that: include: The electric-thermal integrated energy system model construction module couples the power transmission system model with the heating system model through electric-thermal coupling equipment, and couples the power transmission system model with the electric-thermal system model through electric coupling equipment; The load forecasting module uses a long-short-term memory artificial neural network to predict the electric load, thermal load, and gas load at multiple future moments. Constraint construction module, which builds system backup constraints, generator set operation constraints, wind farm operation constraints, power network constraints, thermal system operation constraints, gas source point constraints, pipeline constraints, node supply and demand balance constraints, and establishes coupled equipment constraints; The system optimization target construction module constructs the electric and thermal system target model and the natural gas system target model of the electric and thermal integrated energy system respectively; The alternating iterative optimization solution module uses the alternating iterative optimization method to optimize and solve the variables of the electrical and thermal integrated energy system at multiple prediction moments.

10. A computer-readable medium, characterized in that It stores a computer program executed by an electronic device, and when the computer program runs on the electronic device, the electronic device executes the steps of the method according to any one of claims 1 to 8.

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