An electrical integrated energy system operation optimization method and related device

Abstract

Embodiments of the present application disclose a kind of electrical integrated energy system operation optimization method and related equipment, the method comprises: obtaining the basic operation parameter of electrical integrated energy system, and the dynamic model of electrical integrated energy system is constructed, the dynamic model includes power system model, gas system model and coupling element model, the coupling element model includes electric gas equipment model and gas turbine model;The target dynamic model is obtained by algebraic processing to the dynamic model;Under the preset boundary condition, the target operation parameter when the target dynamic model operation cost is lowest is determined, and the optimization of electrical integrated energy system operation is completed based on the target operation parameter.For the model of coupling element in electrical integrated energy system, it is advantageous to describe the detailed relationship of power and gas in pressure, temperature, power distribution and the like, so as to accurately formulate the operation control strategy of electrical integrated energy system, improve the economy and safety of system.

Description

Technical Field

[0001] This invention relates to the field of energy management and application technology, and in particular to a method and related equipment for optimizing the operation of an integrated electrical energy system. Background Technology

[0002] As the negative impacts of climate change and environmental pollution intensify, countries worldwide are exploring new forms of clean, efficient, and sustainable energy utilization. Against this backdrop, the European Union has proposed building a pan-European smart energy network; the United States and Japan have also respectively proposed "hydrogen plans" and "integrated energy plans" to transform energy utilization. Conducting research on core technologies for multi-energy complementarity aligns with significant energy strategic needs. With the energy internet, smart energy, and multi-energy complementarity as development directions, we are actively promoting the theoretical research and engineering applications of multi-energy complementary integrated energy systems. As a typical form of integrated energy system, the integrated electric energy system couples the electricity and gas subsystems through equipment such as cogeneration units. Unlike traditional discrete energy systems, gas turbines and electro-gasification equipment can fully utilize the complementary conversion relationship between electricity and gas to improve economic efficiency, promote the consumption of renewable energy, and have broad application prospects.

[0003] Operational optimization of an integrated electrical system involves optimizing certain state variables within the system under given boundary conditions to achieve the optimal state distribution for a specific performance index (such as economy, environmental friendliness, and energy efficiency). The operational optimization model is described by nonlinear partial differential equations, ordinary differential equations, and algebra. However, existing research generally neglects the nonlinearity and dynamics of the coupled components in the system, simplifying the complex characteristics of the state variables in the integrated electrical energy system, resulting in significant discrepancies between the obtained results and the actual situation. Summary of the Invention

[0004] In view of this, the present invention provides a method and related equipment for optimizing the operation of an integrated electrical energy system, which is used to solve the problem that there is a large difference between the simulation results and the actual situation in the operation optimization process of an integrated electrical system in the prior art.

[0005] To achieve one or more of the above objectives or other objectives, the present invention proposes an operation optimization method for an integrated electrical energy system, comprising: obtaining basic operating parameters of the integrated electrical energy system and constructing a dynamic model of the integrated electrical energy system, wherein the dynamic model includes a power system model, a gas system model and a coupling element model, wherein the coupling element model includes an electric gas generator model and a gas turbine model;

[0006] The dynamic model is algebraically transformed to obtain the target dynamic model;

[0007] Under preset boundary conditions, the target operating parameters that minimize the operating cost of the target dynamic model are determined, and the operation of the integrated electrical energy system is optimized based on the target operating parameters.

[0008] Optionally, the step of obtaining the basic operating parameters of the integrated electrical energy system and constructing a dynamic model of the integrated electrical energy system includes:

[0009] Obtain the power operation parameters of the power unit in the electrical integrated energy system, the gas operation parameters of the gas unit in the electrical integrated energy system, and the coupling operation parameters of the coupling unit in the electrical integrated energy system;

[0010] The power system model is constructed using an alternating current power flow description method to depict the power flow distribution of the power system.

[0011] The gas system model is constructed by using the gas pressure and gas mass flow rate in the gas operating parameters as variables.

[0012] The coupling element model is constructed based on the coupling operation parameters.

[0013] Optionally, the step of constructing the coupled element model based on the coupled operating parameters includes:

[0014] The coupling element model includes the electric gas generator model and the gas turbine model, wherein the electric gas generator model is:

[0015]

[0016] In the formula, P pg,t q pg,t and p pg,t The electrical power consumption, output gas mass flow rate, and pressure of the electrogas generator at time t are respectively, and h is the output gas mass flow rate and pressure. g η represents the unit calorific value of the gas. pg The conversion efficiency of the electro-gas generator;

[0017] The gas turbine model includes a compressor model, a combustion chamber model, and a steam turbine model, wherein the compressor model is represented as follows:

[0018]

[0019] To determine the relationship between the compressor outlet temperature and inlet temperature, T i cp,t and T o cp,t These represent the compressor inlet and outlet temperatures, respectively, in K. cp1 K represents the compressor pressure ratio. cp2 K represents the adiabatic efficiency of the compressor. cp3This represents the isentropic air coefficient of the compressor;

[0020]

[0021] To determine the relationship between the compressor outlet pressure and inlet pressure, p i cp,t and p o cp,t These represent the compressor inlet and outlet pressures, respectively.

[0022]

[0023] To determine the power consumption of the compressor, η cp q represents the mechanical efficiency of the compressor. a,t This indicates the mass flow rate of the air entering the compressor;

[0024] The combustion chamber model is as follows:

[0025]

[0026] In the formula, C a and C s q represents the specific heat capacity of air and the mixed flue gas, respectively. g,t To input the gas flow rate into the combustion chamber, T cc,t K represents the combustion chamber outlet temperature. cc1 K is the heat storage coefficient of the combustion chamber. cc2 The lower heating value of the gas;

[0027] The turbine model is as follows:

[0028]

[0029] P tb,t =(q a,t +q g,t C s (T tb,t -T cc,t )

[0030] P gt,t =K tb3 (P tb,t -P cp,t )

[0031] Among them, T tb,t and p tb,t K represents the temperature and pressure of the steam turbine. tb1 K represents the isentropic natural gas coefficient. tb2 K represents the internal efficiency of the steam turbine. tb3 P represents the overall mechanical efficiency of a gas turbine. tb,t P represents the electrical power generated by the steam turbine. gt,tThe effective electrical power output by the gas turbine;

[0032] The coupling element model is obtained based on the electric gas generator model, the compressor model, the combustion chamber model, and the steam turbine model.

[0033] Optionally, the step of constructing the power system model using AC power flow to describe the power flow distribution includes:

[0034] The power system model is constructed by using AC power flow to describe the power flow distribution, specifically as follows:

[0035]

[0036] {Q l,ij =U i U j (G ij sinθ ij -B ij cosθ ij )+B ij U i 2 i,j∈V e

[0037] Among them, U i P represents the voltage magnitude at node i. G,i and P L,i Q represents the active power of the generator and load at node i. G,i and Q L,i G represents the reactive power of the generator and load at node i. ij and B ij θ represents the conductance and susceptance between node i and node j. ij V represents the phase angle difference between node i and node j. e P represents the set of nodes in a power system. l,ij and Q l,i j represents the transmission power between node i and node j.

[0038] Optionally, the step of constructing the gas system model using the gas pressure and gas mass flow rate from the gas operating parameters as variables includes:

[0039] The gas system model is constructed by using gas pressure and gas mass flow rate from the gas operating parameters as variables, specifically:

[0040]

[0041]

[0042]

[0043] Where x and t represent spatial and temporal variables, respectively; p and q represent pipe pressure and pipe mass flow rate, respectively; pn and qn represent nodal pressure and nodal mass flow rate, respectively; c is the velocity of sound; S is the pipe cross-sectional area; D is the pipe inner diameter; and λ is the pipe friction coefficient V. g E represents the set of nodes in a gas system. in k E represents the set of pipelines flowing into node k. out k p represents the set of pipes flowing out from node k. i,Nx p represents the outlet pressure of pipe i. n,0 q represents the inlet pressure of pipe n. i,0 q represents the inlet mass flow rate of pipe i. i,Nx This represents the outlet mass flow rate of pipe i.

[0044] Optionally, the step of performing algebraic processing on the dynamic model to obtain the target dynamic model includes:

[0045] The gas system model in the dynamic model is algebraized using the method of characteristics;

[0046] The gas turbine model was algebraized using a backward difference scheme.

[0047] The target dynamic model is obtained based on the algebraic gas system model and the algebraic gas turbine model.

[0048] Optionally, the step of determining the target operating parameters that minimize the operating cost of the target dynamic model under preset boundary conditions, and optimizing the operation of the integrated electrical energy system based on the target operating parameters, includes:

[0049] Based on the preset boundary conditions, establish safety constraints for power system operation, safety constraints for gas system operation, and safety constraints for coupling element operation;

[0050] The target dynamic model is run based on the power system operation safety constraints, the gas system operation safety constraints, and the coupling element operation safety constraints to obtain the set of operating costs of the target dynamic model;

[0051] Select the minimum value from the set of operating costs to determine the target operating parameters when the operating cost of the target dynamic model is the lowest, and optimize the operation of the integrated electrical energy system based on the target operating parameters.

[0052] On the other hand, this application provides an electrical integrated energy system operation optimization system, the system comprising:

[0053] The model building module is used to obtain the basic operating parameters of the integrated electrical energy system and build a dynamic model of the integrated electrical energy system. The dynamic model includes a power system model, a gas system model, and a coupling element model. The coupling element model includes an electric gas generator model and a gas turbine model.

[0054] The model optimization module is used to perform algebraic processing on the dynamic model to obtain the target dynamic model;

[0055] The parameter determination module is used to determine the target operating parameters when the operating cost of the target dynamic model is minimized under preset boundary conditions, and to optimize the operation of the integrated electrical energy system based on the target operating parameters.

[0056] Thirdly, this application provides an electronic device, including: a processor, a memory, and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor communicates with the memory through the bus, and when the machine-readable instructions are executed by the processor, the steps of the above-described integrated electrical energy system operation optimization method are performed.

[0057] Fourthly, this application provides a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the above-described method for optimizing the operation of an integrated electrical energy system.

[0058] Implementing the embodiments of the present invention will have the following beneficial effects:

[0059] By acquiring the basic operating parameters of the integrated electrical energy system and constructing a dynamic model of the system, including a power system model, a gas system model, and coupling element models (including an electro-gas generator model and a gas turbine model), the dynamic model is algebraically transformed to obtain a target dynamic model. Under preset boundary conditions, the target operating parameters that minimize the operating cost of the target dynamic model are determined, and the operation of the integrated electrical energy system is optimized based on these target operating parameters. Accurate modeling of the coupling relationship between the power system and the gas system in the integrated electrical energy system is beneficial for describing the detailed relationships between electricity and gas in terms of pressure, temperature, and power distribution, thereby accurately formulating operation control strategies for the integrated electrical energy system and improving the system's economy and safety. Attached Figure Description

[0060] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0061] in:

[0062] Figure 1 This is a flowchart of an electrical integrated energy system operation optimization method provided in an embodiment of this application;

[0063] Figure 2 This is the topology of the integrated electrothermal energy system in this embodiment of the invention;

[0064] Figure 3 This is the time-series optimization result of the gas source mass flow rate of node 1 in the gas system in this embodiment of the invention;

[0065] Figure 4 This is the timing optimization result of the phase angle of node 2 in the power system in this embodiment of the invention;

[0066] Figure 5 This is a schematic diagram of the structure of an electrical integrated energy system operation optimization system provided in an embodiment of this application;

[0067] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application;

[0068] Figure 7 This is a schematic diagram of the structure of a storage medium provided in an embodiment of this application. Detailed Implementation

[0069] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0070] like Figure 1 As shown in the figure, this application provides a method for optimizing the operation of an integrated electrical energy system, including:

[0071] S101. Obtain the basic operating parameters of the integrated electrical energy system and construct a dynamic model of the integrated electrical energy system. The dynamic model includes a power system model, a gas system model, and a coupling element model. The coupling element model includes an electric gas generator model and a gas turbine model.

[0072] S102. Perform algebraic processing on the dynamic model to obtain the target dynamic model;

[0073] S103. Under preset boundary conditions, determine the target operating parameters when the operating cost of the target dynamic model is minimized, and optimize the operation of the integrated electrical energy system based on the target operating parameters.

[0074] By acquiring the basic operating parameters of the integrated electrical energy system and constructing a dynamic model of the system, including a power system model, a gas system model, and coupling element models (including an electro-gas generator model and a gas turbine model), the dynamic model is algebraically transformed to obtain a target dynamic model. Under preset boundary conditions, the target operating parameters that minimize the operating cost of the target dynamic model are determined, and the operation of the integrated electrical energy system is optimized based on these target operating parameters. Accurate modeling of the coupling relationship between the power system and the gas system in the integrated electrical energy system is beneficial for describing the detailed relationships between electricity and gas in terms of pressure, temperature, and power distribution, thereby accurately formulating operation control strategies for the integrated electrical energy system and improving the system's economy and safety.

[0075] In one possible implementation, the step of obtaining the basic operating parameters of the integrated electrical energy system and constructing a dynamic model of the integrated electrical energy system includes:

[0076] Obtain the power operation parameters of the power unit in the electrical integrated energy system, the gas operation parameters of the gas unit in the electrical integrated energy system, and the coupling operation parameters of the coupling unit in the electrical integrated energy system;

[0077] The power system model is constructed using an alternating current power flow description method to depict the power flow distribution of the power system.

[0078] The gas system model is constructed by using the gas pressure and gas mass flow rate in the gas operating parameters as variables.

[0079] The coupling element model is constructed based on the coupling operation parameters.

[0080] In one possible implementation, the step of constructing the coupled element model based on the coupled operating parameters includes:

[0081] The coupling element model includes the electric gas generator model and the gas turbine model, wherein the electric gas generator model is:

[0082]

[0083] In the formula, P pg,t q pg,tand p pg,t The electrical power consumption, output gas mass flow rate, and pressure of the electrogas generator at time t are respectively, and h is the output gas mass flow rate and pressure. g η represents the unit calorific value of the gas. pg The conversion efficiency of the electro-gas generator;

[0084] The gas turbine model includes a compressor model, a combustion chamber model, and a steam turbine model, wherein the compressor model is represented as follows:

[0085]

[0086] To determine the relationship between the compressor outlet temperature and inlet temperature, T i cp,t and T o cp,t These represent the compressor inlet and outlet temperatures, respectively, in K. cp1 K represents the compressor pressure ratio. cp2 K represents the adiabatic efficiency of the compressor. cp3 This represents the isentropic air coefficient of the compressor;

[0087]

[0088] To determine the relationship between the compressor outlet pressure and inlet pressure, p i cp,t and p o cp,t These represent the compressor inlet and outlet pressures, respectively.

[0089]

[0090] To determine the power consumption of the compressor, η cp q represents the mechanical efficiency of the compressor. a,t This indicates the mass flow rate of the air entering the compressor;

[0091] The combustion chamber model is as follows:

[0092]

[0093] In the formula, C a and C s q represents the specific heat capacity of air and the mixed flue gas, respectively. g,t To input the gas flow rate into the combustion chamber, T cc,t K represents the combustion chamber outlet temperature. cc1 K is the heat storage coefficient of the combustion chamber. cc2 The lower heating value of the gas;

[0094] The turbine model is as follows:

[0095]

[0096] P tb,t =(q a,t +q g,t C s (T tb,t -T cc,t )

[0097] P gt,t =K tb3 (P tb,t -P cp,t )

[0098] Among them, T tb,t and p tb,t K represents the temperature and pressure of the steam turbine. tb1 K represents the isentropic natural gas coefficient. tb2 K represents the internal efficiency of the steam turbine. tb3 P represents the overall mechanical efficiency of a gas turbine. tb,t P represents the electrical power generated by the steam turbine. gt,t The effective electrical power output by the gas turbine;

[0099] The coupling element model is obtained based on the electric gas generator model, the compressor model, the combustion chamber model, and the steam turbine model.

[0100] In one possible implementation, the step of constructing the power system model using an AC power flow description method for power system power flow distribution includes:

[0101] The power system model is constructed by using AC power flow to describe the power flow distribution, specifically as follows:

[0102]

[0103] {Q l,ij =U i U j (G ij sinθ ij -B ij cosθ ij )+B ij U i 2 i,j∈V e

[0104] Among them, U i P represents the voltage magnitude at node i. G,i and P L,i Q represents the active power of the generator and load at node i. G,i and Q L,i G represents the reactive power of the generator and load at node i. ij and B ijθ represents the conductance and susceptance between node i and node j. ij V represents the phase angle difference between node i and node j. e P represents the set of nodes in a power system. l,ij and Q l,i j represents the transmission power between node i and node j.

[0105] In one possible implementation, the step of constructing the gas system model using gas pressure and gas mass flow rate as variables in the gas operating parameters includes:

[0106] The gas system model is constructed by using gas pressure and gas mass flow rate from the gas operating parameters as variables, specifically:

[0107]

[0108]

[0109]

[0110] Where x and t represent spatial and temporal variables, respectively; p and q represent pipe pressure and pipe mass flow rate, respectively; pn and qn represent nodal pressure and nodal mass flow rate, respectively; c is the velocity of sound; S is the pipe cross-sectional area; D is the pipe inner diameter; and λ is the pipe friction coefficient V. g E represents the set of nodes in a gas system. in k E represents the set of pipelines flowing into node k. out k p represents the set of pipes flowing out from node k. i,Nx p represents the outlet pressure of pipe i. n,0 q represents the inlet pressure of pipe n. i,0 q represents the inlet mass flow rate of pipe i. i,Nx This represents the outlet mass flow rate of pipe i.

[0111] In one possible implementation, the step of performing algebraic processing on the dynamic model to obtain the target dynamic model includes:

[0112] The gas system model in the dynamic model is algebraized using the method of characteristics;

[0113] The gas turbine model was algebraized using a backward difference scheme.

[0114] The target dynamic model is obtained based on the algebraic gas system model and the algebraic gas turbine model.

[0115] For example, the method of characteristics is used to algebraize the partial differential form of the gas system model. Defining the pipe length as L and the time interval under study as τ, dividing the study interval equally yields the discrete time and spatial step sizes:

[0116]

[0117] In the formula, Δx and Δt are the spatial and time steps, respectively, and N1 and N2 are the spatial and time steps, respectively.

[0118] based on

[0119]

[0120] The conditions shown will

[0121]

[0122] and

[0123]

[0124] Transformed into two sets of characteristic line equations:

[0125]

[0126]

[0127] In the formula, and Indicates positive and negative characteristic lines, for

[0128]

[0129] In the interval (x i-1 ,t j ) and (x i ,t j+1 Integrating, we get:

[0130]

[0131] Similarly, for the above expression in the interval (x i ,t j+1 ) and (x i+1 ,t j By integrating, we can obtain:

[0132]

[0133] Discretizing the integral terms in the above equation yields the algebraic form of the system of characteristic line equations:

[0134]

[0135]

[0136] In the formula, p j+1 i p represents the pressure at pipe iΔx at time j+1. j i-1 q represents the pressure at pipe (i-1)Δx at time j. j+1 i q represents the mass flow rate at pipe iΔx at time j+1. j i- 1 represents the mass flow rate at pipe (i-1)Δx at time j, pn j+1 x＝0 and qn j+1 x＝0 pn represents the pressure and mass flow rate at the beginning node of the pipeline at time j+1. j+1 x＝L and qn j+1 x＝L This represents the pressure and mass flow rate at the end node of the pipeline at time j+1.

[0137] Discretizing the equation using a backward difference scheme yields:

[0138]

[0139] In the formula, T cc,t-Δt Let t be the combustion chamber temperature at time t-Δt.

[0140] In one possible implementation, the step of determining the target operating parameters that minimize the operating cost of the target dynamic model under preset boundary conditions, and optimizing the operation of the integrated electrical energy system based on the target operating parameters, includes:

[0141] Based on the preset boundary conditions, establish safety constraints for power system operation, safety constraints for gas system operation, and safety constraints for coupling element operation;

[0142] The target dynamic model is run based on the power system operation safety constraints, the gas system operation safety constraints, and the coupling element operation safety constraints to obtain the set of operating costs of the target dynamic model;

[0143] Select the minimum value from the set of operating costs to determine the target operating parameters when the operating cost of the target dynamic model is the lowest, and optimize the operation of the integrated electrical energy system based on the target operating parameters.

[0144] For example, establishing power system operation safety constraints, including node voltage magnitude constraints, generator output power constraints, and branch power constraints, can be expressed as follows:

[0145] Ui,min ≤U i ≤U i,max i∈V e

[0146] P G,i,min ≤P G,i ≤P G,i,max Q G,i,min ≤Q G,i ≤Q G,i,max i∈V e

[0147]

[0148] In the formula, U i,min and U i,max These are the lower and upper limits of the voltage amplitude at node i, respectively; P G,i,min and P G,i,max Q represents the lower and upper limits of the active power output of the generator at node i, respectively; G,i,min and Q G,i,max These represent the lower and upper limits of the reactive power output of the generator at node i, respectively; P G,i,min and P G,i,max These represent the lower and upper limits of the active power output of the generator at node i, respectively; S l,ij,max These represent the upper limit of the actual power transmitted between nodes i and j, respectively.

[0149] Establishing safety constraints for the operation of a gas system, including branch pressure and flow rate, and node pressure and flow rate constraints, can be expressed as:

[0150] pn i,min ≤pn i ≤pn i,max ,qn i,min ≤qn i ≤qn i,max i∈V g

[0151]

[0152]

[0153] Among them, pn i,min and pn i,max These are the lower and upper pressure limits for node i in the gas system, respectively; qn i,min and qn i,max These are the lower and upper limits of the mass flow rate of node i in the gas system, respectively; p k,min and p k,max These represent the lower and upper pressure limits of pipeline k in the gas system, respectively; q k,min and q k,maxThese are the lower and upper limits of the mass flow rate of pipe k in the gas system, respectively, E g This represents the pipeline set of a gas system.

[0154] Establish safety constraints for the operation of coupling components, including input pressure and mass flow rate constraints for the electrostatic precipitator; compressor inlet pressure and temperature constraints, input air mass flow rate and gas mass flow rate constraints, air-gas mixture ratio constraints, and turbine pressure and temperature constraints in the gas turbine, which can be expressed as:

[0155] q pg,min ≤q pg,t ≤q pg,max ,p pg,min ≤p pg,t ≤p pg,max

[0156]

[0157] q a,min ≤q a,t ≤q a,max ,q g,min ≤q g,t ≤q g,max

[0158] rate min ≤q g,t / q a,t ≤rate max

[0159] T tb,min ≤T tb,t ≤T tb,max ,p tb,min ≤p tb,t ≤p tb,max

[0160] Where, q pg,min and q pg,max These are the lower and upper limits of the input gas flow rate for the electric gas generator, respectively; p pg,min and p pg,max These are the lower and upper limits of the input gas pressure for the electric gas generator, respectively. and These are the lower and upper limits of the compressor inlet pressure in the gas turbine, respectively. and These are the lower and upper limits of the compressor inlet temperature in the gas turbine, respectively; q a,min and q a,max These are the lower and upper limits of the compressor input airflow, respectively; q g,min and q g,max These are the lower and upper limits of the combustion chamber input airflow, respectively; p tb,min and p tb,maxThese are the lower and upper limits of the turbine outlet pressure, respectively; T tb,min and T tb,max These are the lower and upper limits of turbine temperature and pressure, respectively; rate min and rate max These are the lower and upper limits for the mixing ratio of gas and air.

[0161] With the goal of minimizing operating costs and incorporating safety constraints, a method for optimizing the operation of an integrated electrical energy system that considers equipment dynamics is proposed, as shown in the following formula:

[0162]

[0163] st power system constraints: (1)-(2), (23)-(25)

[0164] Gas system constraints: (5), (20)-(21), (26)-(28)

[0165] Coupling element constraints: (6)-(9), (11)-(13), (22), (29)-(33)

[0166] Where, μ 1-6,i Let be the cost function coefficient of the generator or gas source node at node i. The power system constraints are:

[0167]

[0168]

[0169] U i,min ≤U i ≤U i,max i∈V e (twenty three)

[0170] P G,i,min ≤P G,i ≤P G,i,max Q G,i,min ≤Q G,i ≤Q G,i,max i∈V e (twenty four)

[0171]

[0172] The gas system constraints are:

[0173]

[0174]

[0175]

[0176] pni,min ≤pn i ≤pn i,max ,qn i,min ≤qn i ≤qn i,max i∈V g (26)

[0177]

[0178]

[0179] The coupling element constraints are:

[0180]

[0181]

[0182]

[0183]

[0184]

[0185] P tb,t =(q a,t +q g,t C s (T tb,t -T cc,t (12)

[0186] P gt,t =K tb3 (P tb,t -P cp,t (13)

[0187]

[0188] q pg,min ≤q pg,t ≤q pg,max ,p pg,min ≤p pg,t ≤p pg,max (29)

[0189]

[0190] q a,min ≤q a,t ≤q a,max ,q g,min ≤q g,t ≤q g,max (31)

[0191] rate min ≤qg,t / q a,t ≤rate max (32)

[0192] T tb,min ≤T tb,t ≤T tb,max ,p tb,min ≤p tb,t ≤p tb,max (33)

[0193] by Figure 2 Taking the system shown as an example, with a calculation period of 12 hours, a time step of 5 seconds, and a spatial step of 10200 meters, the time-series optimization results of the gas source mass flow rate of node 1 in the gas system are as follows: Figure 3 As shown, the timing optimization results of the phase angle at node 2 of the power system are as follows: Figure 4 As shown.

[0194] On the other hand, such as Figure 5 As shown, this application provides an electrical integrated energy system operation optimization system, the system comprising:

[0195] The model building module 201 is used to obtain the basic operating parameters of the integrated electrical energy system and build a dynamic model of the integrated electrical energy system. The dynamic model includes a power system model, a gas system model and a coupling element model. The coupling element model includes an electric gas generator model and a gas turbine model.

[0196] Model optimization module 202 is used to perform algebraic processing on the dynamic model to obtain the target dynamic model;

[0197] The parameter determination module 203 is used to determine the target operating parameters when the operating cost of the target dynamic model is minimized under preset boundary conditions, and to optimize the operation of the integrated electrical energy system based on the target operating parameters.

[0198] One possible implementation, such as Figure 6 As shown, this application embodiment provides an electronic device 300, including: a memory 310, a processor 320, and a computer program 311 stored in the memory 310 and executable on the processor 320. When the processor 320 executes the computer program 311, it performs the following steps: acquiring a user business request, wherein the business request includes business scenario information and task information; constructing a basic behavior graph knowledge base based on the business scenario information; matching a preset task execution process in a preset template library according to the scenario information and the task information; evaluating the matched preset task execution process according to the basic behavior graph knowledge base and a preset analysis and decision model, obtaining a scheduling execution strategy, and completing the robot scheduling based on the scheduling execution strategy.

[0199] In one possible implementation, such as Figure 7 As shown, this application embodiment provides a computer-readable storage medium 400, on which a computer program 411 is stored. When executed by a processor, the computer program 411 implements the following steps: obtaining a user business request, wherein the business request includes business scenario information and task information; constructing a basic behavior graph knowledge base based on the business scenario information; matching a preset task execution process in a preset template library according to the scenario information and the task information; evaluating the matched preset task execution process according to the basic behavior graph knowledge base and a preset analysis and decision model, obtaining a scheduling execution strategy, and completing the robot scheduling based on the scheduling execution strategy.

[0200] The computer storage medium of this invention can be any combination of one or more computer-readable media. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. For example, a computer-readable storage medium can be, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0201] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of sending, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0202] Program code contained on a computer-readable medium may be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0203] Computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof. These programming languages ​​include object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages—such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0204] Those skilled in the art will understand that the modules or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby allowing them to be stored in a storage device for execution by a computing device, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0205] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

[0206] The above description discloses only preferred embodiments of the present invention and should not be construed as limiting the scope of the present invention. Therefore, equivalent variations made in accordance with the claims of the present invention are still within the scope of the present invention.

Claims

1. A method for optimizing the operation of an integrated electrical energy system, characterized in that, include: The basic operating parameters of the integrated electrical energy system are obtained, and a dynamic model of the integrated electrical energy system is constructed. The dynamic model includes a power system model, a gas system model, and a coupling element model. The coupling element model includes an electric gas generator model and a gas turbine model. The dynamic model is algebraically transformed to obtain the target dynamic model; The step of performing algebraic processing on the dynamic model to obtain the target dynamic model includes: The method of characteristics is used to algebraize the gas system model in the form of partial differential equations in the dynamic model; Define the pipe length as L, and the time interval to be studied as τ. Divide the study interval into equal parts to obtain the discrete time and space steps as follows: In the formula, x and t represents the spatial and temporal step size, respectively, and N1 and N2 represent the number of spatial and temporal steps, respectively; based on The conditions shown will and Transformed into two sets of characteristic line equations: In the formula, and Indicates positive and negative characteristic lines, for In the interval (x i-1 ,t j ) and (x i ,t j+1 Integrating, we get: For the above expression in the interval (x i ,t j+1 ) and (x i+1 ,t j By integrating, we can obtain: Discretizing the integral terms in the above equation yields the algebraic form of the system of characteristic line equations: In the formula, Indicates the time of pipe i at time j+1 Pressure at point x This represents the pipe (i-1) at time j. Pressure at point x Indicates the time of pipe i at time j+1 Mass flow rate at point x This represents the pipe (i-1) at time j. Mass flow rate at x, p and q p represents the pressure and mass flow rate at the beginning node of the pipeline at time j+1. and q This represents the pressure and mass flow rate at the end node of the pipeline at time j+1; The gas turbine model is algebraized using a backward difference scheme, resulting in: In the formula, For t- Combustion chamber temperature at time t; The target dynamic model is obtained based on the algebraic gas system model and the algebraic gas turbine model. Obtain the power operation parameters of the power unit in the electrical integrated energy system, the gas operation parameters of the gas unit in the electrical integrated energy system, and the coupling operation parameters of the coupling unit in the electrical integrated energy system; The gas system model is constructed by using gas pressure and gas mass flow rate from the gas operating parameters as variables, specifically: Where x and t represent spatial and temporal variables, respectively; p and q represent pipe pressure and pipe mass flow rate, respectively; pn and qn represent nodal pressure and nodal mass flow rate, respectively; c is the velocity of sound; S is the pipe cross-sectional area; D is the pipe inner diameter; and λ is the pipe friction coefficient V. g E represents the set of nodes in a gas system. in k E represents the set of pipelines flowing into node k. out k p represents the set of pipes flowing out from node k. i,Nx p represents the outlet pressure of pipe i. n,0 q represents the inlet pressure of pipe n. i,0 q represents the inlet mass flow rate of pipe i. i, Nx This represents the outlet mass flow rate of pipe i; The gas turbine model includes a compressor model, a combustion chamber model, and a steam turbine model, wherein the compressor model is represented as follows: To determine the relationship between the compressor outlet temperature and inlet temperature, T i cp,t and T o cp,t These represent the compressor inlet and outlet temperatures, respectively, in K. cp1 K represents the compressor pressure ratio. cp2 K represents the adiabatic efficiency of the compressor. cp3 This represents the isentropic air coefficient of the compressor; To determine the relationship between the compressor outlet pressure and inlet pressure, p i cp,t and p o cp,t These represent the compressor inlet and outlet pressures, respectively. To determine the power consumption of the compressor, η cp q represents the mechanical efficiency of the compressor. a,t This indicates the mass flow rate of the air entering the compressor; The combustion chamber model is as follows: In the formula, C a and C s q represents the specific heat capacity of air and the mixed flue gas, respectively. g,t To input the gas flow rate into the combustion chamber, T cc,t K represents the combustion chamber outlet temperature. cc1 K is the heat storage coefficient of the combustion chamber. cc2 The lower heating value of the gas; The turbine model is as follows: Among them, T tb,t and p tb,t K represents the temperature and pressure of the steam turbine. tb1 K represents the isentropic natural gas coefficient. tb2 K represents the internal efficiency of the steam turbine. tb3 P represents the overall mechanical efficiency of a gas turbine. tb,t P represents the electrical power generated by the steam turbine. gt,t The effective electrical power output by the gas turbine; Under preset boundary conditions, the target operating parameters that minimize the operating cost of the target dynamic model are determined, and the operation of the integrated electrical energy system is optimized based on the target operating parameters.

2. The method for optimizing the operation of an integrated electrical energy system as described in claim 1, characterized in that, The steps of obtaining the basic operating parameters of the integrated electrical energy system and constructing a dynamic model of the integrated electrical energy system include: The power system model is constructed using an alternating current power flow description method to depict the power flow distribution of the power system. The gas system model is constructed by using the gas pressure and gas mass flow rate in the gas operating parameters as variables. The coupling element model is constructed based on the coupling operation parameters.

3. The method for optimizing the operation of an integrated electrical energy system as described in claim 2, characterized in that, The step of constructing the coupled element model based on the coupled operating parameters includes: The coupling element model includes the electric gas generator model and the gas turbine model, wherein the electric gas generator model is: In the formula, P pg,t q pg,t and p pg,t The electrical power consumption, output gas mass flow rate, and pressure of the electrogas generator at time t are respectively, and h is the output gas mass flow rate and pressure. g η represents the unit calorific value of the gas. pg The conversion efficiency of the electro-gas generator; The coupling element model is obtained based on the electric gas generator model, the compressor model, the combustion chamber model, and the steam turbine model.

4. The method for optimizing the operation of an integrated electrical energy system as described in claim 2, characterized in that, The steps for constructing the power system model using AC power flow to describe the power flow distribution include: The power system model is constructed by using AC power flow to describe the power flow distribution, specifically as follows: Among them, U i P represents the voltage magnitude at node i. G,i and P L,i Q represents the active power of the generator and load at node i. G,i and Q L,i G represents the reactive power of the generator and load at node i. ij and B ij θ represents the conductance and susceptance between node i and node j. ij V represents the phase angle difference between node i and node j. e P represents the set of nodes in a power system. l,ij and Q l,i j represents the transmission power between node i and node j.

5. The method for optimizing the operation of an integrated electrical energy system as described in claim 1, characterized in that, The step of determining the target operating parameters that minimize the operating cost of the target dynamic model under preset boundary conditions, and optimizing the operation of the integrated electrical energy system based on the target operating parameters, includes: Based on the preset boundary conditions, establish safety constraints for power system operation, safety constraints for gas system operation, and safety constraints for coupling element operation; The target dynamic model is run based on the power system operation safety constraints, the gas system operation safety constraints, and the coupling element operation safety constraints to obtain the set of operating costs of the target dynamic model; Select the minimum value from the set of operating costs to determine the target operating parameters when the operating cost of the target dynamic model is the lowest, and optimize the operation of the integrated electrical energy system based on the target operating parameters.

6. An electrical integrated energy system operation optimization system, characterized in that, The system includes: The model building module is used to obtain the basic operating parameters of the integrated electrical energy system and build a dynamic model of the integrated electrical energy system. The dynamic model includes a power system model, a gas system model, and a coupling element model. The coupling element model includes an electric gas generator model and a gas turbine model. The model optimization module is used to perform algebraic processing on the dynamic model to obtain the target dynamic model; The step of performing algebraic processing on the dynamic model to obtain the target dynamic model includes: The method of characteristics is used to algebraize the gas system model in the form of partial differential equations in the dynamic model; Define the pipe length as L, and the time interval to be studied as τ. Divide the study interval into equal parts to obtain the discrete time and space steps as follows: In the formula, x and t represents the spatial and temporal step size, respectively, and N1 and N2 represent the number of spatial and temporal steps, respectively; based on The conditions shown will and Transformed into two sets of characteristic line equations: In the formula, + and - Indicates positive and negative characteristic lines, for In the interval (x i-1 ,t j ) and (x i ,t j+1 Integrating, we get: For the above expression in the interval (x i ,t j+1 ) and (x i+1 ,t j By integrating, we can obtain: Discretizing the integral terms in the above equation yields the algebraic form of the system of characteristic line equations: In the formula, p j+1 i Indicates the time of pipe i at time j+1 The pressure at point x, p j i-1 This represents the pipe (i-1) at time j. The pressure at point x, q j+1 i Indicates the time of pipe i at time j+1 Mass flow rate at x, q j i- 1 indicates that the pipe (i-1) is at time j. Mass flow rate at x, pn j+1 x=0 and qn j+1 x=0 pn represents the pressure and mass flow rate at the beginning node of the pipeline at time j+1. j+1 x=L and qn j+1 x=L This represents the pressure and mass flow rate at the end node of the pipeline at time j+1; The gas turbine model is algebraized using a backward difference scheme, resulting in: In the formula, T cc,t- t For t- Combustion chamber temperature at time t; The target dynamic model is obtained based on the algebraic gas system model and the algebraic gas turbine model. Obtain the power operation parameters of the power unit in the electrical integrated energy system, the gas operation parameters of the gas unit in the electrical integrated energy system, and the coupling operation parameters of the coupling unit in the electrical integrated energy system; The gas system model is constructed by using gas pressure and gas mass flow rate from the gas operating parameters as variables, specifically: Where x and t represent spatial and temporal variables, respectively; p and q represent pipe pressure and pipe mass flow rate, respectively; pn and qn represent nodal pressure and nodal mass flow rate, respectively; c is the velocity of sound; S is the pipe cross-sectional area; D is the pipe inner diameter; and λ is the pipe friction coefficient V. g E represents the set of nodes in a gas system. in k E represents the set of pipelines flowing into node k. out k p represents the set of pipes flowing out from node k. i,Nx p represents the outlet pressure of pipe i. n,0 q represents the inlet pressure of pipe n. i,0 q represents the inlet mass flow rate of pipe i. i, Nx This represents the outlet mass flow rate of pipe i; The gas turbine model includes a compressor model, a combustion chamber model, and a steam turbine model, wherein the compressor model is represented as follows: To determine the relationship between the compressor outlet temperature and inlet temperature, T i cp,t and T o cp,t These represent the compressor inlet and outlet temperatures, respectively, in K. cp1 K represents the compressor pressure ratio. cp2 K represents the adiabatic efficiency of the compressor. cp3 This represents the isentropic air coefficient of the compressor; To determine the relationship between the compressor outlet pressure and inlet pressure, p i cp,t and p o cp,t These represent the compressor inlet and outlet pressures, respectively. To determine the power consumption of the compressor, η cp q represents the mechanical efficiency of the compressor. a,t This indicates the mass flow rate of the air entering the compressor; The combustion chamber model is as follows: In the formula, C a and C s q represents the specific heat capacity of air and the mixed flue gas, respectively. g,t To input the gas flow rate into the combustion chamber, T cc,t K represents the combustion chamber outlet temperature. cc1 K is the heat storage coefficient of the combustion chamber. cc2 The lower heating value of the gas; The turbine model is as follows: Among them, T tb,t and p tb,t K represents the temperature and pressure of the steam turbine. tb1 K represents the isentropic natural gas coefficient. tb2 K represents the internal efficiency of the steam turbine. tb3 P represents the overall mechanical efficiency of a gas turbine. tb,t P represents the electrical power generated by the steam turbine. gt,t The effective electrical power output by the gas turbine; The parameter determination module is used to determine the target operating parameters when the operating cost of the target dynamic model is minimized under preset boundary conditions, and to optimize the operation of the integrated electrical energy system based on the target operating parameters.

7. An electronic device, characterized in that, include: The device includes a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory via the bus. When the machine-readable instructions are executed by the processor, they perform the steps of the electrical integrated energy system operation optimization method as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which, when executed by a processor, performs the steps of the electrical integrated energy system operation optimization method as described in any one of claims 1 to 5.

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