Optimal Scheduling Model for Stochastic Electrothermal Coupling System Considering Asymmetric Heat Losses

Abstract

An optimization dispatching model for a random electric-thermal coupling system taking into account asymmetric heat loss, wherein the objective function of the optimization dispatching model takes the minimum total dispatching cost of the optimization dispatching model as the optimization target, and adds the abandoned wind power as a penalty term to the objective function; the constraints of the optimization dispatching model include the constraints of the operation of the power system and the operation of the thermal system: the constraints of the operation of the power system are composed of the constraints of the balance of the power output of the units, the constraints of the operation of the thermal power units, the constraints of the operation of the wind power units, the constraints of the operation of the cogeneration units, and the constraints of the power of the interconnection lines. The constraints of the operation of the thermal system are composed of the constraints of the network nodes and the constraints of the heat network pipelines. The present invention takes into account the asymmetric heat loss process of the heat network pipelines, and gives full play to the dynamic characteristics of heat migration of the thermal system to improve the wind power consumption level and economic benefits of the random electric-thermal coupling system.

Description

Technical Field

[0001] The present invention relates to the technical field of integrated energy system operation control, and in particular to an optimization scheduling model for a random electric-thermal coupling system taking into account asymmetric heat loss. Background Art

[0002] During the winter in the "Three Norths" region, the demand for centralized heating and the demand for wind power consumption overlap, which seriously reduces the grid's ability to absorb renewable energy. From the perspective of physical characteristics, electric energy is relatively easy to transmit but difficult to store, while thermal energy is relatively easy to store but difficult to transmit. There is a natural complementarity between the power system and the thermal system. Integrating the power system and the thermal system for unified dispatch, and fully tapping the coordination and flexibility space between the power network and the thermal network as well as thermal power units, cogeneration units, boilers and other equipment, has become one of the important ways to solve the problem of large-scale renewable energy consumption.

[0003] The dispatching of the electric-thermal coupling system operates on an hourly time scale. The temperature of the heat network pipeline will change continuously with the heat loss. This change is much slower than the electromagnetic transient and electromechanical transient processes of the power system. At this time, the power system can be described by algebraic equations, while the thermal system still needs to take into account the dynamic process of heat migration in the heat network. However, in actual engineering applications, the return water pipe and the water supply pipe of the heat network are embedded in the same insulating casing for laying. At this time, the heat loss of the heat network is not only affected by the environment, but also by the heat loss between the water supply / return pipes. In the dispatching of the electric-thermal coupling system, the release of the flexibility of equipment such as cogeneration units increases the frequency and amplitude of the fluctuation of the inlet temperature of the heat source pipeline, and the non-uniform distribution of the pipeline temperature increases, resulting in an increase in the heat loss of the pipeline supply / return pipe. In fact, heat loss is the main operating cost of the thermal system to support the flexibility of the power grid. Therefore, it is necessary to accurately take into account the influence of heat loss in the dynamic process of heat migration to improve the economic efficiency of the electric-thermal coupling dispatching results in actual engineering applications.

[0004] In addition, wind power uncertainty is also one of the important factors affecting the results of electric-thermal coupling scheduling. Currently, two main solution methods, stochastic optimization and robust optimization, are used to deal with the uncertainty of wind power in the system. However, the probability distribution of wind power in actual engineering applications is inherently uncertain, and it is difficult to guarantee the effectiveness of its stochastic optimization results. Similarly, although robust optimization can be represented by the boundary parameters of its uncertainty, the final results are usually too conservative. Therefore, how to maximize the system's ability to resist fluctuations while ensuring the economic benefits of the system is a technical problem that needs to be urgently solved in the optimization and scheduling of random electric-thermal coupling systems at this stage. Summary of the invention

[0005] In order to further bring into play the comprehensive benefits of the random electrothermal coupling system, the present invention provides an optimization scheduling method for a random electrothermal coupling system taking into account asymmetric heat loss, aiming to make full use of the dynamic process of heat migration in the thermal system to improve the wind power consumption level and economic benefits of the random electrothermal coupling system, and to achieve effective resistance to wind power uncertainty in the power system while ensuring the economy of the random electrothermal coupling system through the information gap robust optimization method.

[0006] The technical solution adopted by the present invention is:

[0007] The method for optimizing the scheduling of a stochastic electrothermal coupling system taking into account asymmetric heat loss includes the following steps:

[0008] Step 1: Based on the heat migration process of the heat network pipeline considering the actual heat loss, a thermal system model taking into account the asymmetric heat loss is established;

[0009] Step 2: Using the thermal system model established in step 1 that takes into account asymmetric heat loss, the influence of wind power uncertainty is considered in the traditional electrothermal coupling system structure, and a random electrothermal coupling system optimization scheduling model is established;

[0010] Step 3: Based on the stochastic electrothermal coupling system optimal dispatch model established in step 2, the information gap robust optimization method is used to model the uncertainty of wind power and solve the model relaxation;

[0011] Through the above steps, the optimal scheduling of the random electrothermal coupling system is achieved.

[0012] The invention provides a random electrothermal coupling system optimization scheduling method taking into account asymmetric heat loss, which has the advantages of:

[0013] Taking the minimum total dispatch cost of the random electrothermal coupling system as the objective function, the constraints of the operation of the power system and the thermal system are established. The heat migration process considering the asymmetric heat loss is taken into account in the constraints of the thermal system operation. At the same time, by using the information gap robust optimization method, the uncertainty of wind power in the power system is modeled, and then the original optimization dispatch model is transformed into the information gap robust optimization dispatch model of the random electrothermal coupling system. By relaxing the model and solving it with commercial software, the optimal result of the optimization dispatch method of the random electrothermal coupling system considering the asymmetric heat loss is obtained.

[0014] The method of the present invention takes into account the asymmetric heat loss process of the heat network pipeline, and gives full play to the dynamic characteristics of heat migration of the thermal system to improve the wind power consumption level and economic benefits of the random electrothermal coupling system. The information gap robust optimization method is used for solution, which can be applied to the current situation of wind power uncertainty in the random electrothermal coupling system, and fully ensure the safety and stability of the system operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a diagram of the actual random electrothermal coupling system in a certain area;

[0016] Figure 2 The actual electric heat load demand and the maximum electric output curve of wind power forecast for a certain area;

[0017] Figure 3 It is the inlet and outlet temperature diagram of the No. 67 water supply pipe of the thermal system;

[0018] Figure 4 It is the inlet and outlet temperature diagram of return pipe No. 67 of the thermal system;

[0019] Figure 5 It is the thermal output dispatch plan diagram of the cogeneration unit;

[0020] Figure 6 It is the power output dispatch plan diagram for cogeneration units, thermal power units and wind turbine units;

[0021] Figure 7 This is the wind curtailment rate diagram of the random electric-thermal coupling system;

[0022] Figure 8 This is a trend chart of the total scheduling cost of the system and its uncertainty radius. DETAILED DESCRIPTION

[0023] The method for optimizing the scheduling of a stochastic electrothermal coupling system taking into account asymmetric heat loss includes the following steps:

[0024] Step 1: Based on the heat migration process of the heat network pipeline considering the actual heat loss, a thermal system model taking into account the asymmetric heat loss is established;

[0025] Step 2: Using the thermal system model established in step 1 that takes into account asymmetric heat loss, the influence of wind power uncertainty is considered in the traditional electrothermal coupling system structure, and a random electrothermal coupling system optimization scheduling model is established;

[0026] Step 3: Based on the stochastic electrothermal coupling system optimal dispatch model established in step 2, the information gap robust optimization method is used to model the uncertainty of wind power and solve the model relaxation;

[0027] Through the above steps, the optimal scheduling of the random electrothermal coupling system is achieved.

[0028] In step 1, the heat migration process of the heat network pipeline is represented by a steady-state temperature model, as shown in formula (1):

[0029]

[0030] In the formula, m and c represent the mass flow rate and specific heat capacity of the hot water in the pipeline respectively; T represents the average temperature of the pipeline in space; q represents the heat loss corresponding to the pipeline length dx.

[0031] In the step 1, during the heat migration process of the heat network pipeline, the actual heat loss includes: a symmetrical heat loss process and an asymmetrical heat loss process;

[0032] The symmetrical heat loss process is caused by the heat exchange between the water supply / return pipe and the external environment through the pipe wall insulation layer. The heat loss calculation of the process is shown in formula (2) and formula (3):

[0033]

[0034]

[0035] In the above formula, v represents the water supply pipe network; r represents the return pipe network; s represents the symmetrical heat loss process; and Respectively represent the symmetrical heat loss of the water supply / return pipe; T v and T r Respectively represent the average temperature of the supply / return pipe; T b Represents the average temperature of the external environment; R s Thermal resistance coefficient representing a symmetric heat loss process.

[0036] The asymmetric heat loss process is caused by the heat transfer from the water supply pipe to the return pipe through the insulation layer inside the pipe. The heat loss calculation of this process is shown in formula (4):

[0037]

[0038] In the formula, q a Represents the asymmetric heat loss of the water supply / return pipe; R a Thermal resistance coefficient representing asymmetric heat loss process;

[0039] The heat migration process of the heat network pipeline after taking into account the asymmetric heat loss is shown in equations (5)-(6):

[0040]

[0041] In the formula, m v represents the mass flow rate of hot water in the water supply pipeline; c represents the specific heat capacity of hot water in the pipeline; T v and T r Respectively represent the average temperature of the water supply / return pipe space; T b Indicates the average temperature of the external environment; Represents the symmetrical heat loss of the water supply pipeline; q aRepresents the asymmetric heat loss of the water supply / return pipe; R s and R a represent the thermal resistance coefficients for symmetric and asymmetric heat loss processes, respectively.

[0042]

[0043] In the formula, m r represents the mass flow rate of hot water in the return pipe; c represents the specific heat capacity of hot water in the pipe; T v and T r Respectively represent the average temperature of the water supply / return pipe space; T b Indicates the average temperature of the external environment; Represents the symmetrical heat loss of the return pipe; q a Represents the asymmetric heat loss of the water supply / return pipe; R s and R a Respectively represent the thermal resistance coefficients of symmetric and asymmetric heat loss processes. r The negative sign means that under the premise that the hot water flow direction in the supply pipe is positive, the negative sign is used to explain the reverse flow in the return pipe.

[0044] The operation and regulation mode of the thermal system model is the mass regulation mode, that is, the mass flow of hot water in the heating network pipeline is not changed, and only its temperature is adjusted. At the same time, the structure of the thermal system network is a general node structure, and the subscripts e and n are used to number the heating network pipelines and network nodes respectively. and They respectively represent the front-side and rear-side heating network pipe sets connected to the network node n.

[0045] In step 1, after taking into account the asymmetric heat loss, the thermal system model includes: a network node part and a heat network pipeline part:

[0046] The network node part represents the mass flow balance and heat balance of pipeline hot water at the network node. Its balance equations include: the heat balance equations of the network node at the cogeneration unit and the user's heat load (7)-(8):

[0047]

[0048] In the formula, represents the heat output of the cogeneration unit g at the network node n at time t; c represents the specific heat capacity of the hot water in the pipeline; It represents the mass flow rate of hot water in pipe g of cogeneration unit at network node n at time t; and They represent the inlet and outlet temperatures of the pipe of the cogeneration unit g at the network node n at time t respectively.

[0049]

[0050] In the formula, represents the heat demand of user heat load d at network node n at time t; c represents the specific heat capacity of pipeline hot water; It represents the mass flow rate of hot water in the pipeline of user heat load d at network node n at time t; and They represent the inlet and outlet temperatures of the user heat load d pipeline at network node n at time t respectively.

[0051] The heat balance equations of the network nodes (9)-(10):

[0052]

[0053] In the formula, e represents the number of the heat network pipeline, and They represent the number sets of the front-side and rear-side heat network pipes connected to the network node n respectively; It represents the mass flow rate of hot water in water supply pipe e at time t; and They represent the mass flow of hot water in the pipeline of the cogeneration unit g and the user heat load d at the network node n at time t respectively; represents the outlet temperature of the water supply pipe e at time t; represents the outlet temperature of the pipe g of the cogeneration unit at the network node n at time t; Represents the temperature of node n in the water supply pipeline network at time t.

[0054]

[0055] In the formula, e represents the number of the heat network pipeline, and They represent the number sets of the front-side and rear-side heat network pipes connected to the network node n respectively; It represents the mass flow rate of hot water in the return pipe e at time t; and They represent the mass flow of hot water in the pipeline of the cogeneration unit g and the user heat load d at the network node n at time t respectively; They represent the outlet temperature of the return pipe e at time t respectively; represents the outlet temperature of the user heat load d pipeline at network node n at time t; Represents the temperature of the return pipe network node n at time t.

[0056] The mass flow balance equations of the network nodes (11)-(12) are:

[0057]

[0058] In the formula, e represents the number of the heat network pipeline, and They represent the number sets of the front-side and rear-side heat network pipes connected to the network node n respectively; and They represent the mass flow of hot water in the pipeline of the cogeneration unit g and the user heat load d at the network node n at time t respectively; Represents the mass flow rate of hot water in water supply pipe e at time t.

[0059]

[0060] In the formula, e represents the number of the heat network pipeline, and They represent the number sets of the front-side and rear-side heat network pipes connected to the network node n respectively; and They represent the mass flow of hot water in the pipeline of the cogeneration unit g and the user heat load d at the network node n at time t respectively; Represents the mass flow rate of hot water in the return pipe e at time t.

[0061] The equilibrium assumptions of the outlet temperature of the front pipe and the inlet temperature of the rear pipe of the network node are as follows:

[0062]

[0063] In the formula, e represents the number of the heat network pipeline, Represents the set of numbers of the back-end heat network pipes connected to the network node n; represents the inlet temperature of the water supply pipe e at time t; represents the inlet temperature of the user heat load d pipeline at the network node n at time t; Represents the temperature of node n in the water supply pipeline network at time t.

[0064]

[0065] In the formula, e represents the number of the heat network pipeline, represents the set of front-side heat network pipe numbers connected to network node n; represents the inlet temperature of the return pipe e at time t; represents the inlet temperature of the pipe g of the cogeneration unit at the network node n at time t; Represents the temperature of the return pipe network node n at time t.

[0066] The heat network pipe part represents the temperature change of the pipes connecting each network node. Taking the water supply pipe as an example, its pipe temperature is not only determined by its own heat migration process, but also affected by the external environment temperature and the return pipe temperature. The return pipe is the same. The relationship between the inlet and outlet temperatures of the water supply / return pipe e is shown in equations (15)-(18):

[0067]

[0068] In the formula, and They represent the inlet temperature of the water supply / return pipe e at time t respectively; represents the outlet temperature of the water supply pipe e at time t; T b Represents the average temperature of the external environment; R s and R a denote the thermal resistance coefficients of symmetric and asymmetric heat loss processes respectively; ξ e,t Represents the heat loss coefficient of the heating network pipeline e at time t.

[0069]

[0070] In the formula, represents the inlet temperature of the water supply pipe e at time t; and Respectively represent the outlet temperature of the water supply / return pipe e at time t; T b Represents the average temperature of the external environment; R s and R a denote the thermal resistance coefficients of symmetric and asymmetric heat loss processes respectively; ξ e,t Represents the heat loss coefficient of the heating network pipeline e at time t.

[0071]

[0072] In the formula, ξ e,t represents the heat loss coefficient of the heat network pipe e at time t; R s and R a represents the thermal resistance coefficient of symmetrical and asymmetrical heat loss processes respectively; c represents the specific heat capacity of hot water in the pipeline; l e Indicates the length of the water supply / return pipe e; m e,t Indicates the mass flow rate of hot water in the supply / return pipe.

[0073]

[0074] In the formula, ξ e,t represents the heat loss coefficient of the heat network pipe e at time t; m e,t Indicates the mass flow rate of hot water in the supply / return pipe e; l erepresents the length of the water supply / return pipe e; R represents the thermal resistance coefficient which has no physical meaning. In the process of actually solving the differential equations (5)-(6) and obtaining their solutions (15)-(16), the steps and difficulty of the calculation process are simplified by setting the thermal resistance coefficient R.

[0075] In step 2, the traditional electric-thermal coupling system structure includes: large-scale wind turbines, thermal power units, cogeneration units, power system line networks, and thermal system pipeline networks. The thermal system model described in step 1 is adopted, and under the above-mentioned traditional electric-thermal coupling system structure, the influence of wind turbines on wind power uncertainty factors is considered, and a random electric-thermal coupling system optimization scheduling model taking into account asymmetric heat loss is established.

[0076] The optimal scheduling model of the random electrothermal coupling system includes the objective function of the optimal scheduling model and the constraints of the optimal scheduling model.

[0077] The objective function of the optimization scheduling model takes the minimum total scheduling cost of the optimization scheduling model as the optimization target, and adds the abandoned wind power into the objective function in the form of a penalty term, as shown in formula (19):

[0078] min F total =F chp +F con +F wind (19);

[0079] In the formula, F total represents the total dispatch cost of the random electric-thermal coupling system; F chp and F con They represent the dispatching costs of the combined heat and power unit and the thermal power unit in the random electric-thermal coupling system; F wind It represents the penalty cost of wind turbine curtailment in random electric-thermal coupling system.

[0080] F chp 、F con and F wind The calculation of is shown in equations (20)-(22):

[0081]

[0082] In the formula, F chp represents the dispatching cost of the cogeneration unit and the thermal power unit in the random electric-thermal coupling system; t represents the current dispatching time; T represents the set of all dispatching times; g represents the number of the cogeneration unit in the random electric-thermal coupling system; ψ chp represents the set of all CHP units; f g,p and f g,q Respectively represent the electricity / heat output cost of the cogeneration unit g; P g,t and Qg,t They respectively represent the electrical / thermal output of the cogeneration unit g at time t.

[0083]

[0084] In the formula, F con represents the dispatching cost of the thermal power unit in the random electrothermal coupling system; t represents the current dispatching time; T represents the set of all dispatching times; k represents the number of the thermal power unit in the random electrothermal coupling system; ψ con represents the set of all thermal power units; f k represents the power output cost of thermal power unit k; P k,t Represents the electrical output of thermal power unit k at time t.

[0085]

[0086] In the formula, F wind represents the penalty cost of wind turbine abandonment in the random electrothermal coupling system; t represents the current scheduling time; T represents the set of all scheduling times; i represents the number of wind turbines in the random electrothermal coupling system; ψ wind represents the set of all wind turbines; δ i P represents the wind abandonment penalty coefficient of wind turbine i; i,t,max represents the actual maximum power output of wind turbine i at time t; P i,t Represents the electrical output of wind turbine i at time t.

[0087] The constraints of the optimal dispatch model include the constraints of the power system operation and the constraints of the thermal system operation.

[0088] 1) The constraints of power system operation are composed of the constraints of unit power output balance, the constraints of thermal power unit operation, the constraints of wind power unit operation, the constraints of cogeneration unit operation and the constraints of interconnection line power.

[0089] The constraint condition of the unit power output balance is shown in formula (23):

[0090]

[0091] Where g, k, i and j represent the numbers of the cogeneration units, thermal power units, wind turbine units and user loads in the random electric-thermal coupling system; ψ chp , con , wind and ψ d represents the set of all cogeneration units, thermal power units, wind power units and user power loads; P g,t represents the electrical output of the cogeneration unit g at time t; P k,trepresents the power output of thermal power unit k at time t; P i,t represents the power output of wind turbine i at time t; P j,t Represents the electricity demand of user load j at time t.

[0092] The constraints of thermal power unit operation are shown in formula (24):

[0093] P k,t,min ≤P k,t ≤P k,t,max (twenty four);

[0094] Where P k,t represents the power output of thermal power unit k at time t; P k,t,min and P k,t,max They represent the minimum and maximum power output of thermal power unit k at time t respectively.

[0095] The constraints of wind turbine operation are shown in formula (25):

[0096] 0≤P i,t ≤P i,t,max (25);

[0097] Where P i,t,max represents the actual maximum power output of wind turbine i at time t; P i,t Represents the electrical output of wind turbine i at time t.

[0098] The constraints for the operation of the cogeneration unit are shown in equations (26)-(28):

[0099] P g,t ≥r g Q g,t (26);

[0100] Where P g,t and Q g,t They represent the electricity / heat output of the cogeneration unit g at time t; r g It represents the electrical / thermal output coupling coefficient of the cogeneration unit g.

[0101] F g,t,min ≤ρ g,p P g,t +ρ g,q Q g,t ≤F g,t,max (27);

[0102] In the formula, F g,t,min and F g,t,max They represent the minimum and maximum fuel intake of the CHP unit g at time t; ρ g,p and ρ g,qRespectively represent the electricity / heat output fuel consumption rate of the cogeneration unit g; P g,t and Q g,t They respectively represent the electrical / thermal output of the cogeneration unit g at time t.

[0103] 0≤Q g,t ≤Q g,t,max (28);

[0104] In the formula, Q g,t represents the thermal output of the cogeneration unit g at time t; Q g,t,max Represents the maximum thermal output of the cogeneration unit g at time t.

[0105] The constraints of the tie line power are shown in equations (29)-(30):

[0106] L l,t,min ≤L l,t ≤L l,t,max (29);

[0107] Where, L l,t represents the power of the tie line l at time t; L l,t,min and L l,t,max They represent the minimum and maximum power of the tie line l at time t respectively.

[0108]

[0109] Where, L l,t represents the power of the tie line l at time t; l, g, k, i and j represent the numbers of the lines, cogeneration units, thermal power units, wind turbine units and user loads in the random electrothermal coupling system; ψ chp , con , wind and ψ d represents the set of all cogeneration units, thermal power units, wind power units and user power loads; G l-g Indicates the power allocation coefficient of the cogeneration unit; G l-i Indicates the power distribution coefficient of the wind turbine; G l-k Indicates the power distribution coefficient of the thermal power unit; G l-j Indicates the power distribution coefficient of the user's electrical load; P g,t represents the electrical output of the cogeneration unit g at time t; P k,t represents the power output of thermal power unit k at time t; P i,t represents the power output of wind turbine i at time t; P j,t Represents the electricity demand of user load j at time t.

[0110] 2): The constraints of the thermal system operation are composed of the constraints of the network nodes and the constraints of the heat network pipelines.

[0111] The constraints of network nodes are shown in equations (31)-(38):

[0112]

[0113] In the formula, represents the heat output of the cogeneration unit g at the network node n at time t; c represents the specific heat capacity of the hot water in the pipeline; It represents the mass flow rate of hot water in pipe g of cogeneration unit at network node n at time t; and They represent the inlet and outlet temperatures of the pipe of the cogeneration unit g at the network node n at time t respectively.

[0114]

[0115] In the formula, represents the heat demand of user heat load d at network node n at time t; c represents the specific heat capacity of pipeline hot water; It represents the mass flow rate of hot water in the pipeline of user heat load d at network node n at time t; and They represent the inlet and outlet temperatures of the user heat load d pipeline at network node n at time t respectively.

[0116]

[0117] In the formula, e represents the number of the heat network pipeline, and They represent the number sets of the front-side and rear-side heat network pipes connected to the network node n respectively; It represents the mass flow rate of hot water in water supply pipe e at time t; and They represent the mass flow of hot water in the pipeline of the cogeneration unit g and the user heat load d at the network node n at time t respectively; represents the outlet temperature of the water supply pipe e at time t; represents the outlet temperature of the pipe g of the cogeneration unit at the network node n at time t; Represents the temperature of node n in the water supply pipeline network at time t.

[0118]

[0119] In the formula, e represents the number of the heat network pipeline, and They represent the number sets of the front-side and rear-side heat network pipes connected to the network node n respectively; It represents the mass flow rate of hot water in the return pipe e at time t; and They represent the mass flow of hot water in the pipeline of the cogeneration unit g and the user heat load d at the network node n at time t respectively; They represent the outlet temperature of the return pipe e at time t respectively; represents the outlet temperature of the user heat load d pipeline at network node n at time t; Represents the temperature of the return pipe network node n at time t.

[0120]

[0121] In the formula, e represents the number of the heat network pipeline, and They represent the number sets of the front-side and rear-side heat network pipes connected to the network node n respectively; and They represent the mass flow of hot water in the pipeline of the cogeneration unit g and the user heat load d at the network node n at time t respectively; Represents the mass flow rate of hot water in water supply pipe e at time t.

[0122]

[0123] In the formula, e represents the number of the heat network pipeline, and They represent the number sets of the front-side and rear-side heat network pipes connected to the network node n respectively; and They represent the mass flow of hot water in the pipeline of the cogeneration unit g and the user heat load d at the network node n at time t respectively; Represents the mass flow rate of hot water in the return pipe e at time t.

[0124]

[0125] In the formula, e represents the number of the heat network pipeline, Represents the set of numbers of the back-end heat network pipes connected to the network node n; represents the inlet temperature of the water supply pipe e at time t; represents the inlet temperature of the user heat load d pipeline at the network node n at time t; Represents the temperature of node n in the water supply pipeline network at time t.

[0126]

[0127] In the formula, e represents the number of the heat network pipeline, represents the set of front-side heat network pipe numbers connected to network node n; represents the inlet temperature of the return pipe e at time t; represents the inlet temperature of the pipe g of the cogeneration unit at the network node n at time t; Represents the temperature of the return pipe network node n at time t.

[0128] The constraints of the heat network pipeline are shown in equations (39)-(42):

[0129]

[0130] In the formula, and They represent the inlet temperature of the water supply / return pipe e at time t respectively; represents the outlet temperature of the water supply pipe e at time t; T b Represents the average temperature of the external environment; R s and R a denote the thermal resistance coefficients of symmetric and asymmetric heat loss processes respectively; ξ e,t Represents the heat loss coefficient of the heating network pipeline e at time t.

[0131]

[0132] In the formula, represents the inlet temperature of the water supply pipe e at time t; and Respectively represent the outlet temperature of the water supply / return pipe e at time t; T b Represents the average temperature of the external environment; R s and R a denote the thermal resistance coefficients of symmetric and asymmetric heat loss processes respectively; ξ e,t Represents the heat loss coefficient of the heating network pipeline e at time t.

[0133]

[0134] In the formula, ξ e,t represents the heat loss coefficient of the heat network pipe e at time t; R s and R a represents the thermal resistance coefficient of symmetrical and asymmetrical heat loss processes respectively; c represents the specific heat capacity of hot water in the pipeline; l e Indicates the length of the water supply / return pipe e; m e,t Indicates the mass flow rate of hot water in the supply / return pipe.

[0135]

[0136] In the formula, ξ e,t represents the heat loss coefficient of the heat network pipe e at time t; m e,t Indicates the mass flow rate of hot water in the supply / return pipe e; l erepresents the length of the water supply / return pipe e; R represents the thermal resistance coefficient which has no physical meaning. In the process of actually solving the differential equations (5)-(6) and obtaining their solutions (15)-(16), the steps and difficulty of the calculation process are simplified by setting the thermal resistance coefficient R.

[0137] In step 3, based on the random electrothermal coupling system optimization scheduling model in step 2, the information gap robust optimization method is used to model the wind power uncertainty in the system, as shown in formula (43):

[0138] U(α,P′ i,t,max )={|P′ i,t ,max-P i,t,max |≤α|P′ i,t,max |} (43);

[0139] In the formula, U(α,P′ i,t,max ) represents the fluctuation range of the actual maximum power output of wind turbine i at time t; α represents the fluctuation amplitude of the actual maximum power output, that is, the uncertainty radius; P′ i,t,max Represents the predicted maximum power output of wind turbine i at time t.

[0140] When the uncertainty of wind power is taken into account in the optimal dispatch model of the random electric-thermal coupling system, it is difficult for the model objective to achieve the optimal result. In order to ensure its optimization effect, it is also necessary to set the expected dispatch cost F of the model. ro , as shown in formula (44):

[0141] F ro =(1+β)F 0 (44);

[0142] In the formula, F 0 It represents the determined dispatching cost, that is, the dispatching cost calculated when the uncertainty of wind power is not considered in the optimization dispatching model (α=0); β represents the dispatching cost deviation coefficient, that is, the deviation between the expected dispatching cost and the determined dispatching cost. The larger the deviation, the greater the system's ability to avoid risks.

[0143] At this time, the optimization goal of the random electrothermal coupling system optimization scheduling model described in step 2 is transformed into seeking the corresponding maximum wind power uncertainty radius when the total scheduling cost is not higher than the expected scheduling cost, and thereby establishing a random electrothermal coupling system information gap robust optimization scheduling model.

[0144] In step 3, the information gap robust optimization scheduling model of the random electrothermal coupling system includes: an upper layer optimization scheduling model and a lower layer optimization scheduling model:

[0145] ①: The upper-level optimization scheduling model includes: the objective function of the upper-level optimization scheduling model and the constraints of the upper-level optimization scheduling model:

[0146] 1) The objective function of the upper-level optimization scheduling model is shown in formula (45):

[0147] maxα (45);

[0148] Where α represents the fluctuation amplitude of the actual maximum power output, that is, the uncertainty radius.

[0149] 2) Constraints of the upper-level optimization scheduling model, as shown in equations (46)-(65):

[0150]

[0151] In the formula, represents the heat output of the cogeneration unit g at the network node n at time t; c represents the specific heat capacity of the hot water in the pipeline; It represents the mass flow rate of hot water in pipe g of cogeneration unit at network node n at time t; and They represent the inlet and outlet temperatures of the pipe of the cogeneration unit g at the network node n at time t respectively.

[0152]

[0153] In the formula, represents the heat demand of user heat load d at network node n at time t; c represents the specific heat capacity of pipeline hot water; It represents the mass flow rate of hot water in the pipeline of user heat load d at network node n at time t; and They represent the inlet and outlet temperatures of the user heat load d pipeline at network node n at time t respectively.

[0154]

[0155] In the formula, e represents the number of the heat network pipeline, and They represent the number sets of the front-side and rear-side heat network pipes connected to the network node n respectively; It represents the mass flow rate of hot water in water supply pipe e at time t; and They represent the mass flow of hot water in the pipeline of the cogeneration unit g and the user heat load d at the network node n at time t respectively; represents the outlet temperature of the water supply pipe e at time t; represents the outlet temperature of the pipe g of the cogeneration unit at the network node n at time t; Represents the temperature of node n in the water supply pipeline network at time t.

[0156]

[0157] In the formula, e represents the number of the heat network pipeline, represents the set of front-side heat network pipe numbers connected to network node n; represents the inlet temperature of the return pipe e at time t; represents the inlet temperature of the pipe g of the cogeneration unit at the network node n at time t; Represents the temperature of the return pipe network node n at time t.

[0158]

[0159] In the formula, e represents the number of the heat network pipeline, and They represent the number sets of the front-side and rear-side heat network pipes connected to the network node n respectively; and They represent the mass flow of hot water in the pipeline of the cogeneration unit g and the user heat load d at the network node n at time t respectively; Represents the mass flow rate of hot water in water supply pipe e at time t.

[0160]

[0161] In the formula, e represents the number of the heat network pipeline, and They represent the number sets of the front-side and rear-side heat network pipes connected to the network node n respectively; and They represent the mass flow of hot water in the pipeline of the cogeneration unit g and the user heat load d at the network node n at time t respectively; Represents the mass flow rate of hot water in the return pipe e at time t.

[0162]

[0163] In the formula, e represents the number of the heat network pipeline, Represents the set of numbers of the back-end heat network pipes connected to the network node n; represents the inlet temperature of the water supply pipe e at time t; represents the inlet temperature of the user heat load d pipeline at the network node n at time t; Represents the temperature of node n in the water supply pipeline network at time t.

[0164]

[0165] In the formula, e represents the number of the heat network pipeline, represents the set of front-side heat network pipe numbers connected to network node n; represents the inlet temperature of the return pipe e at time t; represents the inlet temperature of the pipe g of the cogeneration unit at the network node n at time t; Represents the temperature of the return pipe network node n at time t.

[0166]

[0167] In the formula, and They represent the inlet temperature of the water supply / return pipe e at time t respectively; represents the outlet temperature of the water supply pipe e at time t; T b Represents the average temperature of the external environment; R s and R a denote the thermal resistance coefficients of symmetric and asymmetric heat loss processes respectively; ξ e,t Represents the heat loss coefficient of the heating network pipeline e at time t.

[0168]

[0169] In the formula, represents the inlet temperature of the water supply pipe e at time t; and Respectively represent the outlet temperature of the water supply / return pipe e at time t; T b Represents the average temperature of the external environment; R s and R a denote the thermal resistance coefficients of symmetric and asymmetric heat loss processes respectively; ξ e,t Represents the heat loss coefficient of the heating network pipeline e at time t.

[0170]

[0171] In the formula, ξ e,t represents the heat loss coefficient of the heat network pipe e at time t; R s and R a represents the thermal resistance coefficient of symmetrical and asymmetrical heat loss processes respectively; c represents the specific heat capacity of hot water in the pipeline; l e Indicates the length of the water supply / return pipe e; m e,t Indicates the mass flow rate of hot water in the supply / return pipe.

[0172]

[0173] In the formula, ξ e,t represents the heat loss coefficient of the heat network pipe e at time t; m e,t Indicates the mass flow rate of hot water in the supply / return pipe e; l erepresents the length of the water supply / return pipe e; R represents the thermal resistance coefficient which has no physical meaning. In the process of actually solving the differential equations (5)-(6) and obtaining their solutions (15)-(16), the steps and difficulty of the calculation process are simplified by setting the thermal resistance coefficient R.

[0174]

[0175] Where g, k, i and j represent the numbers of the cogeneration units, thermal power units, wind turbine units and user loads in the random electric-thermal coupling system; ψ chp , con , wind and ψ d represents the set of all cogeneration units, thermal power units, wind power units and user power loads; P g,t represents the electrical output of the cogeneration unit g at time t; P k,t represents the power output of thermal power unit k at time t; P i,t represents the power output of wind turbine i at time t; P j,t Represents the electricity demand of user load j at time t.

[0176] P k,t,min ≤P k,t ≤P k,t,max (59);

[0177] Where P k,t represents the power output of thermal power unit k at time t; P k,t,min and P k,t,max They represent the minimum and maximum power output of thermal power unit k at time t respectively.

[0178] 0≤P i,t ≤P i,t,max (60);

[0179] Where P i,t,max represents the actual maximum power output of wind turbine i at time t; P i,t Represents the electrical output of wind turbine i at time t.

[0180] P g,t ≥r g Q g,t (61);

[0181] Where P g,t and Q g,t They represent the electricity / heat output of the cogeneration unit g at time t; r g It represents the electrical / thermal output coupling coefficient of the cogeneration unit g.

[0182] F g,t,min ≤ρ g,p Pg,t +ρ g,q Q g,t ≤F g,t,max (62);

[0183] In the formula, F g,t,min and F g,t,max They represent the minimum and maximum fuel intake of the CHP unit g at time t; ρ g,p and ρ g,q Respectively represent the electricity / heat output fuel consumption rate of the cogeneration unit g; P g,t and Q g,t They respectively represent the electrical / thermal output of the cogeneration unit g at time t.

[0184] 0≤Q g,t ≤Q g,t,max (63);

[0185] In the formula, Q g,t represents the thermal output of the cogeneration unit g at time t; Q g,t,max Represents the maximum thermal output of the cogeneration unit g at time t.

[0186] L l,t,min ≤L l,t ≤L l,t,max (64);

[0187] Where, L l,t represents the power of the tie line l at time t; L l,t,min and L l,t,max They represent the minimum and maximum power of the tie line l at time t respectively.

[0188]

[0189] Where, L l,t represents the power of the tie line l at time t; l, g, k, i and j represent the numbers of the lines, cogeneration units, thermal power units, wind turbine units and user loads in the random electrothermal coupling system; ψ chp , con , wind and ψ d Represents the set of all cogeneration units, thermal power units, wind power units and user power loads; G l-g Indicates the power allocation coefficient of the cogeneration unit; G l-i Indicates the power distribution coefficient of the wind turbine; G l-k Indicates the power distribution coefficient of the thermal power unit; G l-j Indicates the power distribution coefficient of the user's electrical load; P g,t represents the electrical output of the cogeneration unit g at time t; P k,trepresents the power output of thermal power unit k at time t; P i,t represents the power output of wind turbine i at time t; P j,t Represents the electricity demand of user load j at time t.

[0190] ②: The lower-level optimization scheduling model includes: the objective function of the lower-level optimization scheduling model and the constraints of the lower-level optimization scheduling model.

[0191] 1) The objective function of the lower-level optimization scheduling model is shown in formula (66):

[0192] max F total ≤F ro (66)

[0193] In the formula, F ro represents the expected scheduling cost of the decision maker; F total Represents the total dispatch cost of the information gap optimization dispatch model for random electric-thermal coupling system.

[0194] 2) The constraints of the lower-level optimization scheduling model are shown in formula (67):

[0195] U(α,P′ i,t,max )={|P′ i,t ,max-P i,t,max |≤α|P′ i,t,max |} (67)

[0196] In the formula, U(α,P′ i,t,max ) represents the fluctuation range of the actual maximum power output of wind turbine i at time t; α represents the fluctuation amplitude of the actual maximum power output, that is, the uncertainty radius; P′ i,t,max Represents the predicted maximum power output of wind turbine i at time t.

[0197] In view of the fact that the above-mentioned information gap robust optimization scheduling model for random electrothermal coupling system has the characteristics of double-layer optimization, it is necessary to reasonably relax the original optimization scheduling model before solving the model, and replace the lower-layer optimization scheduling model with its KKT condition, as shown in Equations (68)-(73):

[0198] -μ 1 +μ 2 =δ i (68);

[0199] In the formula, μ 1 and μ 2 They represent the complementary relaxation coefficients of the KKT conditions; δ i It represents the wind abandonment penalty coefficient of wind turbine i.

[0200] μ 1 ((1-α)P′i,t,max -P i,t,max )=0(69);

[0201] In the formula, μ 1 represents the complementary relaxation coefficient of KKT condition; P i, ' t,max P represents the predicted maximum power output of wind turbine i at time t; i,t,max represents the actual maximum power output of wind turbine i at time t; α represents the fluctuation amplitude of the actual maximum power output, that is, the uncertainty radius.

[0202] μ 2 ((1+α)P′ i,t,max -P i,t,max )=0(70);

[0203] In the formula, μ 2 represents the complementary relaxation coefficient of the KKT condition; P′ i,t,max P represents the predicted maximum power output of wind turbine i at time t; i,t,max represents the actual maximum power output of wind turbine i at time t; α represents the fluctuation amplitude of the actual maximum power output, that is, the uncertainty radius.

[0204] μ 1 ≥0 (71);

[0205] In the formula, μ 1 represents the complementary relaxation coefficient of the KKT condition.

[0206] μ 2 ≥0 (72);

[0207] In the formula, μ 2 represents the complementary relaxation coefficient of the KKT condition.

[0208] (1-α)P′ i,t,max ≤P i,t,max ≤(1+α)P′ i,t,max (73);

[0209] P′ i,t,max P represents the predicted maximum power output of wind turbine i at time t; i,t,max represents the actual maximum power output of wind turbine i at time t; α represents the fluctuation amplitude of the actual maximum power output, that is, the uncertainty radius.

[0210] For the information gap robust optimization scheduling model of the relaxed random electrothermal coupling system, the solving tool CPLEX can be called in the commercial software Matlab to solve the model.

[0211] Example:

[0212] The actual random electrothermal coupling system model of a certain region is adopted. The model structure diagram is shown in Figure 1 , the system electric heat load demand and wind power forecast maximum power output are detailed in Figure 2 , the other parameters are as follows:

[0213] 1. Power system parameters:

[0214] In this embodiment, the power system line network parameters are all taken from the IEEE standard 39-node model parameters, the electric output cost of the cogeneration unit is 0.2 (kW) * h, the thermal output cost of the cogeneration unit is 0.3 (kW) * h, the electric output cost of the thermal power unit is 0.4 (kW) * h, the wind power cost penalty coefficient is 0.7 (kW) * h, the minimum electric output of the thermal power unit is 0MW, the maximum electric output of the thermal power unit is 100MW, the electric-thermal coupling system of the cogeneration unit is 0.6, the maximum fuel intake of the cogeneration unit is 365kg, the minimum fuel intake of the cogeneration unit is 200kg, the electric output fuel consumption rate of the cogeneration unit is 1.2kg / MW, the thermal output fuel consumption rate of the cogeneration unit is 0.8kg / MW, and the maximum thermal output of the cogeneration unit is 240MW.

[0215] 2. Thermal system parameters:

[0216] In this embodiment, the pipe network parameters of the thermal system are all taken from the actual parameters of a certain area.

[0217] Finally, a corresponding mathematical simulation model was established in the commercial software Matlab. Through simulation verification, the effectiveness of taking into account the asymmetric heat loss in the random electrothermal coupling system to improve its comprehensive benefits and the rationality and advantages of using the information gap robust optimization method in dealing with wind power uncertainty problems were verified.

[0218] Figure 3-Figure 7 The figure shows the simulation results that verify the effectiveness of considering asymmetric heat loss in improving the comprehensive benefits of the random electrothermal coupling system. Two operating conditions are set during the simulation: Condition 1, the optimal scheduling of the random electrothermal coupling system considering only symmetric heat loss, the thermal resistance coefficient of the symmetric heat loss process is 3.448 (mK) / W; Condition 2, the optimal scheduling of the random electrothermal coupling system considering asymmetric heat loss, the thermal resistance coefficient of the symmetric heat loss process is 3.992 (mK) / W, and the thermal resistance coefficient of the asymmetric heat loss process is 12.605 (mK) / W.

[0219] observe Figure 3 and Figure 4The inlet and outlet temperatures of the No. 67 water supply / return pipe are shown. According to the data shown, it can be calculated that the average heat loss of the water supply / return pipe is 0.6836MW and 0.5741MW when operating under condition 1, and the average heat loss of the water supply / return pipe is 0.6217MW and 0.4710MW when operating under condition 2. Comparing condition 1 with condition 2, it can be seen that the heat loss of the water supply / return pipe in condition 2 has decreased year-on-year. Among them, the average reduction in heat loss of the water supply pipe accounts for about 8.57% of the original heat loss, while the average reduction in heat loss of the return pipe is much greater than that of the water supply pipe, accounting for about 19.31% of the original heat loss. The reason is that after taking into account the asymmetric heat loss process of the heat network pipe, part of the heat loss originally caused by the heat exchange between the water supply pipe and the external environment will be supplemented to the return pipe in the form of heat transfer through the pipe insulation layer with greater thermal resistance. Based on this, not only the heat loss of the water supply pipe is reduced due to the increase of thermal resistance of its loss process, but also the heat loss of the return pipe is further reduced due to the heat supplement from the water supply pipe.

[0220] observe Figure 5 and Figure 6 The thermal / electric output dispatch plan of the unit shown in the figure shows that the thermal output change trend of the cogeneration unit is basically the same when comparing working conditions 1 and 2. However, in working condition 2, with the overall rise in the temperature of the heat network pipeline, the thermal output of the unit will be constrained by the heat balance equation of the network node, and will decrease by 11.23MW year-on-year (the reduction accounts for about 4.89% of the original thermal output). Similarly, with the reduction of the thermal output of the cogeneration unit, during the low heat load period (9-15 o'clock), the electrical output cost of the cogeneration unit is lower than that of the thermal power unit. When the wind turbine unit is fully powered, the output of the cogeneration unit increases and the output of the thermal power unit decreases, making the dispatch more economical during the 9-15 period.

[0221] observe Figure 7 The wind curtailment rate is shown in Figure 1. By comparing working condition 1 with working condition 2, it can be seen that during the peak period (0-6 o'clock) when the wind power is predicted to have the maximum power output, as the thermal output of the cogeneration unit decreases, its power output will be adjusted under the constraints of the electric-thermal coupling relationship of the cogeneration unit, so that wind power has a larger grid connection space. The wind curtailment rate situation diagram more intuitively shows that the wind curtailment situation in working condition 2 is significantly better than that in working condition 1, and the reduced wind curtailment rate can reach up to 9.13%. The system wind power consumption will be effectively alleviated, and the economic efficiency of dispatching in this period will be further improved.

[0222] The simulation results of the two operating conditions show that when operating under operating condition 1, the total system cost is 266.7704747 million yuan, the electricity cost of the cogeneration unit is 77.6416273 million yuan, the thermal cost of cogeneration is 150.4988149 million yuan, the cost of the thermal power unit is 28.4183713 million yuan, and the cost of wind power abandonment is 10.2116612 million yuan; when operating under operating condition 2, the total system cost is 252.5551305 million yuan, the electricity cost of the cogeneration unit is 79.3413844 million yuan, the thermal cost of cogeneration is 142.2849972 million yuan, the cost of the thermal power unit is 23.4552688 million yuan, and the cost of wind power abandonment is 7.4734801 million yuan. Comparing Condition 1 with Condition 2, it can be seen that after taking into account the asymmetric loss process of the heat network in Condition 2, the thermal output of the cogeneration unit decreases; due to the reduction in wind abandonment, the wind power output increases, and the system electrical load required by the cogeneration unit and the thermal power unit is reduced; at the same time, during the low heat load period, the cogeneration unit with a lower cost will share part of the thermal power unit's electrical output. Under the combined influence of these three situations, the electricity cost of the cogeneration unit in Condition 2 increases, while the total system cost, the thermal cost of the cogeneration unit, the cost of the thermal power unit, and the wind power abandonment cost are all reduced relative to Condition 1.

[0223] Figure 8 The figure shows the simulation results that verify the rationality of using the information gap robust optimization method to deal with wind power uncertainty problems. Figure 8 The trend of the dispatching cost and uncertainty radius shown in the figure shows that in the information gap robust optimization method, as the cost deviation coefficient set by the decision maker increases, the uncertainty radius increases and the dispatching cost increases. This is because in the information gap robust optimization, the decision maker believes that uncertainty will have a negative impact on the reduction of dispatching costs. The larger the uncertainty radius, the smaller the risk brought by the uncertainty of the actual maximum power output of wind power, so the dispatching cost is smaller, and the output is in [(1-α)P′ i,t,max ,(1+α)P′ i,t,max ] changes within the range, the scheduling cost can be guaranteed to be lower than the decision maker's expected scheduling cost.

[0224] At the same time, in order to verify the advantages of using the information gap robust optimization method in dealing with wind power uncertainty problems, two operating conditions are set in the simulation: Condition 3, the traditional min-max (maximum and minimum extreme scenarios) robust optimization method is used to solve the random electrothermal coupling system optimization scheduling model; Condition 4, the information gap robust optimization method is used to solve the random electrothermal coupling system optimization scheduling model. The current uncertainty radius is set to 0.012, 0.035 and 0.057. The simulation results of the two working conditions show that when the operating condition 3 is running, the dispatching cost corresponding to the uncertainty radius of 0.012 is 256.2127417 million yuan, the dispatching cost corresponding to the uncertainty radius of 0.035 is 263.2423923 million yuan, and the dispatching cost corresponding to the uncertainty radius of 0.057 is 270.0066608 million yuan; when the operating condition 4 is running, the dispatching cost corresponding to the uncertainty radius of 0.012 is 252.8076856 million yuan, the dispatching cost corresponding to the uncertainty radius of 0.035 is 253.3127959 million yuan, and the dispatching cost corresponding to the uncertainty radius of 0.057 is 253.8179062 million yuan. Comparing working conditions 3 and 4, it can be seen that when the wind power uncertainty radius of the information gap robust optimization method is much larger than that of the traditional robust optimization method, the dispatching cost results obtained by optimization are not much different. Obviously, the information gap robust optimization method is more adaptable to the wind power uncertainty in the random electrothermal coupling system than the traditional robust optimization method. Similarly, when the wind power uncertainty radius of the information gap robust optimization method is equal to that of the traditional robust optimization method, the cost obtained by the information gap robust optimization method will be much smaller than that of the traditional robust optimization method, which can once again prove the economic advantage of the information gap robust optimization method over the traditional robust optimization method.

Claims

1. Optimal scheduling model of stochastic electrothermal coupling system considering asymmetric heat loss, Features: The objective function of the optimization scheduling model takes the minimum total scheduling cost of the optimization scheduling model as the optimization target, and adds the abandoned wind power into the objective function in the form of a penalty term, as shown in formula (19): min F total =F chp +F con +F wind (19); In the formula, F total represents the total dispatch cost of the random electric-thermal coupling system; F chp and F con They represent the dispatching costs of the combined heat and power unit and the thermal power unit in the random electric-thermal coupling system; F wind represents the wind curtailment penalty cost of wind turbines in the random electric-thermal coupling system; F chp 、F con and F wind The calculation of is shown in equations (20)-(22): In the formula, F chp represents the dispatching cost of the cogeneration unit and the thermal power unit in the random electric-thermal coupling system; t represents the current dispatching time; T represents the set of all dispatching times; g represents the number of the cogeneration unit in the random electric-thermal coupling system; ψ chp represents the set of all CHP units; f g,p and f g,q Respectively represent the electricity / heat output cost of the cogeneration unit g; P g,t and Q g,t They represent the electricity / heat output of the cogeneration unit g at time t respectively; In the formula, F con represents the dispatching cost of the thermal power unit in the random electrothermal coupling system; t represents the current dispatching time; T represents the set of all dispatching times; k represents the number of the thermal power unit in the random electrothermal coupling system; ψ con represents the set of all thermal power units; f k represents the power output cost of thermal power unit k; P k,t represents the power output of thermal power unit k at time t; In the formula, F wind represents the penalty cost of wind turbine abandonment in the random electrothermal coupling system; t represents the current scheduling time; T represents the set of all scheduling times; i represents the number of wind turbines in the random electrothermal coupling system; ψ wind represents the set of all wind turbines; δ i P represents the wind abandonment penalty coefficient of wind turbine i; i,t,max represents the actual maximum power output of wind turbine i at time t; P i,t Represents the electrical output of wind turbine i at time t.

2. According to the stochastic electrothermal coupling system optimization scheduling model taking into account asymmetric heat loss according to claim 1, Features: The constraints of the optimal dispatch model include the constraints of the power system operation and the constraints of the thermal system operation: 1) The constraints of power system operation are composed of the constraints of unit power output balance, the constraints of thermal power unit operation, the constraints of wind power unit operation, the constraints of cogeneration unit operation and the constraints of interconnection line power. The constraint condition of the unit power output balance is shown in formula (23): Where g, k, i and j represent the numbers of the cogeneration units, thermal power units, wind turbine units and user loads in the random electric-thermal coupling system; ψ chp , con , wind and ψ d represents the set of all cogeneration units, thermal power units, wind power units and user power loads; P g,t represents the electrical output of the cogeneration unit g at time t; P k,t represents the power output of thermal power unit k at time t; P i,t represents the power output of wind turbine i at time t; P j,t represents the electricity demand of user load j at time t; The constraints of thermal power unit operation are shown in formula (24): P k,t,min ≤P k,t ≤P k,t,max (24); Where P k,t represents the power output of thermal power unit k at time t; P k,t,min and P k,t,max They represent the minimum and maximum power output of thermal power unit k at time t respectively; The constraints of wind turbine operation are shown in formula (25): 0≤P i,t ≤P i,t,max (25); Where P i,t,max represents the actual maximum power output of wind turbine i at time t; P i,t represents the electrical output of wind turbine i at time t; The constraints for the operation of the cogeneration unit are shown in equations (26)-(28): P g,t ≥r g Q g,t (26); Where P g,t and Q g,t They represent the electricity / heat output of the cogeneration unit g at time t; r g represents the electrical / thermal output coupling coefficient of the cogeneration unit g; F g,t,min ≤ρ g,p P g,t +ρ g,q Q g,t ≤F g,t,max (27); In the formula, F g,t,min and F g,t,max They represent the minimum and maximum fuel intake of the CHP unit g at time t; ρ g,p and ρ g,q Respectively represent the electricity / heat output fuel consumption rate of the cogeneration unit g; P g,t and Q g,t They represent the electricity / heat output of the cogeneration unit g at time t respectively; 0≤Q g,t ≤Q g,t,max (28); In the formula, Q g,t represents the thermal output of the cogeneration unit g at time t; Q g,t,max represents the maximum thermal output of the cogeneration unit g at time t; The constraints of the tie line power are shown in equations (29)-(30): L l,t,min ≤L l,t ≤L l,t,max (29); Where, L l,t represents the power of the tie line l at time t; L l,t,min and L l,t,max They represent the minimum and maximum power of the tie line l at time t respectively; Where, L l,t represents the power of the tie line l at time t; l, g, k, i and j represent the numbers of the lines, cogeneration units, thermal power units, wind turbine units and user loads in the random electrothermal coupling system; ψ chp , con , wind and ψ d represents the set of all cogeneration units, thermal power units, wind power units and user power loads; G l-g Indicates the power allocation coefficient of the cogeneration unit; G l-i Indicates the power distribution coefficient of the wind turbine; G l-k Indicates the power distribution coefficient of the thermal power unit; G l-j Indicates the power distribution coefficient of the user's electrical load; P g,t represents the electrical output of the cogeneration unit g at time t; P k,t represents the power output of thermal power unit k at time t; P i,t represents the power output of wind turbine i at time t; P j,t represents the electricity demand of user load j at time t; 2): The constraints of the thermal system operation are composed of the constraints of the network nodes and the constraints of the heat network pipelines; the constraints of the network nodes are shown in equations (31)-(38): In the formula, represents the heat output of the cogeneration unit g at the network node n at time t; c represents the specific heat capacity of the hot water in the pipeline; It represents the mass flow rate of hot water in pipe g of cogeneration unit at network node n at time t; and They represent the inlet and outlet temperatures of the pipe g of the cogeneration unit at the network node n at time t respectively; In the formula, represents the heat demand of user heat load d at network node n at time t; c represents the specific heat capacity of pipeline hot water; It represents the mass flow rate of hot water in the pipeline of user heat load d at network node n at time t; and They represent the inlet and outlet temperatures of the user heat load d pipeline at the network node n at time t respectively; In the formula, e represents the number of the heat network pipeline, and They represent the number sets of the front-side and rear-side heat network pipes connected to the network node n respectively; It represents the mass flow rate of hot water in water supply pipe e at time t; and They represent the mass flow of hot water in the pipeline of the cogeneration unit g and the user heat load d at the network node n at time t respectively; represents the outlet temperature of the water supply pipe e at time t; represents the outlet temperature of the pipe g of the cogeneration unit at the network node n at time t; represents the temperature of node n in the water supply pipeline network at time t; In the formula, e represents the number of the heat network pipeline, and They represent the number sets of the front-side and rear-side heat network pipes connected to the network node n respectively; It represents the mass flow rate of hot water in the return pipe e at time t; and They represent the mass flow of hot water in the pipeline of the cogeneration unit g and the user heat load d at the network node n at time t respectively; They represent the outlet temperature of the return pipe e at time t respectively; represents the outlet temperature of the user heat load d pipeline at network node n at time t; represents the temperature of the return pipe network node n at time t; In the formula, e represents the number of the heat network pipeline, and They represent the number sets of the front-side and rear-side heat network pipes connected to the network node n respectively; and They represent the mass flow of hot water in the pipeline of the cogeneration unit g and the user heat load d at the network node n at time t respectively; It represents the mass flow rate of hot water in water supply pipe e at time t; In the formula, e represents the number of the heat network pipeline, and They represent the number sets of the front-side and rear-side heat network pipes connected to the network node n respectively; and They represent the mass flow of hot water in the pipeline of the cogeneration unit g and the user heat load d at the network node n at time t respectively; It represents the mass flow rate of hot water in the return pipe e at time t; In the formula, e represents the number of the heat network pipeline, Represents the set of numbers of the back-end heat network pipes connected to the network node n; represents the inlet temperature of the water supply pipe e at time t; represents the inlet temperature of the user heat load d pipeline at the network node n at time t; represents the temperature of node n in the water supply pipeline network at time t; In the formula, e represents the number of the heat network pipeline, represents the set of front-side heat network pipe numbers connected to network node n; represents the inlet temperature of the return pipe e at time t; represents the inlet temperature of the pipe g of the cogeneration unit at the network node n at time t; represents the temperature of the return pipe network node n at time t; The constraints of the heat network pipeline are shown in equations (39)-(42): In the formula, and They represent the inlet temperature of the water supply / return pipe e at time t respectively; represents the outlet temperature of the water supply pipe e at time t; T b Represents the average temperature of the external environment; R s and R a denote the thermal resistance coefficients of symmetric and asymmetric heat loss processes respectively; ξ e,t It represents the heat loss coefficient of the heat network pipe e at time t; In the formula, represents the inlet temperature of the water supply pipe e at time t; and Respectively represent the outlet temperature of the water supply / return pipe e at time t; T b Represents the average temperature of the external environment; R s and R a denote the thermal resistance coefficients of symmetric and asymmetric heat loss processes respectively; ξ e,t It represents the heat loss coefficient of the heat network pipe e at time t; In the formula, ξ e,t represents the heat loss coefficient of the heat network pipe e at time t; R s and R a represents the thermal resistance coefficient of symmetrical and asymmetrical heat loss processes respectively; c represents the specific heat capacity of hot water in the pipeline; l e Indicates the length of the water supply / return pipe e; m e,t Indicates the mass flow rate of hot water in the supply / return pipe e; In the formula, ξ e,t represents the heat loss coefficient of the heat network pipe e at time t; m e,t Indicates the mass flow rate of hot water in the supply / return pipe e; l e Indicates the length of the supply / return pipe e.

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