Operation control method and device of integrated energy microgrid group based on cooperative game

Abstract

The invention provides an operation control method and device for a comprehensive energy micro-grid group based on a cooperative game, and the method comprises the steps: constructing an optimized operation model according to the constitution factors of the operation cost in the comprehensive energy micro-grid group, and determining the minimum operation cost and maximum benefit of the comprehensive energy micro-grid group through optimization; constructing a multi-microgrid asymmetric Nash bargaining model based on a cooperative game, and converting the multi-microgrid asymmetric Nash bargaining model into an alliance income model and an alliance income distribution model through equivalent transformation; obtaining optimal microgrid interaction energy according to an alternating direction multiplier method and an alliance income model; and obtaining optimal payment according to the optimal microgrid interaction energy, an alternating direction multiplier method and an alliance income distribution model. According to the method and the device, through establishing the optimized operation model of the integrated energy micro-grid group and the multi-micro-grid asymmetric Nash bargaining model based on the cooperative game, the total operation cost of the multiple integrated energy micro-grids and the operation cost of each integrated energy micro-grid are reduced, and mutual energy aid between the integrated energy micro-grids is effectively stimulated.

Description

Technical Field

[0001] The present application relates to the technical field of integrated energy microgrids, and particularly to an operation control method and device for an integrated energy microgrid group based on cooperative game. Background Art

[0002] With the continuous development of the economic society, problems such as energy shortage and environmental pollution caused by the consumption of global fossil energy are becoming increasingly severe. The integrated energy microgrid with new energy as the main power supply, as an important part of the new power system, not only alleviates the dependence on fossil energy, but also improves the local consumption level of new energy. It is an important measure to promote the adjustment of the energy structure and achieve the "dual carbon" goal; therefore, it is necessary to conduct research on the optimal operation problem of the integrated energy microgrid and the collaborative optimal operation problem of the integrated energy microgrid group to reduce the comprehensive operation cost of the integrated energy microgrid group and ensure the effectiveness of the operation strategy. Summary of the Invention

[0003] The technical objective to be achieved by the embodiments of the present application is to provide an operation control method and device for an integrated energy microgrid group based on cooperative game, so as to solve the problems that the current comprehensive operation cost of multiple integrated energy microgrid groups cannot be effectively reduced and the benefits cannot be reasonably distributed.

[0004] To solve the above technical problems, the embodiments of the present application provide an operation control method for an integrated energy microgrid group based on cooperative game, including:

[0005] According to the factors constituting the operation cost of the integrated energy microgrid group, an optimal operation model is constructed. Based on the optimal operation model, the minimum operation cost of the integrated energy microgrid group is determined through optimization, and then the maximum benefit is determined;

[0006] A multi-microgrid asymmetric Nash bargaining model based on cooperative game for the integrated energy microgrid group is constructed. Through equivalent transformation, the multi-microgrid asymmetric Nash bargaining model is transformed into a coalition benefit model and an in-coalition benefit distribution model. The multi-microgrid asymmetric Nash bargaining model satisfies that the product of the increased benefits after cooperation within each integrated energy microgrid group is the largest, and the sum of the benefits after cooperation within each integrated energy microgrid group is equal to the maximum benefit;

[0007] According to the alternating direction method of multipliers and the coalition benefit model, the optimal microgrid interaction energy of each integrated energy microgrid is obtained;

[0008] According to the optimal microgrid interaction energy of each integrated energy microgrid, the alternating direction method of multipliers, and the in-coalition benefit distribution model, the optimal payment of each integrated energy microgrid is obtained.

[0009] In some embodiments, the coalition benefit model satisfies that the product of the benefits after cooperation within each integrated energy microgrid group is the largest;

[0010] The revenue distribution model within the alliance satisfies being maximized; where N represents the number of integrated energy microgrids; Z n represents the payment that the nth integrated energy microgrid group needs to give to other integrated energy microgrids after cooperation, and c n represents the revenue of the nth integrated energy microgrid group after cooperation; represents the revenue when the nth integrated energy microgrid operates independently.

[0011] In some embodiments, after obtaining the optimal microgrid interaction energy of each integrated energy microgrid, it further includes:

[0012] Determining the energy contribution degree corresponding to each integrated energy microgrid according to the optimal microgrid interaction energy;

[0013] Based on the energy contribution degree corresponding to each integrated energy microgrid, correcting the revenue distribution model within the alliance to obtain a revenue distribution model within the alliance based on the energy contribution degree.

[0014] In some embodiments, the obtaining of the optimal microgrid interaction energy of each integrated energy microgrid according to the alternating direction multiplier method and the alliance revenue model includes:

[0015] Constructing a first augmented Lagrangian function according to the first objective function in the alliance revenue model as:

[0016]

[0017] Where represents the first augmented Lagrangian value; T represents the number of time periods in the time period set; z represents the energy types of interaction between each integrated energy microgrid; represents the first Lagrange multiplier at time period t; represents the z energy that the integrated energy microgrid n expects to interact with the integrated energy microgrid m at time period t; represents the z energy that the integrated energy microgrid m expects to interact with the integrated energy microgrid n at time period t;

[0018] Obtaining the optimal microgrid interaction energy of each integrated energy microgrid according to the alternating direction multiplier method and the first augmented Lagrangian function.

[0019] In some embodiments, the obtaining of the optimal microgrid interaction energy of each integrated energy microgrid according to the alternating direction multiplier method and the first augmented Lagrangian function includes:

[0020] Initialize the first augmented Lagrangian function to obtain the initialized first iteration count, the first Lagrange multiplier, and the microgrid interaction energy corresponding to each integrated energy microgrid, and determine the first primal residual threshold and the first dual residual threshold;

[0021] Substitute the current microgrid interaction energy into the current first augmented Lagrangian function to obtain the new microgrid interaction energy corresponding to each integrated energy microgrid;

[0022] Determine the first primal residual and the first dual residual between the currently obtained microgrid interaction energy and the microgrid interaction energy obtained in the previous iteration;

[0023] Judge whether the obtained first primal residual is not greater than the first primal residual threshold and the first dual residual is not greater than the first dual residual threshold;

[0024] If so, determine the current microgrid interaction energy as the optimal microgrid interaction energy;

[0025] If not, increase the first iteration count by 1, update the first Lagrange multiplier according to the current microgrid interaction energy and the first iteration count, and return to execute the step of substituting the current microgrid interaction energy into the current first augmented Lagrangian function to obtain the new microgrid interaction energy corresponding to each integrated energy microgrid.

[0026] In some embodiments, the obtaining of the optimal payment for each integrated energy microgrid according to the optimal microgrid interaction energy of each integrated energy microgrid, the alternating direction multiplier method, and the intra-alliance revenue distribution model includes:

[0027] Construct a second augmented Lagrangian function according to the second objective function in the intra-alliance revenue distribution model based on the energy contribution degree as:

[0028]

[0029] where, represents the second augmented Lagrangian value; a n represents the energy contribution degree of integrated energy microgrid n; Ψ n represents the second Lagrange multiplier; Z m represents the payment that the m-th integrated energy microgrid group needs to give to other integrated energy microgrids after cooperation; γ n represents the penalty factor;

[0030] Obtain the optimal payment for each integrated energy microgrid according to the alternating direction multiplier method and the second augmented Lagrangian function.

[0031] In some embodiments, the obtaining of the optimal payment for each integrated energy microgrid according to the alternating direction multiplier method and the second augmented Lagrangian function includes:

[0032] Initialize the second augmented Lagrangian function to obtain the initialized second iteration count, the second Lagrange multiplier, and the payments of each integrated energy microgrid, and determine the second primal residual threshold, the second dual residual threshold, and the penalty factor;

[0033] Substitute the current payments of each integrated energy microgrid into the current second augmented Lagrangian function to obtain the new payments of each integrated energy microgrid;

[0034] Determine the second primal residual and the second dual residual between the currently obtained payments and the payments obtained in the previous adjacent iteration;

[0035] Judge whether the obtained second primal residual is not greater than the second primal residual threshold and the second dual residual is not greater than the second dual residual threshold;

[0036] If so, determine the current payment as the optimal payment;

[0037] If not, increase the second iteration count by 1, update the second Lagrange multiplier according to the current payment and the second iteration count, and return to execute the step of substituting the current payments of each integrated energy microgrid into the current second augmented Lagrangian function to obtain the new payments of each integrated energy microgrid.

[0038] Another embodiment of the present application further provides an operation control device for an integrated energy microgrid group based on cooperative game, including:

[0039] A first optimization module for constructing an optimal operation model according to the operation cost composition factors of the integrated energy microgrid group, and based on the optimal operation model, determining the minimum operation cost of the integrated energy microgrid group through optimization, and further determining the maximum revenue;

[0040] A model construction module for constructing a multi-microgrid asymmetric Nash bargaining model of the integrated energy microgrid group based on cooperative game, and through equivalent transformation, transforming the multi-microgrid asymmetric Nash bargaining model into an alliance revenue model and an in-alliance revenue distribution model, where the multi-microgrid asymmetric Nash bargaining model satisfies that the product of the increased revenues after cooperation within each integrated energy microgrid group is the largest, and the sum of the revenues after cooperation within each integrated energy microgrid group is equal to the maximum revenue;

[0041] A second optimization module for obtaining the optimal microgrid interaction energy of each integrated energy microgrid according to the alternating direction method of multipliers and the alliance revenue model;

[0042] A third optimization module for obtaining the optimal payment of each integrated energy microgrid according to the optimal microgrid interaction energy of each integrated energy microgrid, the alternating direction method of multipliers, and the in-alliance revenue distribution model.

[0043] Another embodiment of the present application further provides a server, including a processor, a memory, and a computer program stored on the memory and executable on the processor. When the computer program is executed by the processor, the steps of the operation control method of the integrated energy microgrid group based on cooperative game as described above are implemented.

[0044] Another embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the operation control method of the integrated energy microgrid group based on cooperative game as described above are implemented.

[0045] Compared with the prior art, the operation control method and device of the integrated energy microgrid group based on cooperative game provided by the embodiments of the present application have at least the following beneficial effects:

[0046] Aiming at the optimal operation problem of the integrated energy microgrid group, on the basis of considering various operation cost components, with the goal of the optimal economic operation of the integrated energy microgrid group, an optimal operation model of the integrated energy microgrid group is established. Finally, based on the multi-microgrid asymmetric Nash bargaining model of cooperative game, the optimal microgrid interaction energy and optimal payment of each integrated energy microgrid are obtained, thereby reducing the total operation cost of the integrated energy microgrid group and the operation cost of each integrated energy microgrid, and solving the problem of unfair distribution in the traditional Nash bargaining model, effectively stimulating the energy mutual assistance among integrated energy microgrids. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 is a schematic structural diagram of a wind power generation system;

[0048] Figure 2 is a schematic structural diagram of a photovoltaic power generation system;

[0049] Figure 3 is a schematic structural diagram of a combined heat and power system;

[0050] Figure 4 is one of the schematic flowcharts of the control method in the present application;

[0051] Figure 5 is another schematic flowchart of the control method in the present application;

[0052] Figure 6 is a third schematic flowchart of the control method in the present application;

[0053] Figure 7 is a fourth schematic flowchart of the control method in the present application;

[0054] Figure 8 is a fifth schematic flowchart of the control method in the present application;

[0055] Figure 9 This is a schematic structural diagram of the control device in the present application. Detailed implementation manners

[0056] To make the technical problems, technical solutions and advantages to be solved by the present application clearer, the following will be described in detail with reference to the accompanying drawings and specific embodiments. In the following description, specific details such as specific configurations and components are provided only to help a comprehensive understanding of the embodiments of the present application. Therefore, those skilled in the art should clearly understand that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present application. In addition, descriptions of known functions and structures are omitted for clarity and conciseness.

[0057] It should be understood that the "one embodiment" or "an embodiment" mentioned throughout the specification means that a specific feature, structure or characteristic related to the embodiment is included in at least one embodiment of the present application. Therefore, the "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner.

[0058] In various embodiments of the present application, it should be understood that the magnitudes of the serial numbers of the following processes do not mean the order of execution is prior or posterior, and the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0059] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this article generally represents an "or" relationship between the front and rear associated objects.

[0060] In the embodiments provided by the present application, it should be understood that "B corresponding to A" means that B is associated with A, and B can be determined according to A. However, it should also be understood that determining B according to A does not mean determining B only according to A, and B can also be determined according to A and / or other information.

[0061] When explaining the embodiments of the present application, some concepts and related prior art used in the following description are first explained.

[0062] For a comprehensive energy microgrid (hereinafter simply referred to as microgrid), before the following solutions, it is necessary to pre-analyze the operating characteristics of different working units and various controllable loads in the comprehensive energy microgrid, and obtain relevant mathematical models. Specifically, different parts of the comprehensive energy microgrid structure can be divided into the power supply side and the user side;

[0063] Among them, the power supply side includes at least one of the following: wind power generation system, photovoltaic power generation system, cogeneration system, heat pump, battery, and heat storage tank; further, the above power supply side devices can be specifically divided into a power supply unit (such as a wind power generation system, a photovoltaic power generation system, and a cogeneration system), a heat supply unit (such as a cogeneration system and a heat pump), and a controllable unit (such as a battery and a heat storage tank). The following is an example of the mathematical model corresponding to each device or system.

[0064] 1) Wind power generation system

[0065] A wind turbine generator system (WT) is a device that converts mechanical energy into electrical energy. Its main structure includes a wind turbine impeller, a drive shaft, a gearbox, a controller, and a generator. Its specific structure diagram is as shown in Figure 1 shown. The wind power generation system drives the blades to rotate through the wind to generate mechanical energy, and then transmits the mechanical energy to the rotor of the generator through the drive shaft and the gearbox to generate an electromagnetic effect and then convert it into electrical energy. The ideal mathematical model for converting wind energy into electrical energy using kinetic knowledge is as follows:

[0066]

[0067] Among them, P WT represents the wind power generation power; ρ represents the local air density (kg / m 2 ); R represents the radius of the wind turbine (m); V(t) represents the wind speed at time t; C W represents the wind energy utilization rate.

[0068] 2) Photovoltaic power generation system

[0069] A photovoltaic power generation system (PV) is a device that directly converts solar energy into electrical energy through the photovoltaic effect of semiconductors. Its main structure includes photovoltaic panels, a controller, an inverter, etc. The photovoltaic power generation system has the characteristics of simple structure, short early construction period, and high stability. Its specific structure is as shown in Figure 2 shown. As shown in Figure 2 shown, the photovoltaic panels are used as a medium to convert solar energy into direct current and then convert it into alternating current through an inverter. The role of the controller is to control the maximum power output of the entire photovoltaic power generation system and obtain electrical energy that meets the load quality requirements; from actual engineering experience, the photovoltaic power generation system is often affected by the light intensity and temperature at time t. Its specific mathematical model is as follows:

[0070]

[0071]

[0072] Among them, T PV (t) represents the operating temperature (°C) of the photovoltaic power generation system at time t; T e (t) represents the ambient temperature (°C) of the photovoltaic power generation system at time t; G(t) represents the sunlight intensity (W / m 2 ); P PV (t) represents the output power (KW) of the photovoltaic power generation system at time t; represents the maximum output power (KW) of the photovoltaic power generation system under standard light intensity and temperature test conditions; G STC represents the standard light intensity, such as 1000 W / m 2 ; k represents the power temperature coefficient; T STC represents the standard temperature (°C).

[0073] 3) Cogeneration system

[0074] The cogeneration system is the core equipment in the integrated energy microgrid, and its composition mainly includes a gas turbine and a waste heat boiler; among them, the gas turbine belongs to a small thermal generator, and its basic structure includes: a compressor, a combustion chamber, a gas turbine, a generator set, etc. At the same time, it can utilize the waste heat of the flue gas generated by burning natural gas through connecting to a waste heat boiler to meet the heat energy demand of users. Its specific structure diagram is as shown in Figure 3 shown. The mathematical model established for the cogeneration unit is as follows:

[0075] P E,GT (t) = G gas (t)η GT L gas

[0076]

[0077] Among them, P E,GT (t) represents the power generation power (kW) of the gas turbine at time t; G gas (t) represents the natural gas consumption (m 3 ) at time t; η GT represents the power generation efficiency of the gas turbine; L gas represents the lower calorific value of natural gas (kWh / m3); P H，GT (t) represents the output thermal power (kW) of the waste heat boiler at time t; η Loss represents the loss rate during the heat energy recovery process of the waste heat boiler; δ heat represents the waste heat boiler efficiency.

[0078] 4) Heat pump

[0079] The heat pump (HP) is a commonly used "electricity - heat" conversion device, which has the characteristics of low noise and high efficiency. Its general principle is to use shallow geothermal energy as the heat source and only a small amount of electric energy to achieve the conversion from low - grade heat energy to high - grade heat energy. It is often three times the conversion rate of ordinary electric boiler equipment. Its mathematical model is as follows:

[0080] P H,HP (t)=P E,HP (t)η HP

[0081] Among them, P H,HP (t) represents the heat output power of the heat pump at time t (kW); P E,HP (t) represents the input electric power of the heat pump at time t (kW); η HP represents the "electricity - heat" conversion efficiency of the heat pump.

[0082] 5) Battery

[0083] Energy storage refers to storing different forms of energy through specific devices or physical and chemical media for future use. It can be mainly divided into electrical energy storage, thermal energy storage, electromagnetic energy storage, etc. At present, for the integrated energy micro - grid, the battery (Battery Storge, BS) of electrochemical energy storage has the characteristics of safety, stability, mature development technology, high charge - discharge efficiency, etc. Therefore, all the electrical energy storage devices described in this article take this type of battery as an example. The mathematical model is constructed according to the battery capacity, state of charge (SOC), and charge - discharge power of the battery:

[0084]

[0085] Among them, SOC(t) represents the state of charge at time t, that is, the ratio of the remaining charge in the battery at time t to the battery capacity, and generally takes values between [0, 1]; represents the charge - discharge efficiency of the battery; represents the charge - discharge power of the battery at time t (kW); E BS represents the battery capacity of the battery (kWh), that is, all the electric energy that the battery can store / release.

[0086] 6) Thermal storage tank

[0087] After installing a combined heat and power (CHP) system in an integrated energy microgrid, there is often a certain coupling relationship between the electricity and heat production in the integrated energy microgrid. When there is an imbalance between the electricity and heat supply and demand of users, it will cause the phenomenon of energy curtailment in the integrated energy microgrid system. The introduction of a heat storage tank (HS) can absorb heat energy for storage when the heat energy produced by the CHP system is excessive, and release heat energy to meet the heat load demand of users when there is a heat deficit, thus effectively ensuring the heat energy supply and demand of the integrated energy microgrid. At the same time, participating in demand response can improve the economy of the system. Therefore, an integrated energy microgrid with CHP often installs a heat storage tank. The characteristics of the heat storage tank are similar to those of a battery. Therefore, in this paper, the mathematical model of the heat storage tank is also determined by the heat storage tank capacity, the heat storage state quantity (HSS), and the charging and discharging power:

[0088]

[0089] Among them, HSS(t) represents the heat storage state quantity at time t; represents the charging and discharging efficiency of the heat storage tank; represents the charging and discharging power (kW) of the heat storage tank at time t; E HS represents the heat storage tank capacity (kWh).

[0090] On the electricity consumption side, it includes: dispatchable loads and non-dispatchable loads. Among them, non-dispatchable loads are the loads that cannot be interrupted during the daily operation of the integrated energy microgrid. Interrupting such loads often causes relatively large losses (such as elevator and lighting loads). Therefore, they are the rigid loads that need to be satisfied during the daily operation of the integrated energy microgrid system and also the loads with the highest proportion in the daily loads. Optimization control of them is not considered. Dispatchable loads can be specifically divided into interruptible loads and shiftable loads. Interruptible loads are those when the electric power supply of the integrated energy microgrid system is insufficient, the system needs to cut off a certain amount of load and give certain economic compensation to customers, while shiftable loads are those that delay or advance the electricity consumption time of the load on the premise of keeping the total electricity consumption unchanged, such as washing machines and charging devices.

[0091] Therefore, the mathematical model corresponding to the loads on the electricity consumption side is:

[0092] P ELoad =P im +P tr -P cut

[0093] Among them, P ELoad represents the total electric load power (kW) of the system; P im 、P tr 、P cutrespectively represent the unschedulable load, shiftable load, and interruptible load power (kW) of the system.

[0094] Scheduling the shiftable load is one of the important means in the optimal operation of the integrated energy microgrid. Transferring the electricity load needs to meet the following constraints:

[0095] (1) The total amount of shiftable load remains unchanged within a scheduling period, that is:

[0096]

[0097] where P tr (t) represents the load transfer amount (kW) at time t

[0098] (2) The amount of shiftable load needs to be transferred within a certain range, that is:

[0099]

[0100] where represents the upper and lower limits of the transfer load power (kW) at time t.

[0101] (3) The interruptible load also needs to be interrupted within a certain range, that is:

[0102]

[0103] where represents the upper limit (KW) of the interruptible load at time t.

[0104] See Figure 4 , an embodiment of the present application provides an operation control method for an integrated energy microgrid group based on cooperative game, including:

[0105] Step S401, according to the operation cost composition factors of the integrated energy microgrid group, construct an optimal operation model. Based on the optimal operation model, determine the minimum operation cost of the integrated energy microgrid group through optimization, and then determine the maximum benefit;

[0106] Step S402, construct a multi-microgrid asymmetric Nash bargaining model for the integrated energy microgrid group based on cooperative game. Through equivalent transformation, transform the multi-microgrid asymmetric Nash bargaining model into a coalition benefit model and an in-coalition benefit distribution model;

[0107] Step S403, according to the alternating direction multiplier method and the coalition benefit model, obtain the optimal microgrid interaction energy of each integrated energy microgrid;

[0108] Step S404, according to the optimal microgrid interaction energy of each integrated energy microgrid, the alternating direction multiplier method, and the in-coalition benefit distribution model, obtain the optimal payment of each integrated energy microgrid.

[0109] In this embodiment, the integrated energy microgrid group is a group formed by the alliance of multiple integrated energy microgrids. When controlling the integrated energy microgrid group, first, an optimal operation model is constructed according to the factors constituting the operation cost of the integrated energy microgrid group, that is, an optimal operation model is constructed with the minimum comprehensive operation cost of the integrated energy microgrid group as the goal. The objective function of this optimal operation model can be expressed as:

[0110]

[0111] Among them, C CHP (t) represents the gas purchase cost of the combined heat and power system; C Load (t) represents the regulation cost of the load; C BS (t), C HS (t) respectively represent the loss costs of the battery and the heat storage tank; C Grid (t) represents the interaction cost with the power grid; C Q (t) represents the penalty cost for abandoned energy; C Pol (t) represents the pollutant treatment cost; T represents the number of time periods in the time period concentration; t represents the serial number of the time period.

[0112] Among them, the mathematical models corresponding to each cost can be as follows:

[0113] (1) The gas purchase cost of the combined heat and power system, that is, the cost for the integrated energy microgrid to purchase natural gas from the natural gas supplier, and its mathematical model is:

[0114] C CHP (t) = G gas (t)ρ gas

[0115] Among them, ρ gas represents the unit price of natural gas (yuan / m 3 ); G gas represents the natural gas consumption.

[0116] (2) The load regulation cost

[0117] The load regulation cost is the compensation cost for the integrated energy microgrid system to regulate its own shiftable load and interruptible load through participating in demand response and the discomfort caused to users during operation, and can be divided into shiftable load cost and interruptible load cost. That is, the load regulation cost is the sum of the shiftable load cost and the interruptible load cost, and its specific mathematical model is:

[0118] C Load (t) = C tr-Load (t) + C cut-Loa (t)

[0119] Among them, C tr-Load (t) represents the transfer load cost; C cut-Load (t) represents the interrupted load cost.

[0120] Specifically, the mathematical model of the transfer load cost is:

[0121]

[0122] Among them, λ tr represents the unit transfer load cost coefficient (yuan / kW); represents the load transfer amount (kW).

[0123] The mathematical model of the interrupted load cost is:

[0124] C cut-Load (t) = λ cut P cut (t)

[0125] Among them, λ cut represents the unit interrupted load cost coefficient (yuan / kW), and P cut (t) represents the interrupted load amount (kW).

[0126] (3) Loss cost of the battery and the heat storage tank

[0127] The charging and discharging of the battery and the charging and discharging of the heat storage tank in each time period will cause losses to the equipment itself. The mathematical model of its loss cost is:

[0128]

[0129]

[0130] Among them, C BS,s , C BS,d respectively represent the battery charging and discharging loss cost coefficients (yuan / kW); respectively represent the battery charging and discharging powers; C HS,s , C HS,d respectively represent the heat storage tank heating and discharging loss cost coefficients (yuan / kW), respectively represent the heat storage tank heating and discharging powers.

[0131] (4) Interaction cost with the public power grid

[0132] The grid-connected integrated energy microgrid often conducts power interaction with the power grid during daily operation. When there is an electricity surplus, it sells electricity to the public power grid to obtain benefits, and when there is an electricity gap, it needs to purchase electricity from the public power grid to meet the electricity load. The mathematical model of the interaction cost with the public power grid is:

[0133]

[0134] Among them, represents the power purchase from the public grid at time t (kW); represents the power sold to the public grid at time t (kW); ρ buy (t), ρ sal (t) respectively represent the power purchase price and power selling price of the power grid at time t (yuan); in order to prevent arbitrage in the integrated energy microgrid, generally ρ buy (t) > ρ sal (t).

[0135] (5) Curtailment cost

[0136] During the operation of the integrated energy microgrid, there may be power curtailment and heat curtailment phenomena. On the one hand, power curtailment occurs because of the power constraint of the tie line when the integrated energy microgrid interacts with the power grid. On the other hand, heat curtailment occurs because of the peak-valley electricity price, which makes the microgrid use a combined heat and power system for power supply. Therefore, it is necessary to introduce the curtailment costs of power and heat in the integrated energy microgrid to punish such behaviors. Its mathematical model is:

[0137] C Q (t) = λ e P Q,e (t) + λ h P Q,h (t)

[0138] Among them, λ e , λ h respectively represent the unit curtailment costs of power and heat (yuan / kW); P Q,e (t), P Q,h (t) respectively represent the curtailed power and curtailed heat at time t (kW).

[0139] (6) Pollutant emission cost

[0140] During the operation of the integrated energy microgrid, it is also necessary to consider the environmental benefits. Three types of gases are usually generated during operation, which have an impact on the environment, namely CO2, SO2, NO x , and the quantification of the emission cost is related to the gas emission volume and the treatment cost per unit of gas; among them, the emission cost of the integrated energy microgrid system mainly includes the environmental cost of power generation by the combined heat and power system and the environmental cost during power purchase and transmission from the public grid. Its mathematical model is:

[0141]

[0142] Among them, represents the unit pollutant treatment cost of the three types of gases (yuan / kg); Indicates the three gas emissions (g / kW) when the combined heat and power system generates a unit of electric power; Indicates the three gas emissions (g / kW) per unit power during the purchase and transmission of electricity from the public grid.

[0143] Furthermore, the constraint conditions for optimizing the operation model can also be determined based on the supply and demand of thermal power and electric power, as well as the interaction with the power grid:

[0144]

[0145] Among them, P HLoad (t) represents the total thermal power of the integrated energy microgrid.

[0146]

[0147] Among them, P ELoa (t) represents the total electric power of the integrated energy microgrid.

[0148]

[0149]

[0150]

[0151] Among them, Represents the upper limit of the tie-line power (KW) for the interaction between the integrated energy microgrid and the public power grid.

[0152] Thus, the optimized operation model of the integrated energy microgrid group can be determined. Among them, based on the different structures and equipment of the integrated energy microgrid group, the values of the parameters in the optimized operation models of different integrated energy microgrid groups are different in actual use.

[0153] After determining the optimized operation model of the integrated energy microgrid group, based on the optimized operation model, a multi-microgrid asymmetric Nash bargaining model based on cooperative game is constructed based on the cooperative game theory and the Nash bargaining game model to ensure the balance of the coalition revenue and individual payments.

[0154] Among them, cooperative game emphasizes that there is a strong binding force among individuals to form a coalition to participate in competition. Different from non-cooperative game, which mainly focuses on the individual benefits at the micro level, the purpose of cooperative game is to pursue the maximization of the coalition benefits and then reasonably distribute the generated profits. Cooperative game includes two conditions:

[0155] 1. The overall revenue obtained by the coalition after cooperative game is greater than the sum of the revenues of each individual in the non-cooperative situation;

[0156] 2. After the alliance distributes the benefits, the benefits obtained by each entity should also be greater than the benefits when they do not cooperate.

[0157] Once these two conditions are met, individuals will naturally form cooperation driven by interests. Compared with non - cooperative games, cooperation is more efficient. Therefore, in daily social and economic games, participants tend to use the "reciprocal" method to increase the common profit of all parties. Therefore, for the optimal operation problem of multiple integrated energy micro - grids, it is obviously more appropriate to use cooperative games. The basic steps of cooperative games can be divided into two stages: The first stage is coalition rationality, that is, all parties form a coalition and work together to maximize the benefits of the coalition; the second stage is the profit distribution stage; and the research focus of cooperative games is the profit distribution problem in the second stage.

[0158] The Nash bargaining game model is based on the classical bargaining model and uses the analysis framework of game theory to analyze the bargaining model. This model proposes four hypothetical axioms and finds the Nash equilibrium solution for them. The four hypothetical axioms are as follows:

[0159] 1. (Efficiency) The final solution based on the Nash bargaining model must reach the Pareto - optimal state;

[0160] 2. (Symmetry) The order of offers from each entity does not affect the final solution;

[0161] 3. (Independence) Removing the unselected offers in the choice set does not affect the final solution;

[0162] 4. (Irrelevance) Linear transformation of the objective function does not affect the final solution.

[0163] That is, the Nash bargaining model believes that in this model, both sides reach a final solution that is acceptable to both through mutual compromise and gradual concession, which is also its unique equilibrium solution.

[0164] Therefore, the multi - micro - grid asymmetric Nash bargaining model satisfies that the product of the growth benefits after cooperation within each integrated energy micro - grid group is the largest, and the sum of the benefits after cooperation within each integrated energy micro - grid group is equal to the maximum benefit of the entire integrated energy micro - grid group.

[0165] That is, the objective function of the constructed multi - micro - grid asymmetric Nash bargaining model based on cooperative game is:

[0166]

[0167] Among them, N represents the number of integrated energy micro - grids; C n represents the individual benefit after cooperation within the nth integrated energy micro - grid group; represents the breakdown point of negotiation, which is the benefit obtained when the nth integrated energy micro - grid operates independently;

[0168] The constraints are as follows: It is ensured that the post - cooperation revenue requirement is not less than the revenue during independent operation, which guarantees individual rationality in the cooperative game.

[0169] It can be understood that the sum of the revenues after cooperation within each integrated energy micro - grid group is equal to the maximum revenue of the entire integrated energy micro - grid group, which is also a constraint condition of the multi - micro - grid asymmetric Nash bargaining model.

[0170] Furthermore, by solving the multi - micro - grid asymmetric Nash bargaining model through operations such as model transformation and obtaining relevant parameters, the optimal micro - grid interaction energy and optimal payment corresponding to each integrated energy micro - grid can be obtained.

[0171] In summary, for the optimal operation problem of the integrated energy micro - grid group, based on considering various factors of the operating costs, with the goal of the optimal economic operation of the integrated energy micro - grid group, an optimal operation model of the integrated energy micro - grid group is established. Finally, based on the multi - micro - grid asymmetric Nash bargaining model of cooperative game, the optimal micro - grid interaction energy and optimal payment of each integrated energy micro - grid are obtained, thereby reducing the total operating cost of the integrated energy micro - grid group and the operating costs of each integrated energy micro - grid, and solving the problem of unfair distribution in the traditional Nash bargaining model, effectively stimulating the energy mutual assistance among integrated energy micro - grids.

[0172] Since the multi - micro - grid asymmetric Nash bargaining model is a non - linear and non - convex model with multiple variable couplings and is difficult to solve directly, it is necessary to transform the above model into two sub - problems, namely the coalition benefit maximization sub - problem (coalition revenue model) and the payment sub - problem (intra - coalition revenue distribution model).

[0173] Specifically, in one embodiment, the coalition revenue model satisfies the maximum product of the revenues after cooperation within each integrated energy micro - grid group, that is, its first objective function is:

[0174]

[0175] By solving this equation, the optimal interaction energy between micro - grids, including thermal energy and electrical energy, can be obtained.

[0176] In one embodiment, the second objective function of the intra - coalition revenue distribution model is:

[0177]

[0178] Z n represents the payment that the nth integrated energy micro - grid group needs to give to other integrated energy micro - grids after cooperation.

[0179] Alternatively, the second objective function is the logarithm of the above formula:

[0180]

[0181] By solving this equation, the payment amount of each integrated energy microgrid using the asymmetric Nash bargaining model in the payment sub-problem can be obtained.

[0182] Furthermore, by using the alternating direction method of multipliers to solve the above-mentioned coalition revenue model and the intra-coalition revenue distribution model respectively, the optimal microgrid interaction energy and the optimal payment can be obtained. It should be noted that since the result of the coalition revenue model is required as the basis in the payment sub-problem, the intra-coalition revenue distribution model needs to be solved based on the obtained optimal microgrid interaction energy.

[0183] In some embodiments, after obtaining the optimal microgrid interaction energy of each integrated energy microgrid, it may further include determining the energy contribution degree corresponding to each integrated energy microgrid according to the optimal microgrid interaction energy; and correcting the intra-coalition revenue distribution model based on the energy contribution degree corresponding to each integrated energy microgrid to obtain the intra-coalition revenue distribution model based on the energy contribution degree.

[0184] The third objective function of the intra-coalition revenue distribution model based on the energy contribution degree is:

[0185]

[0186] where a n represents the energy contribution degree of integrated energy microgrid n.

[0187] Alternatively, the third objective function is obtained by taking the logarithm of the above formula:

[0188]

[0189] When integrated energy microgrids conduct energy mutual assistance, the energy provided and obtained by each integrated energy microgrid are not the same. Therefore, to ensure fairness and justice in revenue distribution, it is necessary to use the energy contribution degree of each integrated energy microgrid as a bargaining chip to determine the corresponding revenue distribution and / or payment.

[0190] Among them, when obtaining the energy contribution degree of each integrated energy microgrid, first obtain the energy provided and the energy obtained by each integrated energy microgrid respectively through the following formula:

[0191]

[0192]

[0193] where represents the energy provided by each integrated energy microgrid through cooperation in the multi-integrated energy microgrid system; It represents the energy obtained by each integrated energy microgrid through cooperation in the multi-microgrid system; z represents the type of energy exchanged between each integrated energy microgrid. Among them, T is preferably 24 hours.

[0194] Furthermore, based on the maximum value of the energy provided by each integrated energy microgrid and the maximum value of the energy obtained, the maximum provided energy in the multi-integrated energy microgrid is determined. and the maximum obtained energy That is:

[0195]

[0196] Furthermore, based on the following formula, the contribution degree a of each integrated energy microgrid in the multi-integrated energy microgrid is determined. n :

[0197]

[0198] where e is the natural constant.

[0199] Further, according to the contribution degree a n the above-mentioned finally determined intra-alliance revenue distribution model can be obtained by modifying the intra-alliance revenue distribution model. And this intra-alliance revenue distribution model has the following characteristics:

[0200] (1) The bargaining chips of the integrated energy microgrid are all greater than or equal to zero;

[0201] (2) In the multi-integrated energy microgrid system, as long as the integrated energy microgrid participates in energy mutual assistance, it has bargaining chips;

[0202] (3) For the integrated energy microgrid that does not participate in energy supply and energy acquisition, it has no bargaining chips and the revenue obtained in the multi-integrated energy microgrid is zero;

[0203] (4) The greater the values of energy supply and energy acquisition of the integrated energy microgrid, the higher the bargaining chips obtained, and the contribution degree of energy supply will be greater than the contribution degree of energy acquisition.

[0204] See Figure 5 , specifically, as in step S403 above, the optimal microgrid interaction energy of each integrated energy microgrid obtained according to the alternating direction multiplier method and the alliance revenue model includes:

[0205] Step S501, construct the first augmented Lagrangian function according to the first objective function in the alliance revenue model;

[0206] Step S502, obtain the optimal microgrid interaction energy of each integrated energy microgrid according to the alternating direction multiplier method and the first augmented Lagrangian function.

[0207] In this embodiment, when obtaining the optimal microgrid interaction energy, iterative calculations need to be performed based on the alternating direction method of multipliers. Among them, the alternating direction method of multipliers (ADMM) is a widely used distributed algorithm in machine learning applications. It parallelly solves each sub-problem after transforming the original problem into multiple sub-problems, integrating the relaxation convergence condition of the Lagrangian multiplier method and the decoupling characteristics of the dual ascent method, with good convergence and high robustness, thus facilitating ensuring the accuracy of the obtained results.

[0208] Specifically, when performing calculations, since there is energy interaction between integrated energy microgrids, it is necessary to decouple the energy interaction between integrated energy microgrids, where:

[0209]

[0210] Among them, represents the z energy that the integrated energy microgrid n expects to interact with the integrated energy microgrid m at time period t; represents the z energy that the integrated energy microgrid m expects to interact with the integrated energy microgrid n at time period t; when z = 1, it means the interaction energy is electric power, and when z = 2, it means the interaction energy is thermal power.

[0211] Furthermore, based on the first objective function in the coalition revenue model, a first augmented Lagrangian function is constructed, and the first augmented Lagrangian function is:

[0212]

[0213] Among them, represents the first augmented Lagrangian value; T represents the number of time periods in the time period set; z represents the type of energy interaction between each integrated energy microgrid; represents the first Lagrangian multiplier at time period t.

[0214] And, the constraint condition of this first augmented Lagrangian function is:

[0215] -C n (t)=C n,CHP (t)+C n,Load (t)+C n,BS (t)+C n,HS (t)+C n,Grid (t)+C n,Q (t)+C n,Pol (t)

[0216]

[0217]

[0218]

[0219]

[0220] Among them, represents the maximum transmission power (kW) of the electrical and thermal power transmission connection line / pipeline between integrated energy microgrids.

[0221] By solving the first augmented Lagrangian function using the alternating direction method of multipliers, the optimal microgrid interaction energy can be obtained

[0222] It should be noted that each integrated energy microgrid corresponds to a first augmented Lagrangian function.

[0223] See Figure 6 , further, as in step S502 above, obtaining the optimal microgrid interaction energy of each integrated energy microgrid according to the alternating direction method of multipliers and the first augmented Lagrangian function includes:

[0224] Step S601, initialize the first augmented Lagrangian function to obtain the initialized first iteration number, the first Lagrange multiplier, and the microgrid interaction energy corresponding to each integrated energy microgrid, and determine the first primal residual threshold and the first dual residual threshold;

[0225] Step S602, substitute the current microgrid interaction energy into the current first augmented Lagrangian function to obtain the new microgrid interaction energy corresponding to each integrated energy microgrid;

[0226] Step S603, determine the first primal residual and the first dual residual between the currently obtained microgrid interaction energy and the microgrid interaction energy obtained in the previous iteration;

[0227] Step S604, determine whether the obtained first primal residual is not greater than the first primal residual threshold and the first dual residual is not greater than the first dual residual threshold;

[0228] If the judgment in step S604 is yes, execute step S606; if the judgment in step S604 is no, execute step S605.

[0229] Step S605, increase the first iteration number by 1, and update the first Lagrange multiplier according to the current microgrid interaction energy and the first iteration number;

[0230] After step S605, return to execute step S602;

[0231] Step S606, determine the current microgrid interaction energy as the optimal microgrid interaction energy.

[0232] In this embodiment, an example of the steps for obtaining the optimal interaction energy is given. First, the first augmented Lagrangian function is initialized, that is, the first iteration number is initialized to 0, the first Lagrange multiplier is initialized to 0, and the microgrid interaction energy corresponding to each integrated energy microgrid is initialized to 0, and the first original residual threshold (for example, 10 -3 ) and the first dual residual threshold (for example, 10 -3 ) are determined.

[0233] After calculation, the first Lagrange multiplier is updated according to the preset first Lagrange multiplier update formula, and the first iteration number is incremented by 1. Among them, the first Lagrange multiplier update formula is:

[0234]

[0235] represents the updated first Lagrange multiplier.

[0236] The convergence of the first original residual, that is, the first original residual is not greater than the first original residual threshold, can be expressed as:

[0237]

[0238] The convergence of the first dual residual, that is, the first dual residual is not greater than the first dual residual threshold, can be expressed as:

[0239]

[0240] Among them, ζ1 is the first original residual threshold; ζ2 is the first dual residual threshold.

[0241] See Figure 7 , specifically, as in step S404 above, the obtaining of the optimal payment for each integrated energy microgrid according to the optimal microgrid interaction energy, the alternating direction multiplier method, and the intra-alliance revenue distribution model of each integrated energy microgrid includes:

[0242] Step S701, constructing a second augmented Lagrangian function according to the second objective function in the intra-alliance revenue distribution model based on the energy contribution degree;

[0243] Step S702, obtaining the optimal payment for each integrated energy microgrid according to the alternating direction multiplier method and the second augmented Lagrangian function.

[0244] Similar to the above steps for obtaining the optimal microgrid interaction energy according to the alternating direction multiplier method, in this embodiment, when obtaining the optimal payment according to the alternating direction multiplier method, it is also necessary to first construct a second augmented Lagrangian function according to the second objective function in the intra-alliance revenue distribution model. Among them, the second augmented Lagrangian function is:

[0245]

[0246] Among them, represents the second augmented Lagrangian value; Ψ n represents the Lagrange multiplier; γ n represents the penalty factor.

[0247] Moreover, the constraint condition of this second augmented Lagrangian function is:

[0248]

[0249] By solving the second augmented Lagrangian function through the alternating direction method of multipliers, the optimal payment Z n .

[0250] It should be noted that each integrated energy microgrid corresponds to a second augmented Lagrangian function respectively.

[0251] See Figure 8 , furthermore, as in step 702 above, obtaining the optimal payment of each integrated energy microgrid according to the alternating direction method of multipliers and the second augmented Lagrangian function includes:

[0252] Step S801, initialize the second augmented Lagrangian function to obtain the initialized second iteration number, the second Lagrange multiplier, and the payments of each integrated energy microgrid, and determine the second primal residual threshold, the second dual residual threshold, and the penalty factor;

[0253] Step S802, substitute the current payments of each integrated energy microgrid into the current second augmented Lagrangian function to obtain the new payments of each integrated energy microgrid;

[0254] Step S803, determine the second primal residual and the second dual residual between the currently obtained payment and the payment obtained in the previous adjacent iteration;

[0255] Step S804, judge whether the obtained second primal residual is not greater than the second primal residual threshold and the second dual residual is not greater than the second dual residual threshold;

[0256] If the judgment in step S804 is yes, execute step S806; if the judgment in step S804 is no, execute step S805;

[0257] Step S805, increase the second iteration number by 1, and update the second Lagrange multiplier according to the current payment and the second iteration number;

[0258] After step S805, return to execute step S802;

[0259] Step S806, determine the current payment as the optimal payment.

[0260] In this embodiment, the steps for obtaining the optimal interactive payment are exemplified. First, the second augmented Lagrangian function is initialized, that is, the second iteration number is initialized to 0, the second Lagrange multiplier is initialized to 0, the payment corresponding to each integrated energy microgrid is initialized to 0, and the second original residual threshold (for example, 10 -3 ) and the second dual residual threshold (for example, 10 -3 ) and the first penalty factor (for example, 0.01) are determined;

[0261] Furthermore, based on the above initialized parameters and each payment substituted into the second augmented Lagrangian function for solution, the new payment expected by the integrated energy microgrid is obtained;

[0262] After the calculation, the second Lagrange multiplier is updated according to the preset second Lagrange multiplier update formula, and the second iteration number is incremented by 1. The second Lagrange multiplier update formula is:

[0263]

[0264] represents the updated second Lagrange multiplier.

[0265] Thereafter, the second original residual and the second dual residual of each integrated energy microgrid in the current iteration process are obtained, and threshold judgment is performed with the corresponding thresholds, and the respective second judgment results are obtained.

[0266] Among them, the convergence of the second original residual, that is, the second original residual is not greater than the second original residual threshold, can be expressed as:

[0267]

[0268] The convergence of the second dual residual, that is, the second dual residual is not greater than the second dual residual threshold, can be expressed as:

[0269]

[0270] Among them, θ1 is the second original residual threshold; θ2 is the second dual residual threshold.

[0271] See Figure 9 , another embodiment of the present application further provides an operation control device for an integrated energy microgrid group based on cooperative game, including:

[0272] The first optimization module 901 is configured to construct an optimal operation model according to the operation cost composition factors of the integrated energy microgrid group, and based on the optimal operation model, determine the minimum operation cost of the integrated energy microgrid group through optimization, and further determine the maximum benefit;

[0273] The model construction module 902 is configured to construct a multi-microgrid asymmetric Nash bargaining model based on cooperative game for the integrated energy microgrid group. Through equivalent transformation, the multi-microgrid asymmetric Nash bargaining model is transformed into an alliance revenue model and an in-alliance revenue distribution model. The multi-microgrid asymmetric Nash bargaining model satisfies that the product of the growth revenues after cooperation within each integrated energy microgrid group is maximized, and the sum of the revenues after cooperation within each integrated energy microgrid group is equal to the maximum revenue.

[0274] The second optimization module 903 is configured to obtain the optimal microgrid interaction energy of each integrated energy microgrid according to the alternating direction method of multipliers and the alliance revenue model.

[0275] The third optimization module 904 is configured to obtain the optimal payment of each integrated energy microgrid according to the optimal microgrid interaction energy of each integrated energy microgrid, the alternating direction method of multipliers, and the in-alliance revenue distribution model.

[0276] In some embodiments, after obtaining the optimal microgrid interaction energy of each integrated energy microgrid, the model construction module 902 is further configured to:

[0277] Determine the energy contribution degree corresponding to each integrated energy microgrid according to the optimal microgrid interaction energy; and correct the in-alliance revenue distribution model based on the energy contribution degree corresponding to each integrated energy microgrid to obtain an in-alliance revenue distribution model based on energy contribution degree.

[0278] In some embodiments, the second optimization module 903, which is configured to obtain the optimal microgrid interaction energy of each integrated energy microgrid according to the alternating direction method of multipliers and the alliance revenue model, is configured to:

[0279] Construct a first augmented Lagrangian function according to the first objective function in the alliance revenue model as:

[0280]

[0281] Where represents the first augmented Lagrangian value; T represents the number of time periods in the time period set; z represents the energy types of interaction between each integrated energy microgrid; represents the first Lagrange multiplier at time period t; represents the z energy that integrated energy microgrid n expects to interact with integrated energy microgrid m at time period t; represents the z energy that integrated energy microgrid m expects to interact with integrated energy microgrid n at time period t;

[0282] Obtain the optimal microgrid interaction energy of each integrated energy microgrid according to the alternating direction method of multipliers and the first augmented Lagrangian function.

[0283] In some embodiments, the second optimization module 903, which obtains the optimal microgrid interaction energy of each integrated energy microgrid according to the alternating direction multiplier method and the first augmented Lagrangian function, is used for:

[0284] Initialize the first augmented Lagrangian function to obtain the initialized first iteration count, the first Lagrange multiplier, and the microgrid interaction energy corresponding to each integrated energy microgrid, and determine the first primal residual threshold and the first dual residual threshold; substitute the current microgrid interaction energy into the current first augmented Lagrangian function to obtain the new microgrid interaction energy corresponding to each integrated energy microgrid; determine the first primal residual and the first dual residual between the currently obtained microgrid interaction energy and the microgrid interaction energy obtained in the previous iteration; determine whether the obtained first primal residual is not greater than the first primal residual threshold and the first dual residual is not greater than the first dual residual threshold; if so, determine the current microgrid interaction energy as the optimal microgrid interaction energy; if not, increase the first iteration count by 1, update the first Lagrange multiplier according to the current microgrid interaction energy and the first iteration count, and return to execute substituting the current microgrid interaction energy into the current first augmented Lagrangian function to obtain the new microgrid interaction energy corresponding to each integrated energy microgrid.

[0285] In some embodiments, the third optimization module 904, which obtains the optimal payment of each integrated energy microgrid according to the optimal microgrid interaction energy of each integrated energy microgrid, the alternating direction multiplier method, and the in - alliance revenue distribution model, is used for:

[0286] Construct a second augmented Lagrangian function according to the second objective function in the in - alliance revenue distribution model based on energy contribution degree as:

[0287]

[0288] Where represents the second augmented Lagrangian value; a n represents the energy contribution degree of integrated energy microgrid n; Ψ n represents the second Lagrange multiplier; Z m represents the payment that the m - th integrated energy microgrid group needs to give to other integrated energy microgrids after cooperation; γ n represents the penalty factor;

[0289] Obtain the optimal payment of each integrated energy microgrid according to the alternating direction multiplier method and the second augmented Lagrangian function.

[0290] In some embodiments, the third optimization module 904, which obtains the optimal payment of each integrated energy microgrid according to the alternating direction multiplier method and the second augmented Lagrangian function, is used for:

[0291] Initialize the second augmented Lagrangian function to obtain the initialized second iteration count, the second Lagrange multiplier, and the payments of each integrated energy microgrid. Determine the second primal residual threshold, the second dual residual threshold, and the penalty factor. Substitute the current payments of each integrated energy microgrid into the current second augmented Lagrangian function to obtain the new payments of each integrated energy microgrid. Determine the second primal residual and the second dual residual between the currently obtained payments and the payments obtained in the previous iteration. Determine whether the obtained second primal residual is not greater than the second primal residual threshold and the second dual residual is not greater than the second dual residual threshold. If so, determine the current payments as the optimal payments. If not, increment the second iteration count by 1, update the second Lagrange multiplier based on the current payments and the second iteration count, and return to execute the step of substituting the current payments of each integrated energy microgrid into the current second augmented Lagrangian function to obtain the new payments of each integrated energy microgrid.

[0292] The apparatus embodiment of the present application is an apparatus corresponding to the embodiment of the operation control method of the integrated energy microgrid group based on cooperative game. All the implementation means in the above method embodiment are applicable to the embodiment of this apparatus and can also achieve the same technical effect.

[0293] Another embodiment of the present application further provides a server, including a processor, a memory, and a computer program stored on the memory and executable on the processor. When the computer program is executed by the processor, it implements the steps of the operation control method of the integrated energy microgrid group based on cooperative game as described above.

[0294] Another embodiment of the present application further provides a computer-readable storage medium with a computer program stored thereon. When the computer program is executed by a processor, it implements the steps of the operation control method of the integrated energy microgrid group based on cooperative game as described above.

[0295] In addition, the present application may repeat reference numerals and / or letters in different examples. This repetition is for the purpose of simplicity and clarity and does not itself indicate the relationship between the various embodiments and / or arrangements discussed.

[0296] It should also be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variation thereof is intended to cover non-exclusive inclusion.

[0297] The above are the preferred embodiments of the present application. It should be noted that for those of ordinary skill in the art, without departing from the principle described in the present application, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present application.

Claims

1. An operation control method for an integrated energy microgrid group based on cooperative game, characterized in that, Including: Construct an optimal operation model according to the operating cost composition factors of the integrated energy microgrid group. Based on the optimal operation model, determine the minimum operating cost of the integrated energy microgrid group through optimization, and then determine the maximum benefit. Construct a multi-microgrid asymmetric Nash bargaining model based on cooperative game for the integrated energy microgrid group. Through equivalent transformation, transform the multi-microgrid asymmetric Nash bargaining model into an alliance benefit model and an in-alliance benefit distribution model. The multi-microgrid asymmetric Nash bargaining model satisfies that the product of the increased benefits after cooperation within each integrated energy microgrid group is the largest, and the sum of the benefits after cooperation within each integrated energy microgrid group is equal to the maximum benefit. Obtain the optimal microgrid interaction energy of each integrated energy microgrid according to the alternating direction multiplier method and the alliance benefit model. Obtain the optimal payment of each integrated energy microgrid according to the optimal microgrid interaction energy of each integrated energy microgrid, the alternating direction multiplier method, and the in-alliance benefit distribution model.

2. The method according to claim 1, characterized in that, The alliance benefit model satisfies that the product of the benefits after cooperation within each integrated energy microgrid group is the largest. The revenue distribution model within the alliance satisfies being the maximum; where N represents the number of integrated energy microgrids; Z n represents the payment that the nth integrated energy microgrid group needs to give to other integrated energy microgrids after cooperation, and C n represents the revenue of the nth integrated energy microgrid group after cooperation; represents the revenue when the nth integrated energy microgrid operates alone.

3. The method according to claim 2, wherein After obtaining the optimal microgrid interaction energy of each integrated energy microgrid, it further includes: Determine the energy contribution degree corresponding to each integrated energy microgrid according to the optimal microgrid interaction energy. Modify the in-alliance benefit distribution model based on the energy contribution degree corresponding to each integrated energy microgrid to obtain an in-alliance benefit distribution model based on energy contribution degree.

4. The method according to claim 2, wherein The obtaining the optimal microgrid interaction energy of each integrated energy microgrid according to the alternating direction multiplier method and the alliance benefit model includes: Construct a first augmented Lagrangian function according to the first objective function in the alliance benefit model as: Among them, represents the first augmented Lagrangian value; T represents the number of time periods in the time period set; z represents the energy types of interactions between various integrated energy microgrids; represents the first Lagrange multiplier at time period t; represents the z energy that integrated energy microgrid n expects to interact with integrated energy microgrid m at time period t; represents the z energy that integrated energy microgrid m expects to interact with integrated energy microgrid n at time period t; Obtain the optimal microgrid interaction energy of each integrated energy microgrid according to the alternating direction multiplier method and the first augmented Lagrangian function.

5. The method according to claim 4, wherein The obtaining the optimal microgrid interaction energy of each integrated energy microgrid according to the alternating direction multiplier method and the first augmented Lagrangian function includes: Initialize the first augmented Lagrangian function to obtain the initialized first iteration number, the first Lagrange multiplier, and the microgrid interaction energy corresponding to each integrated energy microgrid, and determine the first primal residual threshold and the first dual residual threshold. Substitute the current microgrid interaction energy into the current first augmented Lagrangian function to obtain the new microgrid interaction energy corresponding to each integrated energy microgrid. Determine the first primal residual and the first dual residual between the currently obtained microgrid interaction energy and the microgrid interaction energy obtained in the previous adjacent time. Judge whether the obtained first primal residual is not greater than the first primal residual threshold and the first dual residual is not greater than the first dual residual threshold. If so, determine the current microgrid interaction energy as the optimal microgrid interaction energy. If not, increase the first iteration number by 1, update the first Lagrange multiplier according to the current microgrid interaction energy and the first iteration number, and return to execute the step of substituting the current microgrid interaction energy into the current first augmented Lagrangian function to obtain the new microgrid interaction energy corresponding to each integrated energy microgrid.

6. The method according to claim 3, wherein Obtaining the optimal payment for each integrated energy microgrid according to the optimal microgrid interaction energy of each integrated energy microgrid, the alternating direction multiplier method, and the in-alliance revenue distribution model includes: Constructing a second augmented Lagrangian function according to the second objective function in the in-alliance revenue distribution model based on the energy contribution degree as: Among them, represents the second augmented Lagrangian value; a n represents the energy contribution degree of the integrated energy microgrid n; Ψ n represents the second Lagrange multiplier; Z m represents the payment that the m-th integrated energy microgrid group needs to give to other integrated energy microgrids after cooperation; γ n represents the penalty factor; Obtaining the optimal payment for each integrated energy microgrid according to the alternating direction multiplier method and the second augmented Lagrangian function.

7. The method according to claim 6, wherein The obtaining the optimal payment for each integrated energy microgrid according to the alternating direction multiplier method and the second augmented Lagrangian function includes: Initializing the second augmented Lagrangian function to obtain the initialized second iteration number, second Lagrange multiplier, and the payment of each integrated energy microgrid, and determining the second primal residual threshold, second dual residual threshold, and penalty factor; Substituting the current payment of each integrated energy microgrid into the current second augmented Lagrangian function to obtain the new payment of each integrated energy microgrid; Determining the second primal residual and second dual residual between the currently obtained payment and the payment obtained in the previous adjacent iteration; Judging whether the obtained second primal residual is not greater than the second primal residual threshold and the second dual residual is not greater than the second dual residual threshold; If so, determining the current payment as the optimal payment; If not, increasing the second iteration number by 1, updating the second Lagrange multiplier according to the current payment and the second iteration number, and returning to execute the step of substituting the current payment of each integrated energy microgrid into the current second augmented Lagrangian function to obtain the new payment of each integrated energy microgrid.

8. An operation control device for an integrated energy microgrid group based on cooperative game, characterized in that, Including: A first optimization module, configured to construct an optimal operation model according to the operating cost composition factors of the integrated energy microgrid group, and based on the optimal operation model, determining the minimum operating cost of the integrated energy microgrid group through optimization, and further determining the maximum revenue; A model construction module, configured to construct a multi-microgrid asymmetric Nash bargaining model based on cooperative game for the integrated energy microgrid group, and through equivalent transformation, transforming the multi-microgrid asymmetric Nash bargaining model into an in-alliance revenue model and an in-alliance revenue distribution model, where the multi-microgrid asymmetric Nash bargaining model satisfies that the product of the increased revenues after cooperation within each integrated energy microgrid group is the largest, and the sum of the revenues after cooperation within each integrated energy microgrid group is equal to the maximum revenue; A second optimization module, configured to obtain the optimal microgrid interaction energy of each integrated energy microgrid according to the alternating direction multiplier method and the in-alliance revenue model; A third optimization module, configured to obtain the optimal payment of each integrated energy microgrid according to the optimal microgrid interaction energy of each integrated energy microgrid, the alternating direction multiplier method, and the in-alliance revenue distribution model.

9. A server, characterized in that, Including a processor, a memory, and a computer program stored on the memory and executable on the processor, where when the computer program is executed by the processor, the steps of the operation control method for the integrated energy microgrid group based on cooperative game according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium. When the computer program is executed by a processor, the steps of the operation control method of the integrated energy microgrid group based on cooperative game as described in any one of claims 1 to 7 are implemented.

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