Scheduling Method and Device for Integrated Energy System Based on Multi - layer Game

Abstract

The present invention relates to a scheduling method and device for an integrated energy system based on multi-layer game, belonging to the technical field of energy scheduling in power systems. The method includes: constructing a shared energy storage model, an energy system model, and a prosumer model. The shared energy storage model includes a first power constraint and a first objective function. The energy system model includes a second power constraint and a second objective function. The prosumer alliance model includes an electric and thermal load constraint and a third objective function; constructing a three-layer game model based on the shared energy storage model, the energy system model, and the prosumer alliance model; solving the three-layer game model to obtain the scheduling result of the integrated energy system. The present invention constructs a three-layer game model for the shared energy storage system, the integrated energy system, and the prosumer alliance, thereby balancing the interests of the three parties and solving the problem of unbalanced interest distribution among individual or multiple subjects of the same level in the integrated energy system due to collaborative optimization.

Description

Technical Field

[0001] The present invention relates to the technical field of power system energy scheduling, and particularly to a scheduling method for an integrated energy system based on multi-layer game theory. Background Art

[0002] With the increasing depletion of traditional fossil energy, it has become an urgent task to develop various energy complementary technologies to improve energy use efficiency. Under the background of the carbon neutrality goal, the grid connection of distributed renewable energy sources including photovoltaic and wind power has brought new challenges to the power system.

[0003] Through the complementarity of various energy sources, the integrated energy system optimizes the scheduling of regional flexible resources, and can effectively cope with the output fluctuations of renewable energy sources. Its application has become an inevitable trend. For the optimal scheduling problem of energy complementarity in the integrated energy system, due to the fact that the actual operating conditions involve multi-party collaborative scheduling, the elements of optimizing the internal output of the integrated energy system and participating in the collaborative optimization scheduling of external energy have become increasingly complex. In recent years, research often considers this scheduling problem as a collaborative optimization problem of a single subject or multiple subjects at the same level, and the model only includes the goal of its own benefits, and cannot provide a better decision-making scheme for the integrated energy system in the optimization scheduling in an unfavorable position.

[0004] In summary, there is a lack of a scheduling method for an integrated energy system based on multi-layer game theory in the prior art to coordinate each subject, so as to balance and optimize the interests of each subject. Summary of the Invention

[0005] In view of this, it is necessary to provide a scheduling method and device for an integrated energy system based on multi-layer game theory to solve the problem of unbalanced interest distribution among individual subjects or multiple subjects at the same level in the integrated energy system.

[0006] To solve the above problems, the present invention provides a scheduling method for an integrated energy system based on multi-layer game theory, including:

[0007] Construct a shared energy storage model, an energy system model, and a prosumer model. The shared energy storage model includes a first power constraint and a first objective function constructed with the maximum daily benefit of the shared energy storage system. The energy system model includes a second power constraint and a second objective function constructed with the maximum daily benefit of the energy system. The prosumer alliance model includes an electric and thermal load constraint and a third objective function constructed with the minimum cost of the prosumer alliance.

[0008] Construct a three-layer game model based on the shared energy storage model, the energy system model, and the prosumer alliance model;

[0009] Solve the three-layer game model to obtain the scheduling result of the integrated energy system.

[0010] In a possible implementation, the expression of the first power constraint is:

[0011]

[0012] In the formula, represents the capacity of the shared energy storage station at moment, and respectively represent the charging and discharging power of the shared energy storage station at and respectively represent the charging and discharging efficiency of the shared energy storage station, and respectively represent the lower and upper limits of the capacity of the shared energy storage station, and respectively represent the lower and upper limits of the charging and discharging power of the shared energy storage station, and respectively represent the charging and discharging identification bits of the shared energy storage station at

[0013] The expression of the first objective function is:

[0014]

[0015]

[0016] In the formula, is the comprehensive benefit of the shared energy storage station within a day, and respectively represent the revenues from the transactions between the shared energy storage station and the power grid and the integrated energy system at represents the self-charging, discharging, operation and maintenance cost of the shared energy storage station, and and and respectively represent the power of purchasing and selling electricity from / to the power grid by the shared energy storage station and its power upper limit, and respectively represent that the control variables for purchasing and selling electricity from / to the power grid by the shared energy storage station take 0 / 1, and respectively represent the power of purchasing and selling electricity from / to the shared energy storage by the integrated energy system, represents the cost coefficient for each charge and discharge of the shared energy storage station, and respectively represent the purchase and sale electricity prices announced by the power grid at and respectively represent the purchase and sale electricity prices formulated and announced by the shared energy storage station to the integrated energy system, , respectively represent the lower and upper limits of the electricity purchase price set by the shared energy storage station for the integrated energy system at , respectively represent the lower and upper limits of the electricity purchase price set by the shared energy storage station for the integrated energy system at

[0017] In a possible implementation, the energy system model includes a clean model and a gas model. The clean model includes a wind-solar model and a concentrating solar power plant model. The gas model includes a gas turbine model and a boiler model. The second power constraint includes the input-output power balance constraint of the wind-solar model, the power generation output constraint of the concentrating solar power plant model, and the input-output power balance constraints of the gas turbine model and the boiler model;

[0018] The input-output power balance constraint formula of the wind-solar model is:

[0019]

[0020]

[0021]

[0022]

[0023] In the formula: , , respectively represent the predicted wind power generation, the actual wind power generation, and the curtailed wind power, , , respectively represent the predicted photovoltaic power generation, the actual photovoltaic power generation, and the curtailed photovoltaic power, represents the short-term prediction error of the wind power generation, represents the short-term prediction error of the photovoltaic power generation, represents the normal distribution variance of the predicted wind power generation, represents the normal distribution variance of the predicted photovoltaic power generation, represents the capacity of the battery at time, , respectively represent the charging and discharging powers of the battery, , respectively represent the charging and discharging efficiencies of the battery, , represent the lower and upper limits of the battery capacity, , represent the lower and upper limits of the charging and discharging powers of the battery, , Indicates the identification bit for the charge and discharge of the storage battery;

[0024] The expression for the power generation output constraint of the concentrating power plant model is:

[0025]

[0026]

[0027]

[0028] In the formula: Indicates the power generation of CSP at time, and indicate the thermal power provided by MF and TES to ST, Indicates the power generation efficiency coefficient of CSP, Indicates the upper limit of the power generation of CSP, Indicates the heat storage capacity of TES at and indicate the charging and discharging power of TES, and indicate the charging and discharging efficiency of TES, and indicate the power of the heat energy absorbed by TES from CHP and MF, Indicates the power of TES directly supplying heat to the heat load, and indicate the heat collection power and heat loss power of MF, and indicate the upper limits of the charging and discharging power of TES, and Indicates the identification bit for the charge and discharge of TES;

[0029] The input-output power balance constraint formula for the gas turbine model and the boiler model is:

[0030]

[0031]

[0032]

[0033]

[0034] In the formula: Indicates the heat generation power of GB at Indicates the gas consumption of GB, Indicates the conversion coefficient of heat generation per unit gas consumption of GB, Indicates the upper limit of the heat generation power of GB, and respectively represent the power generation power and heat generation power of CHP at time Indicates the gas consumption of CHP, and represent the power generation and heat generation efficiency coefficients of CHP per unit gas consumption, Indicates the heat power directly provided by CHP to the heat load, and represent the upper limits of the power generation and heat generation powers of CHP, and represent the upper limits of the powers provided by CHP to TES and the heat load;

[0035] The expression of the second objective function is:

[0036]

[0037]

[0038] where: is the daily comprehensive benefit of the integrated energy system, and represent the purchase and sale electricity income from the shared energy storage station and the income from selling energy to the producer - consumer alliance, and and represent the required natural gas cost, the operation and maintenance costs of each device, and the curtailment of wind and solar costs, represents the cost coefficient of purchasing unit volume of natural gas, and are the curtailment of wind and solar cost coefficients, and represent the charge - discharge energy cost coefficients of ESS and TES, represents the power generation cost coefficient of CSP, and are the electricity and heat prices set by the integrated energy system for different producer - consumers, and represent the lower and upper limits of the electricity selling price set by the integrated energy system, and represent the lower and upper limits of the heat selling price set by the integrated energy system, and are the average value constraints of the electricity and heat selling prices of the integrated energy system.

[0039] In a possible implementation manner, the electro - thermal load constraint formula of the producer - consumer alliance is:

[0040]

[0041]

[0042]

[0043] In the formula: represents a member at the predicted power of the electric energy load, represents the predicted power of the rooftop photovoltaic, , represents the reducible electric load and the shiftable electric load, represents the P2P electric energy sharing load with other members, represents the predicted power of the thermal energy load, , represents the reducible thermal load and the shiftable thermal load, , represents the upper limits of the reducible electric load and the shiftable electric load, represents the maximum P2P electric energy sharing power;

[0044] The expression of the third objective function is:

[0045]

[0046]

[0047] In the formula: represents the comprehensive cost of the prosumer alliance, , represent the cost of purchasing electric energy from the integrated energy system and the cost of electric energy demand response, , represent the cost of purchasing thermal energy from the integrated energy system and the cost of thermal energy demand response, , , , respectively represent the reduction cost coefficient and the transfer cost coefficient of the electric and thermal loads, is the trading cost of electric energy sharing among members, , respectively represent the alliance member and the member 's trading electricity price and trading power, represents at the moment the member and the member the electricity price of shared electric energy between them, , represent the upper and lower limits of the shared electric energy electricity price.

[0048] In a possible implementation, the prosumers in the prosumer alliance model are formed through cooperation after Nash negotiation. After solving the three-layer game model to obtain the scheduling result of the integrated energy system, it further includes:

[0049] Converting the scheduling result of the prosumer alliance in the scheduling result into minimizing the alliance cost and distributing the alliance cooperation benefits.

[0050] In a possible implementation, constructing the three-layer game model based on the shared energy storage model, the energy system model, and the prosumer alliance model includes:

[0051] Taking the shared energy storage model as the leader layer of the three-layer game model;

[0052] Taking the energy system model as the first follower layer of the three-layer game model;

[0053] Taking the prosumer model as the second follower layer of the three-layer game model.

[0054] In a possible implementation, solving the three-layer game model to obtain the scheduling result of the integrated energy system includes:

[0055] Solving the three-layer game model based on the particle swarm optimization algorithm to obtain the scheduling result of the integrated energy system.

[0056] On the other hand, the present invention also provides a scheduling device for an integrated energy system based on multi-layer game, including:

[0057] A model construction module, configured to construct a shared energy storage model, an energy system model, and a prosumer model. The shared energy storage model includes a first power constraint and a first objective function constructed based on maximizing the daily benefit of the shared energy storage system. The energy system model includes a second power constraint and a second objective function constructed based on maximizing the daily benefit of the energy system. The prosumer alliance model includes an electric and thermal load constraint and a third objective function constructed based on minimizing the cost of the prosumer alliance;

[0058] A three-layer game model construction module, configured to construct a three-layer game model based on the shared energy storage model, the energy system model, and the prosumer alliance model;

[0059] A scheduling result acquisition module, configured to solve the three-layer game model to obtain the scheduling result of the integrated energy system.

[0060] On the other hand, the present invention also provides an electronic device, including a memory and a processor, wherein,

[0061] The memory is used to store programs;

[0062] The processor, coupled to the memory, is configured to execute the program stored in the memory to implement the steps in the scheduling method of a multi-layer game-based integrated energy system described in any of the above implementation manners.

[0063] On the other hand, the present invention also provides a computer-readable storage medium for storing computer-readable programs or instructions, and when the programs or instructions are executed by a processor, they can implement the steps in the scheduling method of a multi-layer game-based integrated energy system described in any of the above implementation manners.

[0064] The beneficial effects of the present invention are as follows: The scheduling method of a multi-layer game-based integrated energy system provided by the present invention first constructs a shared energy storage model, an energy system model, and a prosumer model. The shared energy storage model includes a first power constraint and a first objective function constructed based on maximizing the daily benefit of the shared energy storage system. The energy system model includes a second power constraint and a second objective function constructed based on maximizing the daily benefit of the energy system. The prosumer alliance model includes an electric and thermal load constraint and a third objective function constructed based on minimizing the cost of the prosumer alliance. Then, a three-layer game model is constructed based on the shared energy storage model, the energy system model, and the prosumer alliance model. By constructing the three-layer game model, the interest distribution among the shared energy storage system, the integrated energy system, and the prosumer alliance is balanced to reach an equilibrium point. Finally, the three-layer game model is solved to obtain the scheduling result of the integrated energy system. The present invention constructs a three-layer game model for the shared energy storage system, the integrated energy system, and the prosumer alliance, thereby balancing the interests of the three parties and solving the problem of unbalanced interest distribution among individual or multiple equal-level collaborative optimizations of the integrated energy system. Description of the Drawings

[0065] Figure 1 It is a structural method flowchart of an embodiment of the scheduling method of a multi-layer game-based integrated energy system provided by the present invention;

[0066] Figure 2 It is a schematic diagram of the energy flow in the shared energy storage station - integrated energy system - prosumer alliance provided by the present invention;

[0067] Figure 3 It is a schematic diagram of the three-level game framework of an embodiment of the scheduling method of a multi-layer game-based integrated energy system provided by the present invention;

[0068] Figure 4 It is a schematic diagram of the Nash bargaining part of an embodiment of the scheduling method of a multi-layer game-based integrated energy system provided by the present invention;

[0069] Figure 5Schematic diagram of the input power requirements of wind, light, and solar tower for heat collection in the energy system in an embodiment of a scheduling method for an integrated energy system based on multi - layer game provided by the present invention;

[0070] Figure 6 Schematic diagram of the input power of the rooftop PV of prosumer 2 and the demand for electric - heat load in an embodiment of a scheduling method for an integrated energy system based on multi - layer game provided by the present invention;

[0071] Figure 7 Schematic diagram of the input power of the rooftop PV of prosumer 3 and the demand for electric - heat load in an embodiment of a scheduling method for an integrated energy system based on multi - layer game provided by the present invention;

[0072] Figure 8 Schematic diagram of the input power of the rooftop PV of prosumer 3 and the demand for electric - heat load in an embodiment of a scheduling method for an integrated energy system based on multi - layer game provided by the present invention;

[0073] Figure 9 Schematic diagram of the optimal scheduling result of the shared energy storage station in scenario 1 of an embodiment of a scheduling method for an integrated energy system based on multi - layer game provided by the present invention;

[0074] Figure 10 Schematic diagram of the optimal scheduling result of the integrated energy system in scenario 1 of an embodiment of a scheduling method for an integrated energy system based on multi - layer game provided by the present invention;

[0075] Figure 11 Schematic diagram of the optimal scheduling result of the prosumer alliance in scenario 1 of an embodiment of a scheduling method for an integrated energy system based on multi - layer game provided by the present invention;

[0076] Figure 12 Schematic diagram of the optimal scheduling result of the shared energy storage station in scenario 2 of an embodiment of a scheduling method for an integrated energy system based on multi - layer game provided by the present invention;

[0077] Figure 13 Schematic diagram of the optimal scheduling result of the integrated energy system in scenario 2 of an embodiment of a scheduling method for an integrated energy system based on multi - layer game provided by the present invention;

[0078] Figure 14 Schematic diagram of the optimal scheduling result of the prosumer alliance in scenario 2 of an embodiment of a scheduling method for an integrated energy system based on multi - layer game provided by the present invention;

[0079] Figure 15 Schematic diagram of the optimal scheduling result of the shared energy storage station in scenario 3 of an embodiment of a scheduling method for an integrated energy system based on multi - layer game provided by the present invention;

[0080] Figure 16 Schematic diagram of the optimal scheduling result of the integrated energy system under Scenario 3 of an embodiment of a scheduling method for an integrated energy system based on multi - layer game provided by the present invention;

[0081] Figure 17 Schematic diagram of the optimal scheduling result of the prosumer alliance under Scenario 3 of an embodiment of a scheduling method for an integrated energy system based on multi - layer game provided by the present invention;

[0082] Figure 18 Schematic diagram of the optimal scheduling result of the shared energy storage station under Scenario 4 of an embodiment of a scheduling method for an integrated energy system based on multi - layer game provided by the present invention;

[0083] Figure 19 Schematic diagram of the optimal scheduling result of the integrated energy system under Scenario 4 of an embodiment of a scheduling method for an integrated energy system based on multi - layer game provided by the present invention;

[0084] Figure 20 Schematic diagram of the optimal scheduling result of the prosumer alliance under Scenario 4 of an embodiment of a scheduling method for an integrated energy system based on multi - layer game provided by the present invention;

[0085] Figure 21 Schematic diagram of the P2P electric energy sharing result between prosumers in an embodiment of a scheduling method for an integrated energy system based on multi - layer game provided by the present invention;

[0086] Figure 22 Schematic diagram of the interest distribution after electric energy sharing between prosumers in an embodiment of a scheduling method for an integrated energy system based on multi - layer game provided by the present invention;

[0087] Figure 23 Schematic diagram of the process of an embodiment of a scheduling device for an integrated energy system based on multi - layer game provided by the present invention;

[0088] Figure 24 Schematic diagram of the structure of an embodiment of the electronic device provided by the present invention. Detailed implementation manners

[0089] The following combines the drawings to specifically describe the preferred embodiments of the present invention. Among them, the drawings constitute a part of this application and are used together with the embodiments of the present invention to explain the principle of the present invention, and are not used to limit the scope of the present invention.

[0090] Before presenting the embodiments, the following terms are explained first.

[0091] The Stackelberg game is a dynamic game model proposed by the German economist Heinrich Freiherr von Stackelberg in 1934. This model is mainly used to analyze the competitive behaviors in oligopoly markets, especially in the presence of a leader and followers. In the Stackelberg game, it is assumed that there are two firms in the market. One firm (the leader) first determines its output, and the other firm (the follower) decides its output after observing the leader's output. When making the output decision, the leader will consider the follower's reaction. Therefore, the leader's decision is based on the anticipation of the follower's reaction.

[0092] The present invention provides a scheduling method and device for an integrated energy system based on multi-layer games, which will be described separately below.

[0093] Figure 1 It is a schematic flowchart of an embodiment of the scheduling method for an integrated energy system based on multi-layer games provided by the present invention. As Figure 1 shown, the scheduling method for an integrated energy system based on multi-layer games includes:

[0094] S101. Construct a shared energy storage model, an energy system model, and a prosumer model. The shared energy storage model includes a first power constraint and a first objective function constructed to maximize the daily benefit of the shared energy storage system. The energy system model includes a second power constraint and a second objective function constructed to maximize the daily benefit of the energy system. The prosumer alliance model includes an electric and thermal load constraint and a third objective function constructed to minimize the cost of the prosumer alliance;

[0095] S102. Construct a three-layer game model based on the shared energy storage model, the energy system model, and the prosumer alliance model;

[0096] S103. Solve the three-layer game model to obtain the scheduling result of the integrated energy system.

[0097] Compared with the prior art, a scheduling method for an integrated energy system based on multi-layer game provided in this embodiment first constructs a shared energy storage model, an energy system model, and a prosumer model. The shared energy storage model includes a first power constraint and a first objective function constructed based on maximizing the daily benefit of the shared energy storage system. The energy system model includes a second power constraint and a second objective function constructed based on maximizing the daily benefit of the energy system. The prosumer alliance model includes an electric and thermal load constraint and a third objective function constructed based on minimizing the cost of the prosumer alliance. Then, a three-layer game model is constructed based on the shared energy storage model, the energy system model, and the prosumer alliance model. By constructing the three-layer game model, the interest distribution among the shared energy storage system, the integrated energy system, and the prosumer alliance is balanced to reach an equilibrium point. Finally, the three-layer game model is solved to obtain the scheduling result of the integrated energy system. The present invention constructs a three-layer game model for the shared energy storage system, the integrated energy system, and the prosumer alliance, thereby balancing the interests of the three parties and solving the problem of unbalanced interest distribution among individual or multiple equal-level collaborative optimization of the integrated energy system's various parties.

[0098] In some embodiments of the present invention, the expression of the first power constraint is:

[0099]

[0100] In the formula, represents the capacity of the shared energy storage station at time, , respectively represent the charging and discharging power of the shared energy storage station at , respectively represent the charging and discharging efficiencies of the shared energy storage station, , respectively represent the lower and upper limits of the capacity of the shared energy storage station, , respectively represent the lower and upper limits of the charging and discharging power of the shared energy storage station, , respectively represent the charging and discharging flag bits of the shared energy storage station at

[0101] In a specific embodiment of the present invention, the parameters of the shared energy storage system are shown in Table 1 below.

[0102] Table 1: Parameters of the shared energy storage system

[0103]

[0104] The expression of the first objective function is:

[0105]

[0106]

[0107] In the formula, is the daily comprehensive benefit of the shared energy storage station, and respectively represent the revenues from the transactions between the shared energy storage station and the power grid and the integrated energy system at time represents the self-charging, discharging, operation and maintenance costs of the shared energy storage station, and and and respectively represent the purchased and sold electric powers of the shared energy storage station to / from the power grid and their power upper limits, and respectively represent the control quantities of 0 / 1 for the purchased and sold electric powers of the shared energy storage station to / from the power grid, and respectively represent the purchased and sold electric powers of the integrated energy system to / from the shared energy storage station, represents the cost coefficient for each charge and discharge of the shared energy storage station, and respectively represent the purchased and sold electricity prices announced by the power grid at time and respectively represent the purchased and sold electricity prices set and announced by the shared energy storage station to the integrated energy system, and respectively represent the lower and upper limits of the electricity purchase price set by the shared energy storage station to the integrated energy system at time and respectively represent the lower and upper limits of the electricity purchase price set by the shared energy storage station to the integrated energy system at time. To prevent the shared energy storage station from deliberately increasing the selling electricity price to the integrated energy system or depressing the electricity purchase price from the integrated energy system for profit, it is necessary to add a constraint on the average value of the purchased and sold electricity prices of the shared energy storage station to the integrated energy system and ,

[0108] In a specific embodiment of the present invention, the time-of-use electricity price announced by the power grid is shown in Table 2.

[0109] Table 2: Time-of-Use Electricity Price Table of the Power Grid

[0110]

[0111] In some embodiments of the present invention, the energy system model includes a clean model and a gas model. The clean model includes a wind-solar model and a concentrating power plant model. The gas model includes a gas turbine model and a boiler model. The second power constraint includes the input-output power balance constraint of the wind-solar model, the power generation output constraint of the concentrating power plant model, and the input-output power balance constraints of the gas turbine model and the boiler model.

[0112] The formula for the input-output power balance constraint of the wind-solar model is:

[0113]

[0114]

[0115]

[0116]

[0117] Where: 、 、 respectively represent the predicted wind power generation, the actual wind power generation, and the curtailed wind power. 、 、 respectively represent the predicted PV power generation, the actual PV power generation, and the curtailed PV power. represents the short-term prediction error of the wind power generation. represents the short-term prediction error of the PV power generation. represents the normal distribution variance of the predicted wind power generation. represents the normal distribution variance of the predicted PV power generation. represents the capacity of the battery at time. 、 respectively represent the charging and discharging powers of the battery. 、 respectively represent the charging and discharging efficiencies of the battery. 、 represent the lower and upper limits of the battery capacity. 、 represent the lower and upper limits of the charging and discharging powers of the battery. 、 represent the charging and discharging identification bits of the battery.

[0118] The expression for the power generation output constraint of the concentrating power plant model is:

[0119]

[0120]

[0121]

[0122] In the formula: represents the power generation power of CSP at time, and represent the thermal power provided by MF and TES to ST, represents the power generation efficiency coefficient of CSP, represents the upper limit of CSP power generation power, represents the heat storage capacity of TES at and represent the charging and discharging power of TES, and represent the charging and discharging efficiency of TES, and represent the power of the heat energy absorbed by TES from CHP and MF, represents the heat supply power of TES directly to the heat load, and represent the heat collection power and heat loss power of MF, and represent the upper limits of the charging and discharging powers of TES, and represent the charging and discharging flag bits of TES; The parameters of each sub-model in the integrated energy system are shown in Table 3.

[0123] Table 3: Parameters of each sub-model in the integrated energy system

[0124]

[0125] The input-output power balance constraint formula of the gas turbine model and the boiler model is:

[0126]

[0127]

[0128]

[0129]

[0130] In the formula: represents the heat generation power of GB at represents the gas consumption of GB, represents the conversion coefficient of heat generation per unit gas consumption of GB, represents the upper limit of GB heat generation power, and respectively represent The power generation power and heat generation power of the CHP at a certain moment Indicates the gas consumption of the CHP 、 Indicates the power generation and heat generation efficiency coefficients of the CHP per unit gas consumption Indicates the heat power directly provided by the CHP to the heat load 、 Indicates the upper limits of the power generation and heat generation powers of the CHP 、 Indicates the upper limits of the powers provided by the CHP to the TES and the heat load;

[0131] The expression of the second objective function is:

[0132]

[0133]

[0134] In the formula: Is the comprehensive benefit of the integrated energy system within a day 、 Indicates the revenue from buying and selling electricity with the shared energy storage station and the revenue from selling energy to the producer - consumer alliance 、 、 Indicates the required natural gas cost, the operation and maintenance costs of each device, and the curtailment cost of wind and solar power Indicates the cost coefficient of purchasing unit volume of natural gas 、 Are the curtailment cost coefficients of wind and solar power 、 Indicates the charge - discharge energy cost coefficients of the ESS and TES Indicates the power generation cost coefficient of the CSP 、 Are the electricity and heat prices set by the integrated energy system for different producer - consumers 、 Indicates the lower and upper limits of the electricity selling price set by the integrated energy system 、 Indicates the lower and upper limits of the heat selling price set by the integrated energy system 、 Is the average value constraint of the electricity and heat selling prices of the integrated energy system

[0135] In some embodiments of the present invention, the electric and heat load constraint formula of the producer - consumer alliance is: (1)

[0136] (2)

[0137] (3)

[0138] In the formula: represents a member at the predicted power of the electricity load at a certain moment, represents the predicted power of the rooftop PV, , represents the reducible electricity load and the shiftable electricity load, represents the P2P electricity sharing load with other members, represents the predicted power of the heat load, , represents the reducible heat load and the shiftable heat load, , represents the upper limits of the reducible electricity load and the shiftable electricity load, represents the maximum P2P electricity sharing power;

[0139] The expression of the third objective function is:

[0140] (4)

[0141] (5)

[0142] In the formula: represents the comprehensive cost of the prosumer alliance, , represent the electricity purchase cost from the integrated energy system and the electricity demand response cost, , represent the heat purchase cost from the integrated energy system and the heat demand response cost, , , , respectively represent the reduction cost coefficients and transfer cost coefficients of the electricity and heat loads, is the electricity sharing trade cost between members, , respectively represent the alliance member and member 's trading electricity price and trading power, represents at the moment when member and member share the electricity price between them, , represent the upper and lower limits of the shared electricity price.

[0143] It should be noted that since this Nash bargaining model is a non-convex and non-linear optimization problem and is difficult to solve directly, it is necessary to convert this model into a more easily solvable alliance cost minimization and cooperative revenue distribution Two sub - problems are solved in sequence. In some embodiments of the present invention, the producers - consumers in the producers - consumers alliance model are formed through cooperation after Nash negotiation. After solving the three - layer game model to obtain the scheduling result of the integrated energy system, it further includes:

[0144] Converting the scheduling result of the producers - consumers alliance in the scheduling result into minimizing the alliance cost and allocating the alliance cooperation revenue.

[0145] In a specific embodiment of the present invention, the Nash bargaining solution model among the members within the producers - consumers alliance is expressed by the following formula: (6)

[0146] (7)

[0147] In the formula: is the comprehensive energy purchase cost when the alliance members do not participate in Nash negotiation within a day, that is, the breakdown point of negotiation cooperation. is the comprehensive energy purchase cost when the alliance members participate in Nash negotiation and do not consider the payment for shared electric energy part, is the difference in comprehensive energy purchase cost before and after the alliance members participate in electric energy sharing. The relevant parameters of the producers - consumers alliance are shown in Table 4.

[0148] Table 4 Relevant parameters of the producers - consumers alliance

[0149]

[0150] However, since this Nash negotiation model is a non - convex non - linear optimization problem and it is difficult to directly solve it, it is necessary to convert this model into two sub - problems of minimizing the alliance cost and allocating the cooperation revenue and solve them in sequence.

[0151] Set as the energy purchase cost when not considering the payment for shared electric energy after alliance cooperation , then the sub - problem minimizing the alliance cost can be expressed by the following formula:

[0152]

[0153] Set as the optimal solution obtained in the sub - problem , then the sub - problem allocating the cooperation revenue can be expressed by the following formula:

[0154]

[0155] In some embodiments of the present invention, the three - layer game model constructed based on the shared energy storage model, the energy system model, and the prosumer alliance model includes:

[0156] Taking the shared energy storage model as the leader of the three - layer game model;

[0157] Taking the energy system model as the first follower of the three - layer game model;

[0158] Taking the prosumer model as the second follower of the three - layer game model.

[0159] In some embodiments of the present invention, the solving of the three - layer game model to obtain the scheduling result of the integrated energy system includes:

[0160] Solving the three - layer game model based on the particle swarm algorithm to obtain the scheduling result of the integrated energy system.

[0161] The present invention introduces combined heat and power generation and a concentrating solar power plant into the integrated energy system, and uses the flexibility of combined heat and power generation to make up for the deficiencies of wind turbine generators, photovoltaic generator sets, and concentrating solar power plant units in terms of electricity and heat load demands; in addition, the heat energy storage device in the concentrating solar power plant is used to store the surplus heat energy, and it is charged into the steam turbine during the peak electricity load period to be converted into electrical energy. This enables the integrated energy system to not only meet the load demand, but also greatly improve the utilization rate of primary energy such as natural gas and coal.

[0162] Regarding the load - side demand problem of prosumers in the integrated energy system, this technical solution takes the alliance composed of multiple prosumers as a whole to participate in the master - slave game in the vertical direction, and uses its integrated energy demand response strategy to minimize the energy purchase cost of the prosumer alliance; in addition, this technology embeds the electricity sharing among prosumers as a Nash bargaining cooperative game into the third - level game subject. This enables each prosumer individual to reduce its own energy purchase cost through two methods: the energy demand restriction of the prosumer alliance and the Nash bargaining cooperation with other prosumers.

[0163] In the specific embodiments of the present invention, as Figure 5 、 Figure 6 、 Figure 7 、 Figure 8 shown are the schematic diagrams of the input / demand of each electricity and heat power, and as Figure 9 、 Figure 10 、 Figure 11 shown are the schematic diagrams of the optimal scheduling results of the shared energy storage station - integrated energy system - prosumer alliance at each time period under Scenario 1, and as Figure 12 、 Figure 13 、 Figure 14 shown are the schematic diagrams of the optimal scheduling results of the shared energy storage station - integrated energy system - prosumer alliance at each time period under Scenario 2, and as Figure 15 、 Figure 16 shown are...Figure 17 The figure shows the schematic diagram of the optimal scheduling results of the shared energy storage station - integrated energy system - prosumer alliance in each time period under Scenario 3. As Figure 18 、 Figure 19 、 Figure 20 The figure shows the schematic diagram of the optimal scheduling results of the shared energy storage station - integrated energy system - prosumer alliance in each time period under Scenario 4 ( Figure 9 ), as Figure 21 The figure shows the schematic diagram of the P2P electricity sharing results among prosumers. As Figure 22 The figure shows the schematic diagram of the benefit distribution after electricity sharing among prosumers. The comparison table of the costs of each subject after collaborative optimization scheduling under different scenarios (Table 5), and the comparison table of the costs of each prosumer before and after cooperation (Table 6).

[0164] Table 5 Comparison table of the cost results of each subject after collaborative optimization scheduling under different strategy scenarios

[0165]

[0166] Table 6: Comparison table of the costs of each prosumer before and after cooperation

[0167]

[0168] Comparison of the optimal scheduling results of the shared energy storage station - integrated energy system - prosumer alliance under different scenarios. Compared with Scenario 1, in Scenario 2, the prosumers reach a cooperation alliance, and theoretically, a more flexible energy scheduling strategy can be provided for each level of subject. In Figure 9 , due to the dual influence of the time-of-use electricity price of the power grid and the energy purchase and sale strategy of the integrated energy system, the shared energy storage station can purchase electricity as a reserve when there is sufficient surplus energy in the integrated energy system and sell it to the power grid during peak electricity periods (11:00 - 14:00; 18:00 - 20:00). Comparing Figure 10 and Figure 13 , comparing Figure 11 and Figure 14 , although there is electricity sharing among prosumers, the total energy consumption demand remains unchanged. Compared with Scenario 2, in Scenario 3, the energy demand response of prosumers is considered, and a more flexible energy consumption strategy is provided. Comparing Figure 12 and Figure 15 , the shared energy storage station no longer provides electricity to the integrated energy system during the peak electricity period (18:00 - 20:00) and directly sells the surplus energy to the power grid. Comparing Figure 13 and Figure 16 , comparing Figure 14 and Figure 17, there are obvious changes in the energy consumption of the producer-consumer alliance. Among them, the period with the largest reduction in electricity demand is 647.16 kw from 19:00 to 20:00, and the period with the largest reduction in heat demand is 294.696 KW from 13:00 to 14:00. In addition, the maximum increase in electricity demand is 260.14 kw (from 23:00 to 24:00), and it is necessary to further explore the impact of adding electricity sharing among producers and consumers on the energy scheduling results.

[0169] Compare Figure 15 and Figure 18 , since the integrated energy system needs to meet the further decline in electricity of the producer-consumer alliance, the maximum electricity purchase from the shared energy storage station by the integrated energy system is reduced by 149.51 kw (from 1:00 to 2:00). Compare Figure 16 and Figure 19 , Compare Figure 17 and Figure 20 , the maximum reduction in electricity demand of the producer-consumer alliance is 166.658 kw (from 13:00 to 14:00), and the maximum increase in electricity demand is 263.17 kw (from 9:00 to 10:00), verifying the effectiveness of electricity sharing among producers and consumers in reducing their own energy consumption costs. In addition, since the electricity demand of the producer-consumer alliance decreased by 167.658 kw from 13:00 to 14:00, the power generation output of CSP decreased from the original 250 kw to 163.782 kw. At this time, the electricity output of CHP decreased from 128.022 kw to 47.582 kw, and the heat output decreased from 192.034 kw to 71.3726 kw. It is worth noting that compared with Scenario 1, the daily natural gas loss of the integrated energy system in Scenario 4 decreased by 9.32%.

[0170] Observing Table 5, it can be seen that the income of the shared energy storage station has decreased significantly. This is because of the indirect influence of the lowest-level producers and consumers by changing their energy consumption strategies. However, due to its highest status, it can still maintain high economic efficiency. But compared with Scenario 1, the income of the integrated energy system in Scenario 4 has increased by 604.931 instead. This is because the producers and consumers have changed their own energy consumption strategies, reducing the comprehensive cost of the producer-consumer alliance by 4171.938 while the integrated energy system has gradually reduced the electricity purchase volume during the high-price period set by the shared energy storage station. Observing Table 6, it can be seen that regardless of whether the demand response of producers and consumers is considered, their comprehensive cost after cooperation is always lower than the original energy purchase cost before cooperation. But when comparing Scenario 4 and Scenario 1 in Table 5, the comprehensive energy purchase cost of the producer-consumer alliance has decreased by 12.16%.

[0171] Observe Figure 21 and Figure 22, the electricity sharing price between producers 1 and 2 fluctuates within the range of [0.2195 - 0.2715], the electricity sharing price between producers 1 and 3 fluctuates within the range of [0.2083 - 0.4832], and the electricity sharing price between producers 2 and 3 fluctuates within the range of [0.2041 - 0.4011], meeting the set constraint intervals. Observe Figure 10 , the algorithm converges after 38 iterations of solution. Producer 1 converges from the initial -261.995 yuan to -868.734 yuan, producer 2 converges from the initial -470.849 yuan to -980.856 yuan, and producer 3 converges from the initial 1830.93 yuan to 1848.71 yuan. Combining Tables 5 and 6, the costs of producers 1 and 2 are significantly reduced. Although the cost increases after adding the cooperation of producer 3, this part will be compensated through reallocation of the bargaining part to ensure that producer 3 will not damage its own interests due to cooperation. The total energy purchase cost of the producer alliance is reduced by 12.16%. It is verified that producers in a monopolistic position in the master-slave game framework can seek cooperation by realizing electricity sharing among members and adjust their energy consumption strategies using their own energy demand response, so as to further reduce the energy purchase cost when they are in a monopolistic position.

[0172] To better implement a scheduling method for an integrated energy system based on multi-layer game in an embodiment of the present invention, correspondingly, on the basis of a scheduling method for an integrated energy system based on multi-layer game, as Figure 23 shown, an embodiment of the present invention further provides a scheduling device for an integrated energy system based on multi-layer game. A scheduling device 2300 for an integrated energy system based on multi-layer game includes:

[0173] A model construction module 2301, configured to construct a shared energy storage model, an energy system model, and a producer model. The shared energy storage model includes a first power constraint and a first objective function constructed with the maximum daily benefit of the shared energy storage system. The energy system model includes a second power constraint and a second objective function constructed with the maximum daily benefit of the energy system. The producer alliance model includes an electric and thermal load constraint and a third objective function constructed with the minimum cost of the producer alliance;

[0174] A three-layer game model construction module 2302, configured to construct a three-layer game model based on the shared energy storage model, the energy system model, and the producer alliance model;

[0175] A scheduling result acquisition module 2303, configured to solve the three-layer game model to obtain the scheduling result of the integrated energy system.

[0176] The scheduling device 2300 of an integrated energy system based on multi - layer game provided by the above - mentioned embodiment can implement the technical solutions described in the embodiment of the scheduling method of an integrated energy system based on multi - layer game. The specific implementation principles of the above - mentioned modules or units can be referred to the corresponding content in the embodiment of the scheduling method of an integrated energy system based on multi - layer game, which will not be elaborated here.

[0177] As Figure 24 shown, the present invention also correspondingly provides an electronic device 2400. The electronic device 2400 includes a processor 2401, a memory 2402, and a display 2403. Figure 24 Only some components of the electronic device 2400 are shown, but it should be understood that it is not required to implement all the shown components, and more or fewer components can be alternatively implemented.

[0178] In some embodiments, the processor 2401 can be a central processing unit (CPU), a microprocessor, or other data - processing chips, and is used to run the program code stored in the memory 2402 or process data, such as the scheduling method of an integrated energy system based on multi - layer game in the present invention.

[0179] In some embodiments, the processor 2401 can be a single server or a server group. The server group can be centralized or distributed. In some embodiments, the processor 2401 can be local or remote. In some embodiments, the processor 2401 can be implemented on a cloud platform. In some embodiments, the cloud platform can include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an internal cloud, a multi - cloud, etc., or any combination of the above.

[0180] In some embodiments, the memory 2402 can be an internal storage unit of the electronic device 2400, such as the hard disk or memory of the electronic device 2400. In some other embodiments, the memory 2402 can also be an external storage device of the electronic device 2400, such as a plug - in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc., equipped on the electronic device 2400.

[0181] Furthermore, the memory 2402 can also include both the internal storage unit and the external storage device of the electronic device 2400. The memory 2402 is used to store the application software installed in the electronic device 2400 and various types of data.

[0182] The display 2403 can be an LED display, a liquid crystal display, a touch liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, etc. in some embodiments. The display 2403 is used to display information in the electronic device 2400 and to display a visual user interface. The components 2401-2403 of the electronic device 2400 communicate with each other via a system bus.

[0183] In one embodiment, when the processor 2401 executes a scheduling program of a multi-layer game-based integrated energy system in the memory 2402, the following steps can be implemented:

[0184] Construct a shared energy storage model, an energy system model, and a prosumer model. The shared energy storage model includes a first power constraint and a first objective function constructed to maximize the daily benefit of the shared energy storage system. The energy system model includes a second power constraint and a second objective function constructed to maximize the daily benefit of the energy system. The prosumer alliance model includes an electric and thermal load constraint and a third objective function constructed to minimize the cost of the prosumer alliance.

[0185] Construct a three-layer game model based on the shared energy storage model, the energy system model, and the prosumer alliance model.

[0186] Solve the three-layer game model to obtain the scheduling result of the integrated energy system.

[0187] It should be understood that when the processor 2401 executes a scheduling program of a multi-layer game-based integrated energy system in the memory 2402, in addition to the above functions, other functions can also be implemented. For details, refer to the description of the corresponding method embodiments above.

[0188] Furthermore, the type of the electronic device 2400 mentioned in the embodiments of the present invention is not specifically limited. The electronic device 2400 can be a portable electronic device such as a mobile phone, a tablet computer, a personal digital assistant (PDA), a wearable device, a laptop, etc. Exemplary embodiments of the portable electronic device include, but are not limited to, portable electronic devices running IOS, android, microsoft, or other operating systems. The above portable electronic devices can also be other portable electronic devices, such as a laptop with a touch-sensitive surface (e.g., a touch panel). It should also be understood that in some other embodiments of the present invention, the electronic device 2400 can also be a non-portable electronic device, but a desktop computer with a touch-sensitive surface (e.g., a touch panel).

[0189] Those skilled in the art can understand that all or part of the processes of implementing the methods of the above embodiments can be completed by instructing relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium. Among them, the computer-readable storage medium is a magnetic disk, an optical disk, a read-only memory or a random access memory, etc.

[0190] As mentioned above, the above are only the preferred specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention.

Claims

1. A scheduling method for an integrated energy system based on multi-layer game, characterized in that: include: Constructing a shared energy storage model, an energy system model, and a producer-seller model. The shared energy storage model includes a first power constraint and a first objective function constructed by maximizing the daily benefit of the shared energy storage system. The energy system model includes a second power constraint and a second objective function constructed by maximizing the daily benefit of the energy system. The producer-seller alliance model includes an electric and thermal load constraint and a third objective function constructed by minimizing the cost of the producer-seller alliance. Construct a three-layer game model based on the shared energy storage model, energy system model and producer-seller alliance model; Solve the three-layer game model and obtain the dispatch results of the integrated energy system; The expression of the first power constraint is: In the formula, Indicates that shared energy storage is The capacity of the moment, , Respectively Share the charging and discharging power of the energy storage station at all times. , They represent the charging and discharging efficiency of the shared energy storage station, , They represent the lower and upper limits of the shared energy storage station capacity, , They represent the lower and upper limits of the charging and discharging power of the shared energy storage station, respectively. , Respectively Share the charging and discharging identification position of the energy storage station at all times; The expression of the first objective function is: In the formula, To share the comprehensive benefits of energy storage stations within a day, , Respectively Always share the benefits of energy storage stations, power grids, and integrated energy system transactions. represents the charging, discharging and maintenance cost of the shared energy storage station itself, , , , They represent the power purchased and sold by the shared energy storage station to the grid and its upper limit, , They represent the control amount of the shared energy storage station purchasing and selling electricity to the power grid, which is 0 / 1. , They represent the power purchased and sold by the integrated energy system to the shared energy storage, Represents the cost coefficient of each charge and discharge of the shared energy storage station, , Respectively The electricity purchase and sale prices released by the power grid at the moment, , They represent the electricity purchase and sale prices formulated and released by the shared energy storage station to the integrated energy system, , Respectively The time-sharing energy storage station sets the lower and upper limits of the electricity purchase price for the integrated energy system. , Respectively The time-sharing energy storage station sets the lower and upper limits of the electricity purchase price to the integrated energy system; The energy system model includes a clean model and a gas model, the clean model includes a wind-solar model and a concentrated solar power station model, the gas model includes a gas turbine model and a boiler model, and the second power constraint includes an input-output power balance constraint of the wind-solar model, a power generation output constraint of the concentrated solar power station model, and an input-output power balance constraint of the gas turbine model and the boiler model; The input and output power balance constraint formula of the wind-solar model is: Where: , , They represent the predicted wind power generation, actual wind power generation and abandoned wind power, respectively. , , They represent the predicted photovoltaic power generation, actual photovoltaic power generation and abandoned power, respectively. represents the short-term forecast error of wind power generation, represents the short-term prediction error of photovoltaic power generation, represents the normal distribution variance of the predicted wind power generation, represents the normal distribution variance of the predicted photovoltaic power generation, Indicates that the battery is The capacity of the moment, , Respectively represent the charging and discharging power of the battery, , They represent the charging and discharging efficiency of the battery respectively. , Indicates the lower and upper limits of battery capacity. , Indicates the lower and upper limits of battery charging and discharging power. , Indicates the battery charge and discharge identification position; The expression of the power generation output constraint of the concentrated solar power station model is: Where: Indicates that CSP is Power generation at all times, , represents the thermal power provided by MF and TES to ST, represents the power generation efficiency coefficient of CSP, Indicates the upper limit of CSP power generation, express The heat storage of TES at the moment, , Indicates the TES charging and discharging power. , Indicates the charging and discharging efficiency of TES, , It indicates that the thermal energy absorbed by TES comes from the power of CHP and MF, Indicates the heating power directly supplied by TES to the heat load, , represents the MF heat collection power and heat loss power, , Indicates the upper limit of TES charging and discharging power. , Indicates the charging and discharging heat flag of TES; The input and output power balance constraint formulas of the gas turbine model and the boiler model are: Where: express The heat generation power of GB at the moment, Indicates the gas consumption in GB, Indicates the conversion coefficient of GB unit gas consumption and heat production, Indicates the upper limit of GB heat generation power, , Respectively The power generation and heat generation of CHP at the moment, Indicates the gas consumption of CHP, , It represents the efficiency coefficient of CHP unit gas consumption for electricity and heat production, It represents the thermal power provided by CHP directly to the thermal load, , Indicates the upper limit of the power of CHP to generate electricity and heat, , It represents the upper limit of the power provided by CHP to TES and thermal load; The expression of the second objective function is: Where: For the comprehensive benefits of the integrated energy system within a day, , Represents the revenue from the purchase and sale of electricity with the shared energy storage station and the revenue from the sale of energy to the producer-seller alliance. , , Indicates the required natural gas cost, equipment operation and maintenance cost, and wind and solar power abandonment cost. represents the cost coefficient of purchasing unit volume of natural gas, , is the cost coefficient of wind and solar power abandonment, , Indicates the energy cost coefficient of ESS and TES charging and discharging, represents the CSP power generation cost coefficient, , The electricity and heat prices set for different producers and sellers in the integrated energy system, , It indicates the lower and upper limits of the electricity price set by the integrated energy system. , It indicates the lower and upper limits of the heat selling price set by the integrated energy system. , To constrain the average price of electricity and heat energy sold in the integrated energy system; The electric heat load constraint formula of the producer-seller alliance is: Where: Indicates members exist The predicted power of the electric energy load at each moment, represents the predicted rooftop photovoltaic power, , Indicates that the electrical load can be reduced and the electrical load can be shifted. Indicates P2P power sharing load with other members, represents the predicted power of thermal load, , Indicates that heat load can be reduced and heat load can be shifted. , Indicates the upper limit of the load that can be reduced and the load that can be shifted. Indicates the maximum power of P2P power sharing; The expression of the third objective function is: Where: represents the comprehensive cost of the producer-seller alliance, , represents the cost of purchasing electricity from the integrated energy system and the cost of responding to electricity demand, , represents the cost of purchasing heat energy from the integrated energy system and the cost of responding to heat energy demand, , , , Represent the reduction cost coefficient and transfer cost coefficient of electricity and heat load respectively, To share the trade costs of electricity among members, , Represents alliance members With members The transaction price and transaction power of express Moment Member With members Shared electricity prices between , Indicates the upper and lower limits of the shared electricity price.

2. The scheduling method of the integrated energy system based on multi-layer game according to claim 1 is characterized in that: The producers and sellers in the producer-seller alliance model are formed through cooperation after Nash negotiation. After solving the three-layer game model and obtaining the dispatch result of the integrated energy system, it also includes: The scheduling result of the producer-seller alliance in the scheduling result is converted into the minimum alliance cost and the distribution of alliance cooperation benefits.

3. The scheduling method of the integrated energy system based on multi-layer game according to claim 1 is characterized in that: The three-layer game model is constructed based on the shared energy storage model, the energy system model and the producer-seller alliance model, including: Leadership with a three-tier game model based on a shared energy storage model; The energy system model is the first follower of the three-layer game model; The producer-seller model is the second follower of the three-level game model.

4. The scheduling method of the integrated energy system based on multi-layer game according to claim 1 is characterized in that: The three-layer game model is solved to obtain the dispatch result of the integrated energy system, including: The three-layer game model is solved based on the particle swarm algorithm to obtain the scheduling results of the integrated energy system.

5. A scheduling device for an integrated energy system based on multi-layer game, used to implement a scheduling method for an integrated energy system based on multi-layer game as described in any one of claims 1 to 4, characterized in that: include: A model building module, used to build a shared energy storage model, an energy system model and a prosumer model, wherein the shared energy storage model includes a first power constraint and a first objective function constructed by maximizing the daily benefit of the shared energy storage system, the energy system model includes a second power constraint and a second objective function constructed by maximizing the daily benefit of the energy system, and the prosumer alliance model includes an electric and thermal load constraint and a third objective function constructed by minimizing the cost of the prosumer alliance; A three-layer game model construction module, which is used to construct a three-layer game model based on a shared energy storage model, an energy system model, and a producer-seller alliance model; The scheduling result acquisition module is used to solve the three-layer game model and obtain the scheduling results of the integrated energy system.

6. An electronic device, characterized in that: comprising a memory and a processor, wherein: The memory is used to store programs; The processor is coupled to the memory and is used to execute the program stored in the memory to implement the steps in the scheduling method of an integrated energy system based on multi-layer game as described in any one of claims 1 to 4 above.

7. A computer-readable storage medium, characterized in that: Used to store computer-readable programs or instructions, which, when executed by a processor, can implement the steps in a scheduling method for an integrated energy system based on multi-layer game as described in any one of claims 1 to 4 above.

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