Scheduling method and device of integrated energy system based on multi-layer game

Abstract

The invention relates to a scheduling method and device of an integrated energy system based on a multi-layer game, and belongs to the technical field of power system energy scheduling, the method comprises the steps that a shared energy storage model, an energy system model and a producer model are constructed, the shared energy storage model comprises a first power constraint and a first objective function, and the energy system model comprises a second power constraint and a second objective function; the energy system model comprises a second power constraint and a second objective function, and the producer and marketing alliance model comprises an electric heating 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 producer alliance model; and solving the three-layer game model to obtain a scheduling result of the integrated energy system. According to the invention, the shared energy storage system, the integrated energy system and the producer alliance are used to construct a three-layer game model, so that the benefits of the three parties are balanced, and the problem of unbalanced benefit distribution of each subject caused by same-level collaborative optimization of a single subject or multiple subjects of the integrated energy system is solved.

Description

Technical Field

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

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

[0003] The integrated energy system can effectively cope with the output fluctuation of renewable energy by optimizing the dispatch of regional flexible resources through the complementarity of multiple energy sources, and its application has become an inevitable trend. Regarding the optimal dispatching problem of energy complementarity in the integrated energy system, since the actual operating conditions involve the coordinated dispatching of multiple parties, the elements of internal output optimization and participation in the coordinated optimization dispatching of external energy in the integrated energy system have become increasingly complex. In recent years, research has often considered this dispatching problem as a coordinated optimization problem of a single subject or multiple subjects of the same level. The model only includes the goal of its own benefits, and cannot provide better decision-making solutions in the optimal dispatching of the integrated energy system, which is at a disadvantage.

[0004] In summary, the existing technology lacks a scheduling method for an integrated energy system based on multi-layer game to coordinate various entities, thereby balancing and optimizing the interests of various entities. 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 to solve the problem of unbalanced benefit distribution among entities caused by the collaborative optimization of a single entity or multiple entities at the same level in the integrated energy system.

[0006] In order to solve the above problems, the present invention provides a scheduling method for an integrated energy system based on multi-layer game, comprising: 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; The three-layer game model is solved to obtain the dispatch results of the integrated energy system.

[0007] In a possible implementation manner, the expression of the first power constraint is:

[0008]

[0009] 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:

[0010]

[0011] 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.

[0012] 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 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:

[0013]

[0014]

[0015]

[0016] 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:

[0017]

[0018]

[0019] 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:

[0020]

[0021]

[0022]

[0023] 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:

[0024]

[0025] 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 ESS and TES charging and discharging energy cost coefficient, 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. , It is a constraint on the average price of electricity and heat energy sold in the integrated energy system.

[0026] In a possible implementation, the electric heat load constraint formula of the producer-seller alliance is:

[0027]

[0028]

[0029] 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 heat load reduction and heat load shifting. , 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:

[0030]

[0031] 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.

[0032] In a possible implementation, 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, the following is further included: 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.

[0033] In a possible implementation, 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.

[0034] In a possible implementation, solving the three-layer game model to obtain a dispatch result of the integrated energy system includes: The three-layer game model is solved based on the particle swarm algorithm to obtain the scheduling results of the integrated energy system.

[0035] On the other hand, the present invention also provides a scheduling device for an integrated energy system based on multi-layer game, comprising: 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.

[0036] On the other hand, the present invention also provides an electronic device, including 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 a scheduling method for an integrated energy system based on multi-layer game described in any one of the above implementations.

[0037] On the other hand, the present invention also provides a computer-readable storage medium for storing 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 described in any of the above-mentioned implementation methods.

[0038] The beneficial effect of the present invention is as follows: the present invention provides a scheduling method for an integrated energy system based on multi-layer game, firstly constructing a shared energy storage model, an energy system model and a producer-seller model, wherein the shared energy storage model includes a first power constraint and a first objective function constructed by maximizing the intraday 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 intraday benefit of the energy system, and 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, and then constructing a three-layer game model based on the shared energy storage model, the energy system model and the producer-seller alliance model, constructing a three-layer game model to balance the interest distribution of the shared energy storage system, the integrated energy system and the producer-seller alliance to reach a balance point, and finally 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 of the shared energy storage system, the integrated energy system and the producer-seller alliance, thereby balancing the interests of the three parties, and solves the problem of unbalanced interest distribution of each subject caused by the same-level collaborative optimization of a single subject or multiple subjects in the integrated energy system. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 A structural method flow chart of an embodiment of a scheduling method for an integrated energy system based on multi-layer game provided by the present invention; Figure 2 A schematic diagram of the energy flows in the shared energy storage station-integrated energy system-producer-seller alliance provided by the present invention; Figure 3 A schematic diagram of a three-level game framework of an embodiment of a scheduling method for an integrated energy system based on multi-layer game provided by the present invention; Figure 4 A schematic diagram of the Nash bargaining part of an embodiment of a scheduling method for an integrated energy system based on multi-layer game provided by the present invention; Figure 5 A schematic diagram of the input power requirements of wind, light and concentrated light towers of an energy system in one embodiment of a scheduling method of a comprehensive energy system based on multi-layer game provided by the present invention; Figure 6 A schematic diagram of the photovoltaic input power and electric heat load demand of the roof of producer and seller 2 in one embodiment of a scheduling method of an integrated energy system based on multi-layer game provided by the present invention; Figure 7 A schematic diagram of the photovoltaic input power and electric heat load demand of the roof of producer and seller 3 in one embodiment of a scheduling method of an integrated energy system based on multi-layer game provided by the present invention; Figure 8 A schematic diagram of the photovoltaic input power and electric heat load demand of the roof of producer and seller 3 in one embodiment of a scheduling method of an integrated energy system based on multi-layer game provided by the present invention; Fig. 9 A schematic diagram of the optimal scheduling result of a shared energy storage station under scenario 1 of an embodiment of a scheduling method for an integrated energy system based on multi-layer game provided by the present invention; Fig.10 A schematic diagram of the optimal scheduling result of the integrated energy system under scenario 1 of an embodiment of a scheduling method for an integrated energy system based on multi-layer game provided by the present invention; Fig.11 A schematic diagram of the optimal scheduling result of the producer-seller alliance under scenario 1 of an embodiment of a scheduling method for an integrated energy system based on multi-layer game provided by the present invention; Fig.12 A schematic diagram of the optimal scheduling result of a shared energy storage station under scenario 2 of an embodiment of a scheduling method for an integrated energy system based on multi-layer game provided by the present invention; Fig.13 A schematic diagram of the optimal scheduling result of the integrated energy system under scenario 2 of an embodiment of a scheduling method for an integrated energy system based on multi-layer game provided by the present invention; Fig.14 A schematic diagram of the optimal scheduling result of the producer-seller alliance under scenario 2 of an embodiment of a scheduling method for an integrated energy system based on multi-layer game provided by the present invention; Fig.15 A schematic diagram of the optimal scheduling result of a shared energy storage station 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; Fig.16 A 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; Fig.17 A schematic diagram of the optimal scheduling result of the producer-seller 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; Fig.18 A schematic diagram of the optimal scheduling result of a 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; Fig.19 A 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; Fig. 20 A schematic diagram of the optimal scheduling result of the producer-seller 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; Fig.21A schematic diagram of the results of P2P power sharing between producers and sellers according to an embodiment of a scheduling method for an integrated energy system based on multi-layer game provided by the present invention; Fig. 22 An embodiment of a scheduling method for an integrated energy system based on multi-layer game provided by the present invention is a schematic diagram of profit distribution after electric energy sharing between producers and sellers; Fig.23 A schematic flow chart of an embodiment of a scheduling device for an integrated energy system based on multi-layer game provided by the present invention; Fig.24 A schematic structural diagram of an embodiment of an electronic device provided by the present invention. DETAILED DESCRIPTION

[0040] The preferred embodiments of the present invention are described in detail below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not used to limit the scope of the present invention.

[0041] Before presenting the embodiments, the following terms are explained.

[0042] The Stackelberg game is a dynamic game model proposed by German economist Heinrich Freiherrvon Stackelberg in 1934. The model is mainly used to analyze competitive behavior in oligopoly markets, especially when there are leaders and followers. In the Stackelberg game, it is assumed that there are two manufacturers in the market, one of which (the leader) decides its output first, and the other (the follower) decides its own output after observing the leader's output. When the leader decides the output, it will take into account the reaction of the followers, so the leader's decision is based on the expectation of the follower's reaction.

[0043] The present invention provides a scheduling method and device for an integrated energy system based on multi-layer game, which are described below respectively.

[0044] Figure 1 A schematic flow chart of an embodiment of a scheduling method for an integrated energy system based on multi-layer game provided by the present invention is shown in FIG. Figure 1 As shown in FIG. 1 , the scheduling method of the integrated energy system based on multi-layer game includes: S101, constructing 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; S102, constructing a three-layer game model based on the shared energy storage model, energy system model and producer-seller alliance model; S103. Solve the three-layer game model to obtain the scheduling result of the integrated energy system.

[0045] Compared with the prior art, the present embodiment provides a scheduling method for an integrated energy system based on multi-layer game, firstly constructing a shared energy storage model, an energy system model and a producer-seller model, wherein the shared energy storage model includes a first power constraint and a first objective function constructed by maximizing the intraday 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 intraday benefit of the energy system, and 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, and then constructing a three-layer game model based on the shared energy storage model, the energy system model and the producer-seller alliance model, constructing a three-layer game model to balance the interest distribution of the shared energy storage system, the integrated energy system and the producer-seller alliance to reach a balance point, and finally 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 of the shared energy storage system, the integrated energy system and the producer-seller alliance, thereby balancing the interests of the three parties, and solves the problem of unbalanced interest distribution of each subject caused by the same-level collaborative optimization of a single subject or multiple subjects in the integrated energy system.

[0046] In some embodiments of the present invention, the expression of the first power constraint is:

[0047]

[0048] 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 of energy storage stations at all times.

[0049] In a specific embodiment of the present invention, the parameters of the shared energy storage system are shown in Table 1 below.

[0050] Table 1: Parameters of shared energy storage system

[0051] The expression of the first objective function is:

[0052]

[0053] 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 shared energy storage station sets the lower and upper limits of the electricity purchase price for the integrated energy system at all times. In order to prevent the shared energy storage station from deliberately raising the electricity sales price or lowering the electricity purchase price for the integrated energy system due to profit-seeking, it is necessary to increase the average value of the electricity purchase and sales price of the shared energy storage station for the integrated energy system. , , In a specific embodiment of the present invention, the time-of-use electricity price announced by the power grid is shown in Table 2.

[0054] Table 2: Grid time-of-use electricity price table

[0055] 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 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:

[0056]

[0057]

[0058]

[0059] 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:

[0060]

[0061]

[0062] 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 heat charging and discharging identification position of TES; the parameters of each sub-model in the integrated energy system are shown in Table 3.

[0063] Table 3: Parameters of each sub-model in the integrated energy system

[0064] The input and output power balance constraint formulas of the gas turbine model and the boiler model are:

[0065]

[0066]

[0067]

[0068] 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:

[0069]

[0070] 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 ESS and TES charging and discharging energy cost coefficient, 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. , It is a constraint on the average price of electricity and heat energy sold in the integrated energy system.

[0071] In some embodiments of the present invention, the electric heat load constraint formula of the producer-seller alliance is: (1) (2) (3) 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 heat load reduction and heat load shifting. , 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: (4) (5) 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.

[0072] It should be noted that since the Nash negotiation model is a non-convex nonlinear optimization problem, it is difficult to solve it directly. Therefore, it is necessary to convert the model into a more easily solved alliance cost minimization problem. and distribution of cooperative benefits In some embodiments of the present invention, 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 scheduling 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.

[0073] In a specific embodiment of the present invention, the Nash bargaining solution model between members of the producer-seller alliance is expressed by the following formula: (6) (7) Where: The comprehensive energy purchasing cost of alliance members who do not participate in Nash negotiations within the day is the breaking point of negotiation cooperation. After participating in Nash negotiations, alliance members will not consider sharing electricity payment. Part of the comprehensive energy purchase cost, The difference in comprehensive energy purchase cost before and after the alliance members participate in power sharing. The relevant parameters of the producer-seller alliance are shown in Table 4.

[0074] Table 4 Parameters related to producer-seller alliance

[0075] However, since the Nash negotiation model is a non-convex nonlinear optimization problem, it is difficult to solve it directly. Therefore, it is necessary to convert the model into a more easily solved alliance cost minimization problem. and distribution of cooperative benefits Two sub-problems are solved sequentially.

[0076] set up No consideration of shared electricity payment after alliance cooperation The energy purchase cost is Alliance cost minimization can be expressed as follows:

[0077] set up For sub-problems The optimal solution obtained in the subproblem is The distribution of cooperative benefits can be expressed as follows:

[0078] In some embodiments of the present invention, 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.

[0079] In some embodiments of the present invention, solving the three-layer game model to obtain a scheduling result of the integrated energy system includes: The three-layer game model is solved based on the particle swarm algorithm to obtain the scheduling results of the integrated energy system.

[0080] The present invention introduces cogeneration and concentrated solar power stations into the integrated energy system, and uses the flexibility of cogeneration to make up for the insufficient demand for electricity and heat loads of wind turbines, photovoltaic generators and concentrated solar power stations; in addition, the thermal energy storage device in the concentrated solar power station is used to store the surplus thermal energy, which is then charged into the steam turbine during the peak period of electrical load and converted into electrical energy. This allows the integrated energy system to meet the load demand while greatly improving the utilization rate of primary energy such as natural gas and coal.

[0081] In response to the problem of load-side demand of producers and marketers in the integrated energy system, this technical solution regards the alliance of multiple producers and marketers as a whole to participate in the vertical master-slave game, and uses its integrated energy demand response strategy to minimize the energy purchase cost of the producer and marketer alliance; in addition, this technology embeds the power sharing between producers and marketers as a Nash bargaining cooperation game into the third-level game subject. This allows each individual producer and marketer to reduce its own energy purchase cost through two methods: energy demand restriction of the producer and marketer alliance and Nash bargaining cooperation with other producers and marketers.

[0082] In a specific embodiment of the present invention, Figure 5 , Figure 6 , Figure 7 , Figure 8 The following is a schematic diagram of the input / demand of each electrical and thermal power. Fig. 9 , Fig.10 , Fig.11 The following is a schematic diagram of the optimal scheduling results of the shared energy storage station-integrated energy system-producer-seller alliance in each period under scenario 1. Fig.12 , Fig.13 , Fig.14 The following is a schematic diagram of the optimal scheduling results of the shared energy storage station-integrated energy system-producer-seller alliance in each period under scenario 2. Fig.15 , Fig.16 , Fig.17 The following is a schematic diagram of the optimal scheduling results of the shared energy storage station-integrated energy system-producer-seller alliance in each period under scenario 3. Fig.18 , Fig.19 , Fig. 20 The following is a schematic diagram of the optimal scheduling results of the shared energy storage station-integrated energy system-producer-seller alliance in each period under scenario 4 ( Fig. 9 ),like Fig.21 The following is a schematic diagram of the P2P power sharing results between producers and sellers. Fig. 22 The figure shows the profit distribution diagram after electricity sharing between producers and sellers, the cost comparison table of each subject after collaborative optimization scheduling under different scenarios (Table 5), and the cost comparison table of each producer and seller before and after cooperation (Table 6).

[0083] Table 5 Comparison of cost results of each subject after collaborative optimization scheduling under different strategy scenarios

[0084] Table 6: Comparison of costs of producers and sellers before and after cooperation

[0085] Comparison of the optimal scheduling results of shared energy storage station-integrated energy system-producer-seller alliance under different scenarios. Compared with scenario 1, the cooperative alliance between producers and sellers in scenario 2 can theoretically provide more flexible energy scheduling strategies for entities at all levels. Fig. 9 In the energy storage system, due to the dual influence of the grid time-of-use electricity price and the energy purchase and sale strategy of the integrated energy system, the shared energy storage station can purchase electricity as a reserve when the integrated energy system has sufficient surplus energy, and sell it to the grid during peak power periods (11:00-14:00; 18:00-20:00). Fig.10 and Fig.13 ,contrast Fig.11 and Fig.14 , although there is power sharing between producers and sellers, the total energy demand remains unchanged. Compared with scenario 2, scenario 3 takes into account the energy demand response of producers and sellers and provides a more flexible energy consumption strategy. Fig.12 and Fig.15 , the shared energy storage station no longer provides electricity to the integrated energy system during peak power periods (18:00-20:00), and directly sells surplus energy to the power grid. Fig.13 and Fig.16 ,contrast Fig.14 and Fig.17 , the energy consumption of the producer-seller alliance has changed significantly, among which the maximum reduction in electricity demand is 647.16kw from 19:00 to 20:00, and the maximum reduction in heat demand is 294.696KW from 13:00 to 14:00. In addition, the maximum increase in electricity demand is 260.14kw (23:00-24:00), and the impact of adding electricity sharing between producers and sellers on energy scheduling results needs to be further explored.

[0086] contrast Fig.15 and Fig.18 As the integrated energy system needs to meet the needs of the producer-seller alliance, the power purchased by the integrated energy system from the shared energy storage station will be reduced by 149.51kw (1:00-2:00). Fig.16 and Fig.19 ,contrast Fig.17 and Fig. 20, the maximum reduction in the power demand of the producer-seller alliance was 166.658kw (13:00-14:00), and the maximum increase in power demand was 263.17kw (9:00-10:00), which verified the effectiveness of power sharing between producers and sellers in reducing their own energy consumption costs. In addition, since the power demand of the producer-seller alliance decreased by 167.658kw from 13:00 to 14:00, the CSP power generation output was reduced from 250kw to 163.782kw, and the CHP power output was reduced from 128.022kw to 47.582kw, and the thermal output was reduced from 192.034kw to 71.3726kw. It is worth noting that compared with scenario 1, the daily natural gas loss of the integrated energy system in scenario 4 was reduced by 9.32%.

[0087] From Table 5, we can see that the revenue of shared energy storage stations has dropped significantly. This is because they are indirectly affected by the lowest-level producers and sellers changing their energy consumption strategies. However, due to their highest status, they can still maintain high economic efficiency. However, compared with scenario 1, the revenue of the integrated energy system in scenario 4 has increased by 604.931. This is because the producers and sellers have reduced the comprehensive cost of the producer and seller alliance by 4171.938 by changing their own energy consumption strategies. At the same time, the integrated energy system has gradually reduced the amount of electricity purchased during the high-price period set by the shared energy storage station. From Table 6, we can see that regardless of whether the demand response of the producers and sellers is taken into account, the comprehensive cost after cooperation is always lower than the original energy purchase cost before cooperation. However, when comparing scenario 4 with scenario 1 in Table 5, the comprehensive energy purchase cost of the producer and seller alliance has decreased by 12.16%.

[0088] observe Fig.21 and Fig. 22 , the electricity price shared by producers and sellers 1-2 fluctuates in the range of [0.2195-0.2715], the electricity price shared by producers and sellers 1-3 fluctuates in the range of [0.2083-0.4832], and the electricity price shared by producers and sellers 2-3 fluctuates in the range of [0.2041-0.4011], which meets the set constraint range. Observation Fig.10 The algorithm converged after 38 iterations. Producer 1 converged from the initial -261.995 yuan to -868.734 yuan, Producer 2 converged from the initial -470.849 yuan to -980.856 yuan, and Producer 3 converged 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 of Producer 3 after cooperation has increased, this part will be compensated by the redistribution 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 was reduced by 12.16%. It is verified that the producers in a monopolized position in the master-slave game framework can explore cooperation by realizing power sharing among members and adjust energy consumption strategies by using their own energy demand response, so that they can further reduce their energy purchase costs when they are in a monopolized position.

[0089] In order to better implement a scheduling method for an integrated energy system based on multi-layer game in an embodiment of the present invention, based on a scheduling method for an integrated energy system based on multi-layer game, correspondingly, as Fig.23 As shown, the 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: Model construction module 2301, used to construct 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 2302 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 2303 is used to solve the three-layer game model to obtain the scheduling result of the integrated energy system.

[0090] The scheduling device 2300 for an integrated energy system based on multi-layer game provided in the above embodiment can implement the technical solution described in the above embodiment of a scheduling method for an integrated energy system based on multi-layer game. The specific implementation principles of the above modules or units can refer to the corresponding contents in the above embodiment of a scheduling method for an integrated energy system based on multi-layer game, which will not be repeated here.

[0091] like Fig.24 As shown, the present invention also provides an electronic device 2400. The electronic device 2400 includes a processor 2401, a memory 2402 and a display 2403. Fig.24 Only some components of the electronic device 2400 are shown, but it should be understood that it is not required to implement all of the components shown, and more or fewer components may be implemented instead.

[0092] In some embodiments, the processor 2401 can be a central processing unit (CPU), a microprocessor or other data processing chip, used to run the program code or process data stored in the memory 2402, such as a scheduling method for an integrated energy system based on multi-layer game in the present invention.

[0093] In some embodiments, the processor 2401 may be a single server or a server group. The server group may be centralized or distributed. In some embodiments, the processor 2401 may be local or remote. In some embodiments, the processor 2401 may be implemented in a cloud platform. In some embodiments, the cloud platform may 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 thereof.

[0094] In some embodiments, the memory 2402 may be an internal storage unit of the electronic device 2400, such as a hard disk or memory of the electronic device 2400. In other embodiments, the memory 1202 may 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.

[0095] Furthermore, the memory 2402 may include both an internal storage unit of the electronic device 2400 and an external storage device. The memory 2402 is used to store application software installed in the electronic device 2400 and various data.

[0096] In some embodiments, the display 2403 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, etc. The display 2403 is used to display information on 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.

[0097] In one embodiment, when the processor 2401 executes a scheduling program of an integrated energy system based on multi-layer game in the memory 2402, the following steps may be implemented: 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; The three-layer game model is solved to obtain the dispatch results of the integrated energy system.

[0098] It should be understood that: when the processor 2401 executes a scheduling program for an integrated energy system based on multi-layer game in the memory 2402, in addition to the above functions, other functions can also be implemented. For details, please refer to the description of the corresponding method embodiment above.

[0099] Furthermore, the embodiment of the present invention does not specifically limit the type of the electronic device 2400 mentioned, and the electronic device 2400 may be a portable electronic device such as a mobile phone, a tablet computer, a personal digital assistant (PDA), a wearable device, a laptop computer, etc. Exemplary embodiments of portable electronic devices include but are not limited to portable electronic devices equipped with IOS, Android, Microsoft or other operating systems. The above-mentioned portable electronic devices may also be other portable electronic devices, such as a laptop computer 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 may not be a portable electronic device, but a desktop computer with a touch-sensitive surface (e.g., a touch panel).

[0100] Those skilled in the art will appreciate that all or part of the processes of the above-mentioned embodiments can be implemented by instructing related hardware through a computer program, and the program can be stored in a computer-readable storage medium, wherein the computer-readable storage medium is a disk, an optical disk, a read-only storage memory, or a random access memory, etc.

[0101] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by any technician familiar with the technical field 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; The three-layer game model is solved to obtain the dispatch results of the integrated energy system.

2. The scheduling method of the integrated energy system based on multi-layer game according to claim 1 is characterized in that: 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.

3. The scheduling method of the integrated energy system based on multi-layer game according to claim 1 is characterized in that: 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 ESS and TES charging and discharging energy cost coefficient, 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. , It is a constraint on the average price of electricity and heat energy sold in the integrated energy system.

4. The scheduling method of the integrated energy system based on multi-layer game according to claim 1 is characterized in that: 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.

5. The scheduling method of the integrated energy system based on multi-layer game according to claim 4 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.

6. 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.

7. 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.

8. A dispatching device for an integrated energy system based on multi-layer game, 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.

9. 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 7.

10. 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 7.

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