Hybrid game-based shared energy storage configuration method and device, equipment and medium

Abstract

The application discloses a shared energy storage configuration method and device based on a mixed game, equipment and a medium. The method first acquires basic data related to a shared energy storage power station and a new energy station cluster, and then constructs a plurality of constraints. The upper shared energy storage power station model of the master-slave game model is constructed with the energy storage service price, the energy storage configuration capacity and the energy storage configuration power as the decision variables, and the lower new energy station cluster model of the master-slave game model is constructed with the minimum total cost of the new energy station cluster as the target. Finally, the master-slave game model is solved based on the constructed constraints, the final energy storage calling plan is obtained, and the shared energy storage power station and the new energy station cluster are adjusted according to the energy storage calling plan. Thus, the reasonable allocation of the energy storage configuration is realized, and the stability of the new energy station cluster cooperation alliance is effectively guaranteed.

Description

Technical Field

[0001] This invention relates to the field of energy storage configuration technology, and in particular to a shared energy storage configuration method, apparatus, equipment and medium based on hybrid game theory. Background Technology

[0002] Against the backdrop of new power system construction, renewable energy generation technologies such as wind power and photovoltaics are developing rapidly, with installed capacity increasing year by year. The shared energy storage operation model refers to one energy storage system serving multiple electricity users, and is not limited to a single form of self-built and self-consumed energy storage.

[0003] Scholars have already begun researching business models for shared energy storage. Among existing technologies, some scholars have proposed user-cooperative optimization models that incorporate shared energy storage, combined heat and power (CHP), and photovoltaic power generation, using community integrated energy systems as the research object. In addition, other scholars have established a shared energy storage master-slave game-theoretic pricing model that considers energy storage participation in frequency regulation, with shared energy storage operators as leaders and wind farms as followers.

[0004] However, in the existing methods described above, the capacity of shared energy storage is predetermined. In actual operation, the capacity of the shared energy storage configuration cannot match the demand of new energy power plants. Over-configuration leads to wasted energy storage resources, while under-configuration results in losses for the new energy power plants. Therefore, there is an urgent need to propose an energy storage configuration method that simultaneously considers the planning and operation of shared energy storage. Summary of the Invention

[0005] This invention provides a method for shared energy storage configuration in a new energy power station cluster based on hybrid game theory. The method constructs a master-slave game model and performs cyclic game calculations based on the master-slave game model to obtain the final energy storage call plan, thereby ensuring the reasonable allocation of energy storage configuration and effectively guaranteeing the stability of the new energy power station cluster cooperation alliance.

[0006] One embodiment of the present invention provides a shared energy storage configuration method based on hybrid game theory, comprising:

[0007] Obtain fixed cost data, performance data, service unit price data, shared power capacity limit of new energy power station clusters, load forecast data of new energy power stations, and power curtailment penalty cost of new energy power station clusters;

[0008] Based on the acquired data, constraints are constructed for energy storage system power, energy storage system capacity, energy storage service unit cost, energy storage charging and discharging, energy storage capacity, new energy output, energy sharing, and power balance.

[0009] Based on the obtained data, an upper-level shared energy storage power station model in the master-slave game model is constructed with energy storage service electricity price, energy storage configuration capacity, and energy storage configuration power as decision variables; and based on the obtained data, a lower-level new energy power station cluster model in the master-slave game model is constructed with the goal of minimizing the total cost of the new energy power station cluster.

[0010] Under the established constraints, the master-slave game model is iteratively calculated until game equilibrium is reached, and the final energy storage dispatch plan is output. The energy storage dispatch plan includes the energy storage service price of the shared energy storage power station, the rated charging and discharging power of the shared energy storage power station, the rated capacity of the energy storage power station, and the charging and discharging power of each new energy power station when storing energy.

[0011] Adjustments will be made to energy storage power stations and new energy power station clusters according to the aforementioned energy storage dispatch plan.

[0012] Furthermore, based on the acquired data, and under the constructed constraints, the master-slave game model is iteratively subjected to game calculations until a game equilibrium is reached, resulting in the final energy storage deployment plan, including:

[0013] When the upper-layer shared energy storage power station model is performing game calculation for the first time, the decision variables are initialized under the constraints of the energy storage system power, the energy storage system capacity, and the energy storage service unit cost, and the initialized decision variables are passed to the lower-layer new energy power station cluster model.

[0014] When the upper-level shared energy storage power station model is not being used for the first game calculation, the upper-level shared energy storage power station model is solved based on the charging and discharging power, cost data, performance data, and service unit price data of each new energy power station obtained after the previous game calculation of the lower-level shared energy storage power station. This yields updated decision variables, and it is determined whether the differences between the decision variables before and after the update in this game calculation are all less than the corresponding preset thresholds.

[0015] If so, stop the game theory calculation and output the final energy storage and utilization plan.

[0016] If not, the updated decision variables will be passed to the lower-level shared energy storage power station;

[0017] Based on the decision variables, performance data, shared power limit of the new energy power station cluster, load forecast data of the new energy power station, and the curtailment penalty cost of the new energy power station cluster, the lower-level shared energy storage power station model is solved under the constraints of energy storage charging and discharging, energy storage capacity, new energy output, energy sharing, and power balance to obtain the updated charging and discharging power of each new energy power station during energy storage. The updated charging and discharging power of each new energy power station during energy storage is then transferred to the updated charging and discharging power of each new energy power station during energy storage.

[0018] Furthermore, the upper-layer shared energy storage power station model includes:

[0019] C revenue =C service -C investor ;

[0020]

[0021] C OM,f =c f P con ;

[0022] In the formula, C revenue Indicates shared energy storage revenue; C service This refers to the energy storage service fee charged by the energy storage power station to the new energy power station; C investor Indicates the investment cost of shared energy storage; C i,service P represents the electricity price for energy storage services used by renewable energy power plants (i). i,ch,t P represents the charging power of the new energy power station when storing energy. i,dis,t represents the discharge power of energy storage at new energy power station i; N represents the planning period in years; r represents the discount rate; α represents the percentage decrease in energy storage costs; C REP Indicates the operation and maintenance cost of the energy storage system; C OM Indicates the operation and maintenance cost of the energy storage system; C INV Indicates the initial investment cost of the energy storage system; C OM,v Indicates variable maintenance costs; C OM,f Indicates fixed maintenance costs; c P Indicates the unit power cost of the energy storage system; c E P represents the unit capacity cost of an energy storage system. con Indicates the planned energy storage configuration capacity; E con Indicates the planned energy storage configuration capacity; T life Indicates the energy storage lifespan; k represents the number of replacements; c f This represents the fixed operation and maintenance cost per unit power of the energy storage system; c vP represents the real-time operation and maintenance cost per unit power of the energy storage system; ch,t P represents the total charging power of energy storage; dis,t This indicates the total discharge power of the stored energy.

[0023] Furthermore, the lower-level shared energy storage power station model includes:

[0024]

[0025] Among them, C new C represents the total cost of a cluster of new energy power stations; i,new C represents the cost of new energy power station i; i,service This indicates the electricity price for energy storage services used by renewable energy power plants (i); C i,dispatch This indicates the operating cost of a new energy power station after it is equipped with storage; C i,ab P represents the cost of wind and solar power curtailment at renewable energy power plants; i,new,t This indicates the actual output of the renewable energy power station; P i,new,pre,t Indicates the predicted output of new energy power plants; c pun This indicates the penalty cost for curtailment of electricity generated by new energy power plant clusters.

[0026] Furthermore, the energy storage charging and discharging power constraint includes:

[0027]

[0028] 0≤P ch,t ≤uP con ;

[0029] 0≤P dis,t ≤(1-u)P con ;

[0030] Among them, P ch,grid,t This represents the charging power of the energy storage system interacting with the external power grid, where u represents the charging / discharging state, 1 indicates charging, and 0 indicates discharging; P dis,grid,t This represents the discharge power of the energy storage system interacting with the external power grid, where u represents the charging / discharging state, 1 indicates charging, and 0 indicates discharging; P ch,t P represents the total charging power of energy storage; dis,t P represents the total discharge power of the stored energy. i,ch,t P represents the charging power of the new energy power station when storing energy. i,dis,t P represents the discharge power of the new energy power station i when storing energy; con This indicates the planned energy storage capacity.

[0031] Furthermore, the energy storage capacity constraint includes:

[0032]

[0033] 0≤E t ≤E con ;

[0034] E0 = E T ;

[0035] Among them, E t E represents the energy storage capacity at time t. T E represents the energy storage capacity at the final moment, and E0 represents the energy storage capacity at the initial moment, 0≤t≤T; η ch Indicates energy storage charging efficiency; η dis P represents the energy storage and discharge efficiency. dis,t P represents the total discharge power of the stored energy. ch,t E represents the total charging power of energy storage. con This indicates the planned energy storage configuration capacity.

[0036] Furthermore, the energy sharing constraint includes:

[0037] 0≤P i-j,share,t ≤sP share,max ;

[0038] 0≤P j-i,share,t ≤(1-s)P share,max ;

[0039] Among them, P share,max Indicates the upper limit of shared electricity capacity for the new energy power station cluster; P j-i,share,t This indicates that renewable energy power station j supplies energy to renewable energy power station i, P i-j,share,t This indicates that new energy power station i supplies energy to new energy power station j, and s indicates the status of the interactive power, where 1 indicates that i supplies energy to j and 0 indicates that j supplies energy to i.

[0040] An embodiment of the present invention also provides a shared energy storage configuration device based on hybrid game theory, including: a data acquisition module, a constraint construction module, a master-slave game model construction module, an energy storage call plan output module, and an adjustment module;

[0041] The data acquisition module is used to acquire fixed cost data of energy storage power stations, performance data of energy storage power stations, service unit price data of energy storage power stations, shared power capacity limit of new energy power station clusters, load forecast data of new energy power stations, and power curtailment penalty cost of new energy power station clusters.

[0042] The constraint construction module is used to construct energy storage system power constraints, energy storage system capacity constraints, energy storage service unit cost constraints, energy storage charging and discharging constraints, energy storage capacity constraints, new energy output constraints, energy sharing constraints, and power balance constraints based on the acquired data.

[0043] The master-slave game model construction module is used to construct an upper-level shared energy storage power station model in the master-slave game model based on the acquired data, with energy storage service electricity price, energy storage configuration capacity and energy storage configuration power as decision variables; and to construct a lower-level new energy power station cluster model in the master-slave game model based on the acquired data, with the goal of minimizing the total cost of the new energy power station cluster.

[0044] The energy storage dispatch plan output module is used to perform game calculations on the master-slave game model cyclically under the constructed constraints until the game equilibrium is reached, and output the final energy storage dispatch plan; wherein, the energy storage dispatch plan includes the energy storage service electricity price of the shared energy storage power station, the rated charging and discharging power of the shared energy storage power station, the rated capacity of the energy storage power station, and the charging and discharging power of each new energy power station when storing energy.

[0045] The adjustment module is used to adjust the energy storage power station and the new energy power station cluster according to the energy storage dispatch plan.

[0046] This application also provides a terminal device, including:

[0047] One or more processors;

[0048] A memory, coupled to the processor, for storing one or more programs;

[0049] When the one or more programs are executed by the one or more processors, the one or more processors implement the shared energy storage configuration method based on hybrid game theory as described in the above embodiments of the invention.

[0050] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the shared energy storage configuration method based on hybrid game theory as described in the above embodiments.

[0051] The following benefits can be obtained by implementing the present invention:

[0052] This invention provides a method for configuring shared energy storage in a new energy power station cluster based on hybrid game theory. The method first obtains basic data related to the shared energy storage power station and the new energy power station cluster, and then constructs several constraints to ensure that the results obtained in solving the model do not exceed the limits.

[0053] Secondly, an upper-level shared energy storage power station model was constructed using energy storage service electricity price, energy storage configuration capacity, and energy storage configuration power as decision variables. A lower-level new energy power station cluster model was constructed using a master-slave game model with the objective of minimizing the total cost of the new energy power station cluster. Thus, the constructed master-slave game model simultaneously uses the configuration information of the shared energy storage system and the revenue from shared energy storage as decision variables, thereby enabling dynamic pricing and capacity configuration of energy storage when solving the model in the subsequent process.

[0054] Finally, the master-slave game model is solved based on the constructed constraints to obtain the final energy storage dispatch plan. According to the energy storage dispatch plan, the shared energy storage power station and the new energy power station cluster are adjusted. Thus, the rational allocation of energy storage configuration is achieved, effectively ensuring the stability of the new energy power station cluster cooperation alliance. Attached Figure Description

[0055] To more clearly illustrate the technical solution of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0056] Figure 1 This is a flowchart illustrating a shared energy storage configuration method based on hybrid game theory provided in a certain embodiment of this application.

[0057] Figure 2 This is a schematic diagram of the structure of a shared energy storage configuration device based on hybrid game theory provided in a certain embodiment of this application;

[0058] Figure 3 This is a schematic diagram of the structure of a terminal device provided in a certain embodiment of this application. Detailed Implementation

[0059] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0060] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0061] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0062] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0063] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0064] In the description of the embodiments of this application, the term "multiple" refers to two or more (including two), similarly, "multiple sets" refers to two or more (including two sets), and "multiple pieces" refers to two or more (including two pieces).

[0065] In the description of the embodiments of this application, unless otherwise expressly specified and limited, technical terms such as "installation," "connection," "joining," and "fixing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. For those skilled in the art, the specific meaning of the above terms in the embodiments of this application can be understood according to the specific circumstances.

[0066] See Figure 1 This is a flowchart illustrating a shared energy storage configuration method based on hybrid game theory, provided in an embodiment of the present invention, comprising:

[0067] S1. Obtain fixed cost data, performance data, service unit price data, shared power capacity limit of new energy power station cluster, load forecast data of new energy power station, and power curtailment penalty cost of new energy power station cluster;

[0068] Specifically, the fixed cost data of the energy storage power station includes: unit power cost, unit capacity cost, unit power fixed operation and maintenance cost, unit power real-time operation and maintenance cost, and the percentage decrease in energy storage cost; the performance data of the energy storage power station includes: the maximum power of the system, the maximum capacity of the energy storage system, and the energy storage charging and discharging efficiency of the energy storage system; the service unit price data of the energy storage power station includes: the upper limit of the service unit price of the energy storage system and the lower limit of the service unit price of the energy storage system; the load forecast data of the new energy power station includes: the day-ahead forecast power of the new energy power station and the forecast output of the new energy power station; specifically, the acquired data also includes the upper limit of the shared power capacity of the new energy power station cluster and the penalty cost for power curtailment of the new energy power station cluster.

[0069] S2. Based on the acquired data, construct the following constraints: energy storage system power constraint, energy storage system capacity constraint, energy storage service unit cost constraint, energy storage charging and discharging constraint, energy storage capacity constraint, new energy output constraint, energy sharing constraint, and power balance constraint.

[0070] Indicatively, the upper-level shared energy storage power station model should meet the constraints of energy storage system power, energy storage system capacity, and energy storage service provider fees. Due to investment cost limitations and practical constraints, energy storage capacity and power cannot be configured without limit. Therefore, the shared energy storage configuration should meet the energy storage system power and capacity constraints. In addition to meeting these constraints, it should also meet the energy storage service provider fee constraints to prevent energy storage power stations from arbitrarily increasing the price of energy storage services in order to maximize their own profits.

[0071] Specifically, the power constraint of the energy storage system includes:

[0072] 0≤P con ≤P max ;

[0073] Among them, P max P represents the maximum power of the energy storage configuration. con This indicates the planned energy storage capacity.

[0074] Specifically, the capacity constraints of the energy storage system include:

[0075] 0≤E con ≤E max ;

[0076] Among them, E maxIndicates the maximum capacity of the energy storage configuration; E con This indicates the planned energy storage configuration capacity.

[0077] Specifically, the cost constraints for the energy storage service provider include:

[0078] c service,min ≤c i,service ≤c service,max ;

[0079] Among them, c service,min Indicates the upper limit of the unit price for energy storage services; c service,max This indicates the lower limit of the unit price for energy storage services.

[0080] Indicatively, the lower-level new energy power station cluster model should meet constraints including energy storage charging and discharging constraints, energy storage capacity constraints, new energy output constraints, energy sharing constraints, and power balance constraints.

[0081] In a preferred embodiment, the energy storage charging and discharging power constraint includes:

[0082]

[0083] 0≤P ch,t ≤uP con ;

[0084] 0≤P dis,t ≤(1-u)P con ;

[0085] Among them, P ch,grid,t This represents the charging power of the energy storage system interacting with the external power grid, where u represents the charging / discharging state, 1 indicates charging, and 0 indicates discharging; P dis,grid,t This represents the discharge power of the energy storage system interacting with the external power grid, where u represents the charging / discharging state, 1 indicates charging, and 0 indicates discharging; P ch,t P represents the total charging power of energy storage; dis,t P represents the total discharge power of the stored energy. i,ch,t P represents the charging power of the new energy power station when storing energy. i,dis,t P represents the discharge power of the new energy power station i when storing energy; con Indicates the planned energy storage configuration capacity;

[0086] It is understandable that 0≤t≤T, and the duration of T can be adjusted according to the actual situation, such as 24 hours.

[0087] In a preferred embodiment, the energy storage capacity constraint includes:

[0088]

[0089] 0≤Et ≤E con ;

[0090] E0 = E T ;

[0091] Among them, E t E represents the energy storage capacity at time t. T E represents the energy storage capacity at the final moment, and E0 represents the energy storage capacity at the initial moment, 0≤t≤T; η ch Indicates energy storage charging efficiency; η dis P represents the energy storage and discharge efficiency. dis,t P represents the total discharge power of the stored energy. ch,t E represents the total charging power of energy storage. con This indicates the planned energy storage configuration capacity;

[0092] It is understandable that 0≤t≤T, and the duration of T can be adjusted according to the actual situation, such as 24 hours.

[0093] In a preferred embodiment, the energy-sharing constraint includes:

[0094] 0≤P i-j,share,t ≤sP share,max ;

[0095] 0≤P j-i,share,t ≤(1-s)P share,max ;

[0096] Among them, P share,max Indicates the upper limit of shared electricity capacity for the new energy power station cluster; P j-i,share,t This indicates that renewable energy power station j supplies energy to renewable energy power station i, P i-j,share,t This indicates that new energy power station i supplies energy to new energy power station j, and s indicates the status of the interactive power, where 1 indicates that i supplies energy to j and 0 indicates that j supplies energy to i.

[0097] Specifically, the constraints on the output of the new energy source include:

[0098] 0≤P i,new,t ≤P i,new,pre,t ;

[0099] Among them, P i,new,pre,t This indicates the predicted output of the new energy power station; P i,new,t This indicates the actual power output of the new energy power station;

[0100] It should be noted that the predicted output of the new energy power station is a fixed value; the actual output of the new energy power station is a decision variable.

[0101] Specifically, the power balance constraint includes:

[0102]

[0103] Among them, P load,t P represents the load power near the renewable energy power station; j-i,share,t This indicates that renewable energy power station j supplies energy to renewable energy power station i, P i-j,share,t This indicates that renewable energy power station i supplies energy to renewable energy power station j, s represents the status of the exchanged electricity, 1 indicates that i supplies energy to j, and 0 indicates that j supplies energy to i; P i,new,t This indicates the actual output of the renewable energy power station; P i,ch,t P represents the charging power of the new energy power station when storing energy. i,dis,t This indicates the discharge power of the new energy power station during energy storage.

[0104] It should be noted that, in the aforementioned power balance constraint, the load power P near the renewable energy power station load,t To determine the values, the rest are decision variables.

[0105] S3. Based on the obtained data, using the energy storage service electricity price, energy storage configuration capacity, and energy storage configuration power as decision variables, construct the upper-level shared energy storage power station model in the master-slave game model; and based on the obtained data, construct the lower-level new energy power station cluster model in the master-slave game model with the goal of minimizing the total cost of the new energy power station cluster.

[0106] To illustrate, it is necessary to first determine the roles of the master and slave in the master-slave game model; designate the upper-level shared energy storage power station as the game leader and the lower-level new energy power station cluster as the game follower, and construct the upper-level shared energy storage power station model and the lower-level new energy power station cluster model in the master-slave game model accordingly.

[0107] In a preferred embodiment, the upper-layer shared energy storage power station model includes:

[0108] C revenue =C service -C investor ;

[0109]

[0110] C OM,f =c f P con ;

[0111] In the formula, C revenue Indicates shared energy storage revenue; C service This refers to the energy storage service fee charged by the energy storage power station to the new energy power station; C investor Indicates the investment cost of shared energy storage; C i,service P represents the electricity price for energy storage services used by renewable energy power plants (i). i,ch,tP represents the charging power of the new energy power station when storing energy. i,dis,t represents the discharge power of energy storage at new energy power station i; N represents the planning period in years; r represents the discount rate; α represents the percentage decrease in energy storage costs; C REP Indicates the operation and maintenance cost of the energy storage system; C OM Indicates the operation and maintenance cost of the energy storage system; C INV Indicates the initial investment cost of the energy storage system; C OM,v Indicates variable maintenance costs; C OM,f Indicates fixed maintenance costs; c P Indicates the unit power cost of the energy storage system; c E P represents the unit capacity cost of an energy storage system. con Indicates the planned energy storage configuration capacity; E con Indicates the planned energy storage configuration capacity; T life Indicates the energy storage lifespan; k represents the number of replacements; c f This represents the fixed operation and maintenance cost per unit power of the energy storage system; c v P represents the real-time operation and maintenance cost per unit power of the energy storage system; ch,t P represents the total charging power of energy storage; dis,t This indicates the total discharge power of the stored energy;

[0112] Specifically, shared energy storage revenue C revenue Including revenue from shared energy storage services C service And shared energy storage investment cost C investor :

[0113] C revenue =C service -C investor

[0114] In the formula, C service C represents the energy storage service fee charged by the energy storage power station to the new energy power station. service The expression is as follows:

[0115]

[0116] In the formula, C i,service P represents the electricity price for energy storage services used by renewable energy power plants (i). i,ch,t P represents the charging power of energy storage used in the new energy power station i; i,dis,t This indicates the discharge power of the energy storage used in the new energy power station i.

[0117] Shared energy storage investment cost C investor Specifically, the lifecycle cost of energy storage refers to all expenses incurred from the initial construction phase to the eventual disposal of the energy storage system. The lifecycle cost includes the initial investment cost C. INVOperation and maintenance costs C OM Equipment replacement cost C REP ;

[0118] Initial investment cost C INV This refers to the fixed costs of energy storage that require a one-time investment at the initial stage of construction, including battery purchase costs, land resource leasing and other related expenses. The initial investment cost includes the planned energy storage capacity P. con And the planned energy storage configuration power E con ;

[0119]

[0120] In the formula, C INV c is the initial investment cost of the energy storage system; P Indicates the unit power cost of the energy storage system; c E P represents the unit capacity cost of an energy storage system. con Indicates the planned energy storage configuration capacity; E con This indicates the planned energy storage configuration capacity;

[0121] It should be noted that the unit capacity cost c of the energy storage system E and the unit power cost of energy storage systems c P These are pre-defined fixed parameters, set by the actual energy storage model.

[0122] Operation and maintenance costs C OM Operation and maintenance costs refer to the expenses incurred in maintaining an energy storage system in a good charging and discharging state throughout its lifespan. These costs are categorized into variable operation and maintenance costs (C). OM,v and fixed maintenance costs C OM,f Among them, the variable operation and maintenance cost C OM,v The fixed operation and maintenance cost C is related to the real-time operating status of energy storage. OM,f This depends on the rated power of the energy storage;

[0123] C OM =C OM,v +C OM,f ;

[0124]

[0125] C OM,f =c f P con ;

[0126] In the formula, C OM c. The operation and maintenance costs of the energy storage system; f This represents the fixed operation and maintenance cost per unit power of the energy storage system; c v P represents the real-time operation and maintenance cost per unit power of the energy storage system;ch,t P represents the total charging power of energy storage; dis,t This indicates the total discharge power of the stored energy;

[0127] It should be noted that the unit power fixed operation and maintenance cost c of the energy storage system f Real-time operation and maintenance cost per unit power c v These are all fixed parameters, set according to the actual energy storage model;

[0128] Equipment replacement cost C REP This refers to the replacement cost of energy storage during the planning period. Factors influencing this cost include the lifespan of the energy storage battery, usage frequency, charge / discharge cycle count, and replacement frequency. It can be expressed as follows:

[0129]

[0130] In the formula, C REP Equipment replacement costs for energy storage systems; T life α represents the energy storage lifespan; k represents the number of replacements; r represents the discount rate; and α represents the percentage decrease in energy storage costs.

[0131] It should be noted that the discount rate r and the energy storage cost reduction ratio α are both preset parameters, set by the actual energy storage model.

[0132] The above-mentioned shared energy storage investment cost is the total cost of energy storage during the planning period. After being allocated to each year, the shared energy storage investment cost can be expressed as follows:

[0133]

[0134] In the formula, N represents the number of years in the planning period.

[0135] In a preferred embodiment, the lower-level shared energy storage power station model includes:

[0136]

[0137] Among them, C new C represents the total cost of a cluster of new energy power stations; i,new C represents the cost of new energy power station i; i,service This indicates the electricity price for energy storage services used by renewable energy power plants (i); C i,dispatch This indicates the operating cost of a new energy power station after it is equipped with storage; C i,ab P represents the cost of wind and solar power curtailment at renewable energy power plants; i,new,t This indicates the actual output of the renewable energy power station; P i,new,pre,t Indicates the predicted output of new energy power plants; c pun This indicates the penalty cost for curtailment of electricity generated by new energy power plant clusters.

[0138] S4. Under the constructed constraints, the master-slave game model is repeatedly calculated until the game equilibrium is reached, and the final energy storage dispatch plan is output; wherein, the energy storage dispatch plan includes the energy storage service electricity price of the shared energy storage power station, the rated charging and discharging power of the shared energy storage power station, the rated capacity of the energy storage power station, and the charging and discharging power of each new energy power station when storing energy.

[0139] In a preferred embodiment, the step of cyclically performing game calculations on the master-slave game model based on the acquired data and under the constructed constraints until game equilibrium is reached, thereby obtaining the final energy storage deployment plan, includes:

[0140] When the upper-layer shared energy storage power station model is performing game calculation for the first time, the decision variables are initialized under the constraints of the energy storage system power, the energy storage system capacity, and the energy storage service unit cost, and the initialized decision variables are passed to the lower-layer new energy power station cluster model.

[0141] When the upper-level shared energy storage power station model is not being used for the first game calculation, the upper-level shared energy storage power station model is solved based on the charging and discharging power, cost data, performance data, and service unit price data of each new energy power station obtained after the previous game calculation of the lower-level shared energy storage power station. This yields updated decision variables, and it is determined whether the differences between the decision variables before and after the update in this game calculation are all less than the corresponding preset thresholds.

[0142] If so, stop the game theory calculation and output the final energy storage and utilization plan.

[0143] If not, the updated decision variables will be passed to the lower-level shared energy storage power station;

[0144] Based on the decision variables, performance data, shared power limit of the new energy power station cluster, load forecast data of the new energy power station, and the power curtailment penalty cost of the new energy power station cluster, the lower-level shared energy storage power station model is solved under the constraints of energy storage charging and discharging, energy storage capacity, new energy output, energy sharing, and power balance to obtain the updated charging and discharging power of each new energy power station during energy storage, and the updated charging and discharging power of each new energy power station during energy storage is transferred to the updated charging and discharging power of each new energy power station during energy storage.

[0145] Specifically, when the upper-level shared energy storage power station model is being used for the first game theory calculation, the energy storage service price c of the shared energy storage power station needs to be initialized under the constraints of the energy storage system power, the energy storage system capacity, and the energy storage service unit cost. i,serviceEnergy storage configuration capacity E con and energy storage configuration power P con Then, the initialized decision variables are passed to the lower-level new energy power station cluster model;

[0146] Specifically, when the upper-level shared energy storage power station model is not undergoing game calculation for the first time, it is necessary to determine whether the game equilibrium has been reached based on the difference between the decision variables before and after the update of the upper-level shared energy storage power station model in this game calculation. The specific conditions for this determination are as follows:

[0147] (1) The difference between the energy storage service price before and after the update in this game calculation is less than C1·C service,max C1 is set to 0.01 according to the actual situation;

[0148] (2) The difference between the energy storage configuration capacity before and after the update in this game calculation is less than C2·E. max C2 is set to 0.001 according to the actual situation;

[0149] (3) The difference between the energy storage configuration power before and after the update in this game calculation is less than C3·P max C3 is set to 0.001 according to the actual situation;

[0150] If the difference between the decision variables before and after the update in this game calculation satisfies conditions (1), (2) and (3), stop the game calculation and output the final energy storage call plan.

[0151] Therefore, the master-slave game model performs game calculations cyclically until it is determined that a game equilibrium has been reached, at which point the game calculations stop and the final energy storage and mobilization plan is output.

[0152] S5. Adjust the energy storage power station and new energy power station cluster according to the energy storage dispatch plan;

[0153] Specifically, after obtaining the final energy storage dispatch plan, adjustments need to be made to the energy storage power stations and the new energy power station clusters based on the energy storage service electricity price of the shared energy storage power stations, the rated charging and discharging power of the shared energy storage power stations, the rated capacity of the energy storage power stations, and the charging and discharging power of each new energy power station when storing energy in the energy storage dispatch plan.

[0154] Furthermore, after obtaining the final energy storage dispatch plan, the service revenue of the new energy power station can be determined based on the energy storage dispatch plan;

[0155] Specifically, based on the cost data, performance data, service unit price data, the shared power capacity limit of the new energy power station cluster, the load forecast data of the new energy power station, the power curtailment penalty cost of the new energy power station cluster, and the energy storage dispatch plan, the final shared energy storage revenue c of the energy storage power station is determined. i,service And the cost C of each new energy power station i,new ;

[0156] Next, the independent costs of each new energy power station were determined without considering energy sharing between the new energy power stations;

[0157] It should be noted that the determination of the independent cost of each renewable energy power station, without considering energy sharing between renewable energy power stations, includes:

[0158] Set the upper limit of the shared power of the new energy power station cluster to 0;

[0159] Under the constructed constraints, the master-slave game model is repeatedly calculated until the game equilibrium is reached, and the independent energy storage dispatch plan is output without considering energy sharing between new energy power stations.

[0160] Based on the cost data, performance data, service unit price data, the shared power capacity limit of the new energy power station cluster, the load forecast data of the new energy power station, the curtailment penalty cost of the new energy power station cluster, and the independent energy storage call plan, the independent cost C of each new energy power station is determined. i,new,0 ;

[0161] Then, based on the cost of each new energy power station and the independent cost of each new energy power station, the allocation coefficient of each new energy power station and the benefit improvement value achieved by each new energy power station through energy sharing are determined.

[0162] Specifically, the benefit improvement value C achieved by each new energy power station through energy sharing is determined by the following formula. i,new,up :

[0163] C i,new,up =C i,new,0 -C i,new ;

[0164] Among them, C i,new,0 C represents the independent cost of renewable energy power station i; i,new This represents the cost of new energy power station i;

[0165] Specifically, the allocation coefficient for each new energy power station is determined using the following formula:

[0166]

[0167] Among them, wi C represents the allocation coefficient for renewable energy power station i; i,new,0 C represents the independent cost of renewable energy power station i; i,new This represents the cost of new energy power station i;

[0168] Finally, the service revenue of each new energy power station is determined based on the aforementioned benefit improvement value and the aforementioned allocation coefficient.

[0169] Specifically, the service revenue of each new energy power station is determined using the following formula:

[0170]

[0171] See Figure 2 This application provides a shared energy storage configuration device based on hybrid game theory in one embodiment, comprising: a data acquisition module, a constraint construction module, a master-slave game model construction module, an energy storage call plan output module, and an adjustment module;

[0172] The data acquisition module is used to acquire fixed cost data of energy storage power stations, performance data of energy storage power stations, service unit price data of energy storage power stations, shared power capacity limit of new energy power station clusters, load forecast data of new energy power stations, and power curtailment penalty cost of new energy power station clusters.

[0173] The constraint construction module is used to construct energy storage system power constraints, energy storage system capacity constraints, energy storage service unit cost constraints, energy storage charging and discharging constraints, energy storage capacity constraints, new energy output constraints, energy sharing constraints, and power balance constraints based on the acquired data.

[0174] The master-slave game model construction module is used to construct an upper-level shared energy storage power station model in the master-slave game model based on the acquired data, with energy storage service electricity price, energy storage configuration capacity and energy storage configuration power as decision variables; and to construct a lower-level new energy power station cluster model in the master-slave game model based on the acquired data, with the goal of minimizing the total cost of the new energy power station cluster.

[0175] The energy storage dispatch plan output module is used to perform game calculations on the master-slave game model cyclically under the constructed constraints until the game equilibrium is reached, and output the final energy storage dispatch plan; wherein, the energy storage dispatch plan includes the energy storage service electricity price of the shared energy storage power station, the rated charging and discharging power of the shared energy storage power station, the rated capacity of the energy storage power station, and the charging and discharging power of each new energy power station when storing energy.

[0176] The adjustment module is used to adjust the energy storage power station and the new energy power station cluster according to the energy storage dispatch plan.

[0177] See Figure 3One embodiment of this application also provides a terminal device, including:

[0178] One or more processors;

[0179] A memory, coupled to the processor, for storing one or more programs;

[0180] When the one or more programs are executed by the one or more processors, the one or more processors implement the shared energy storage configuration method based on hybrid game theory as described above.

[0181] The processor controls the overall operation of the terminal device to complete all or part of the steps of the aforementioned hybrid game-based shared energy storage configuration method. The memory stores various types of data to support the operation of the terminal device. This data may include, for example, instructions for any application or method operating on the terminal device, as well as application-related data. The memory can be implemented using any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0182] In an exemplary embodiment, the terminal device may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to execute the shared energy storage configuration method based on hybrid game theory as described in any of the above embodiments, and achieve the same technical effect as the above method.

[0183] In another exemplary embodiment, a computer-readable storage medium including a computer program is also provided. When executed by a processor, the computer program implements the steps of the shared energy storage configuration method based on hybrid game theory as described in any of the foregoing embodiments. For example, the computer-readable storage medium may be the aforementioned memory including the computer program, which may be executed by a processor of a terminal device to complete the shared energy storage configuration method based on hybrid game theory as described in any of the foregoing embodiments and achieve the same technical effects as the aforementioned method.

[0184] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A shared energy storage configuration method based on hybrid game theory, characterized in that, include: Acquire fixed cost data, performance data, service unit price data, shared power capacity limit of new energy power station clusters, load forecast data of new energy power stations, and curtailment penalty cost of new energy power station clusters; based on the acquired data, construct energy storage system power constraints, energy storage system capacity constraints, energy storage service unit cost constraints, energy storage charging and discharging constraints, energy storage capacity constraints, new energy output constraints, energy sharing constraints, and power balance constraints. Based on the obtained data, an upper-level shared energy storage power station model in the master-slave game model is constructed with energy storage service electricity price, energy storage configuration capacity, and energy storage configuration power as decision variables; and based on the obtained data, a lower-level new energy power station cluster model in the master-slave game model is constructed with the goal of minimizing the total cost of the new energy power station cluster. When the upper-layer shared energy storage power station model is performing game calculation for the first time, the decision variables are initialized under the constraints of the energy storage system power, the energy storage system capacity, and the energy storage service unit cost, and the initialized decision variables are passed to the lower-layer new energy power station cluster model. When the upper-level shared energy storage power station model is not being used for the first game calculation, the upper-level shared energy storage power station model is solved based on the charging and discharging power, cost data, performance data, and service unit price data of each new energy power station obtained after the previous game calculation of the lower-level shared energy storage power station. This yields updated decision variables, and it is determined whether the differences between the decision variables before and after the update in this game calculation are all less than the corresponding preset thresholds. If so, stop the game theory calculation and output the final energy storage and utilization plan. If not, the updated decision variables will be passed to the lower-level shared energy storage power station; Based on the decision variables, performance data, shared power limit of the new energy power station cluster, load forecast data of the new energy power station, and the power curtailment penalty cost of the new energy power station cluster, the lower-level shared energy storage power station model is solved under the constraints of energy storage charging and discharging, energy storage capacity, new energy output, energy sharing, and power balance to obtain the updated charging and discharging power of each new energy power station during energy storage. The updated charging and discharging power of each new energy power station during energy storage is then transferred to the updated charging and discharging power of each new energy power station during energy storage. The energy storage dispatch plan includes the energy storage service price of the shared energy storage power station, the rated charging and discharging power of the shared energy storage power station, the rated capacity of the energy storage power station, and the charging and discharging power of each new energy power station during energy storage. Adjustments will be made to energy storage power stations and new energy power station clusters according to the aforementioned energy storage dispatch plan.

2. The shared energy storage configuration method based on hybrid game theory as described in claim 1, characterized in that, The upper-layer shared energy storage power station model includes: ； ； ； ； ； ； ； In the formula, Indicates shared energy storage revenue; This indicates the energy storage service fee charged by the energy storage power station to the new energy power station; Indicates the investment cost of shared energy storage; Indicates new energy power station Electricity price for energy storage services; Indicates new energy power station Charging power during energy storage; Indicates new energy power station Discharge power during energy storage; Indicates the number of years in the planning period; Indicates the discount rate. Indicates the percentage decrease in energy storage costs; This indicates the operation and maintenance costs of the energy storage system; This indicates the operation and maintenance costs of the energy storage system; This indicates the initial investment cost of the energy storage system; Indicates variable operation and maintenance costs; This represents fixed operation and maintenance costs; This indicates the unit power cost of the energy storage system; This indicates the unit capacity cost of the energy storage system; Indicates the planned energy storage configuration capacity; This indicates the planned energy storage configuration capacity; Indicates the energy storage lifespan; Indicates the number of replacements; This represents the fixed operation and maintenance cost per unit power of the energy storage system; This represents the real-time operation and maintenance cost per unit power of the energy storage system; This indicates the total charging power of the energy storage; This indicates the total discharge power of the stored energy.

3. The shared energy storage configuration method based on hybrid game theory as described in claim 1, characterized in that, The lower-level new energy power station cluster model includes: ； ； in, This represents the total cost of the new energy power station cluster; Indicates new energy power station The cost; Indicates new energy power station Electricity price for energy storage services; This indicates the operating cost of a new energy power station after it is equipped with storage. This indicates the cost of wind and solar power curtailment at renewable energy power plants; This indicates the actual power output of the new energy power station; This indicates the predicted power output of the new energy power station; This indicates the penalty cost for curtailment of electricity generated by new energy power plant clusters.

4. The shared energy storage configuration method based on hybrid game theory as described in claim 1, characterized in that, The energy storage charging and discharging power constraint includes: ； ； ； ； in, This indicates the charging power of the energy storage system interacting with the external power grid. This indicates the charging / discharging state, with 1 indicating charging and 0 indicating discharging. This represents the discharge power of the energy storage system interacting with the external power grid. This indicates the charging / discharging state, with 1 indicating charging and 0 indicating discharging. This indicates the total charging power of the energy storage; This indicates the total discharge power of the stored energy; Indicates new energy power station Charging power during energy storage; Indicates new energy power station Discharge power during energy storage; This indicates the planned energy storage capacity.

5. The shared energy storage configuration method based on hybrid game theory as described in claim 1, characterized in that, The energy storage capacity constraints include: ； ； ； in, Indicates energy storage Real-time energy storage capacity This indicates the energy storage capacity at the final moment. This represents the energy storage capacity at the initial moment. ; Indicates energy storage charging efficiency; Indicates the energy storage discharge efficiency; This indicates the total discharge power of the stored energy; This indicates the total charging power of the energy storage; This indicates the planned energy storage configuration capacity.

6. The shared energy storage configuration method based on hybrid game theory as described in claim 1, characterized in that, The energy sharing constraints include: ； ； in, This indicates the upper limit of the shared electricity capacity of the new energy power station cluster; Indicates new energy power station Towards new energy power stations Energy supply, Indicates new energy power station Towards new energy power stations Energy supply, Indicates the status of the battery level, 1 indicates Towards Energy supply, 0 indicates Towards Energy supply.

7. A shared energy storage configuration device based on hybrid game theory, characterized in that, include: The module includes a data acquisition module, a constraint construction module, a master-slave game model construction module, an energy storage call plan output module, and an adjustment module. The data acquisition module is used to acquire fixed cost data of energy storage power stations, performance data of energy storage power stations, service unit price data of energy storage power stations, shared power capacity limit of new energy power station clusters, load forecast data of new energy power stations, and power curtailment penalty cost of new energy power station clusters; the constraint construction module is used to construct energy storage system power constraints, energy storage system capacity constraints, energy storage service unit cost constraints, energy storage charging and discharging constraints, energy storage capacity constraints, new energy output constraints, energy sharing constraints, and power balance constraints based on the acquired data. The master-slave game model construction module is used to construct an upper-level shared energy storage power station model in the master-slave game model based on the acquired data, with energy storage service electricity price, energy storage configuration capacity and energy storage configuration power as decision variables; and to construct a lower-level new energy power station cluster model in the master-slave game model based on the acquired data, with the goal of minimizing the total cost of the new energy power station cluster. The energy storage dispatch plan output module is used to initialize decision variables under the constraints of energy storage system power, energy storage system capacity, and energy storage service unit cost when the upper-layer shared energy storage power station model is performing game calculation for the first time, and then transmit the initialized decision variables to the lower-layer new energy power station cluster model. When the upper-level shared energy storage power station model is not being used for the first game calculation, the upper-level shared energy storage power station model is solved based on the charging and discharging power, cost data, performance data, and service unit price data of each new energy power station obtained after the previous game calculation of the lower-level shared energy storage power station. This yields updated decision variables, and it is determined whether the differences between the decision variables before and after the update in this game calculation are all less than the corresponding preset thresholds. If so, stop the game theory calculation and output the final energy storage and utilization plan. If not, the updated decision variables will be passed to the lower-level shared energy storage power station; Based on the decision variables, performance data, shared power limit of the new energy power station cluster, load forecast data of the new energy power station, and the power curtailment penalty cost of the new energy power station cluster, the lower-level shared energy storage power station model is solved under the constraints of energy storage charging and discharging, energy storage capacity, new energy output, energy sharing, and power balance to obtain the updated charging and discharging power of each new energy power station during energy storage. The updated charging and discharging power of each new energy power station during energy storage is then transferred to the updated charging and discharging power of each new energy power station during energy storage. The energy storage dispatch plan includes the energy storage service price of the shared energy storage power station, the rated charging and discharging power of the shared energy storage power station, the rated capacity of the energy storage power station, and the charging and discharging power of each new energy power station during energy storage. The adjustment module is used to adjust the energy storage power station and the new energy power station cluster according to the energy storage dispatch plan.

8. A device, characterized in that, include: One or more processors; A memory, coupled to the processor, for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the shared energy storage configuration based on hybrid game theory as described in any one of claims 1-6.

9. A medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the shared energy storage configuration based on hybrid game theory as described in any one of claims 1-6.

Images