Multi-source game joint frequency modulation method and system based on energy storage leadership

Abstract

The application discloses a kind of multi-source game joint frequency modulation method and system based on energy storage leadership, belong to energy storage power grid technical field, including: determining the frequency modulation parameter of multiple frequency modulation sources, constructs multi-source frequency modulation system model;Obtain grid side data;Based on grid side data, using game decision model selects energy storage in multi-source frequency modulation system model as leader, makes initial decision;Other frequency modulation sources are as follower according to the decision of leader and make decision;Leader predicts the best decision of follower, changes the best decision, replaces initial decision;Follower changes the best decision of itself according to the best decision of leader, game reaches Nash equilibrium, obtains the frequency modulation instruction of best decision set;Output the frequency modulation instruction of best decision set.The method of the application can control the frequency modulation power between each frequency modulation source, reduce frequency modulation cost, improve frequency modulation economic benefit.

Description

Technical Field

[0001] This invention belongs to the field of energy storage grid technology, specifically relating to a multi-source game-based joint frequency regulation method and system based on energy storage leadership. Background Technology

[0002] With the development of new energy power systems, the proportion of wind and solar power connected to the grid is gradually increasing. However, the output of wind and solar power is greatly affected by meteorological factors and is highly volatile, posing a challenge to the grid frequency regulation system due to the uncertainty of output.

[0003] In recent years, the participation of energy storage systems in the frequency regulation market has gradually become a research hotspot. Electrochemical energy storage has the characteristics of fast charging and discharging speed, short response time and high precision, and can provide fast and accurate active power support for grid frequency changes.

[0004] Existing energy storage technologies for secondary frequency regulation are mainly focused on energy storage assisting thermal power and wind power frequency regulation, using methods such as particle swarm optimization or fuzzy control to optimize frequency regulation benefits. However, there is limited research on multi-source frequency regulation system models that simultaneously involve wind power, photovoltaic power, thermal power, and energy storage systems. How to leverage the advantages of energy storage in frequency regulation and coordinate the output of multiple frequency regulation sources is a key area requiring further research. Summary of the Invention

[0005] To coordinate the output of multiple frequency regulation sources and optimize the economic benefits of energy storage systems participating in multi-source frequency regulation system models, this invention provides a multi-source game-theoretic joint frequency regulation method and system led by energy storage. This method can control the frequency regulation power among various frequency regulation sources, reduce frequency regulation costs, and improve the economic benefits of frequency regulation.

[0006] The objective of this invention is achieved at least through the following technical solutions:

[0007] In a first aspect, the present invention provides a multi-source game-based joint frequency regulation method based on energy storage leadership, comprising:

[0008] Determine the frequency modulation parameters of the multiple frequency modulation sources and construct a multi-source frequency modulation system model;

[0009] Acquire grid-side data;

[0010] Based on grid-side data, a game-theoretic decision-making model is used to select energy storage as the leader in the multi-source frequency regulation system model and make an initial decision; other frequency regulation sources act as followers and make decisions based on the leader's decision; the leader predicts the followers' best decisions, changes the best decisions, and replaces the initial decisions; the followers change their own best decisions based on the leader's best decisions, and the game reaches a Nash equilibrium, obtaining the frequency regulation instructions of the optimal decision set.

[0011] Output the frequency modulation command for the optimal decision set.

[0012] As a further improvement of the present invention, the multi-source frequency regulation system model selects thermal power units, wind power units, photovoltaic systems, hydropower units and energy storage systems as frequency regulation sources.

[0013] As a further improvement of the present invention, the multi-source frequency regulation system model includes unit output constraints, output time constraints, energy storage SOC constraints, power flow constraints, and node voltage constraints:

[0014]

[0015]

[0016]

[0017] Where P is the output of the frequency modulation module, and P is the lower limit of the output of the corresponding module. The upper limit of the output of the corresponding module; t represents the output period of the frequency modulation system, t s The time when the frequency modulation system starts to output power; t e The time when the frequency regulation system finishes outputting power; S and ΔS represent the SOC value and change of the energy storage unit, respectively; P c P d These represent the charging power and discharging power of the energy storage unit, respectively; η c η d These represent charging efficiency and discharging efficiency, respectively; Δt is the frequency modulation time step; E rate S represents the rated power of the energy storage unit. min S max These represent the lower and upper limits of SOC, respectively.

[0018] In the multi-source frequency regulation system model, power flow constraints and node voltage constraints of the power grid system are also considered:

[0019]

[0020] -θ j.max ≤θ j,t ≤θ j.max

[0021] θ ref,t =0

[0022]

[0023] Where, θ l,t θ j,t Let θ be the voltage phase angle at points l and j; j,max The phase angle limit; θ ref,t f is the phase angle at the equilibrium node; lj,t D represents the power flow of line (l,j), with positive and negative values ​​indicating the direction of the power flow; j,tLet G be the power load demand of node j; G be the set of generating units connected to node j; and F and E be the sets of lines starting and ending at node j, respectively.

[0024] As a further improvement of the present invention, the frequency modulation parameters of the multiple frequency modulation sources include the unit frequency modulation cost, frequency modulation output upper and lower limits, output time period, energy storage SOC upper and lower limits, and energy storage charging and discharging efficiency of each frequency modulation source.

[0025] As a further improvement of the present invention, the unit frequency modulation cost of each frequency modulation source includes:

[0026] The unit frequency regulation cost of thermal power units is described by a quadratic function of unit bias power:

[0027]

[0028] Where a1 is the cost increase coefficient for power offset of thermal power units; P g,t Let t be the frequency-regulated active power supplied by the thermal power unit at time t;

[0029] The cost of frequency regulation for wind turbines is mainly due to the need to change the rotor speed of the wind turbine to deviate from the fixed mechanical torque provided by the current wind speed for additional power. The unit cost of frequency regulation is expressed as:

[0030]

[0031] Where a2 is the cost increase coefficient for wind turbine power offset; P wind,t Let t be the frequency-regulated active power supplied by the wind turbine at time t;

[0032] The unit frequency regulation cost of a photovoltaic system is expressed as:

[0033]

[0034] Where a3 is the photovoltaic system power bias cost increase coefficient; P PV,t Let t be the frequency-modulated active power supplied by the photovoltaic system at time t;

[0035] The unit frequency regulation cost of an energy storage system is expressed as:

[0036]

[0037] Where a4 is the cost factor increased due to additional charging and discharging; a5 is the cost factor increased due to SOC transfer; P ESS,t The frequency-regulating active power supplied by the energy storage system at time t; SOC t SOC0 and SOC0 represent time t and the initial state of charge, respectively.

[0038] As a further improvement of the present invention, the grid-side data includes automatic generation system frequency regulation commands, historical regional control errors, and frequency deviations.

[0039] As a further improvement of the present invention, the game-theoretic decision-making model uses game theory to optimize the allocation of multi-source frequency regulation power, with energy storage acting as the leader to coordinate the multi-source frequency regulation system model and make initial decisions. L s L ∈S L S L This serves as a set of alternative decisions for leaders.

[0040] As a further improvement of the present invention, the other frequency modulation sources, acting as followers, make decisions based on the leader's decisions, including:

[0041] The decision of the i-th follower frequency modulation source is s F.i s F.i ∈S F.i， S F.i Let i be the set of alternative decision sources for the i-th follower frequency modulation source, and let the follower's policy set be represented as:

[0042]

[0043] Among them, U F.i (s L ,s F.i Let x be the profit function of the i-th follower; L For leaders in decision-making L Frequency modulation power below; x F.i For the i-th follower in decision s F.i The frequency modulation power below; c F.i P(x) represents the unit frequency modulation cost of the i-th follower. L ,x F.i Let be the demand function, reflecting the relationship between the demand for a commodity and its price, expressed as:

[0044]

[0045] Where C1 and C2 are demand parameters, C1>0, C2>0; N F For the number of followers; U F.i (s L ,s F.i Updated to:

[0046]

[0047] Among them, s F.i ' is the leader's prediction of the best decision for the i-th follower, s F.i ′∈S F.i ; Optimal frequency modulation power of the i-th follower for:

[0048]

[0049] As a further improvement of the present invention, the leader predicts the best decision of the followers, changes the best decision, and replaces the initial decision, including:

[0050] The leader predicted the optimal decision s of the i-th follower in advance. F.i ′(s F.i ′∈S F.i ′) and profit function U F.i (s L ,s F.i ′), the leader according to s F.i Make the best decision L ′(s L ′∈S L Replace previous decisions L At this point, the leader's profit function is:

[0051]

[0052] Among them, c L The unit frequency modulation cost for the leader; the optimal frequency modulation power for the leader is:

[0053]

[0054] Without considering power loss, the power balance constraint can be expressed as:

[0055]

[0056] Where u is the total frequency modulation command;

[0057] The best output of leaders Based on the above two equations, it can be expressed as follows:

[0058]

[0059] As a further improvement to the present invention, the follower changes its own optimal decision based on the leader's optimal decision, and the game reaches a Nash equilibrium, including: the i-th follower updates its own optimal output according to the above formula:

[0060]

[0061] When the leader and followers determine their outputs based on the above two equations, the game reaches a Nash equilibrium.

[0062] As a further improvement of this invention, the game-theoretic decision-making model is used in power systems with multiple followers. The game process is divided into sequential game and simultaneous game. In the sequential game, the energy storage system, as the sole leader, formulates a frequency regulation strategy based on the followers' needs and the overall frequency regulation command. In the simultaneous game, after the leader determines the frequency regulation output, the followers' frequency regulation sources have no order; all followers believe that the output of other followers is fixed, and the followers' decision-making behavior is simultaneous competition. In the game, the final decisions made by the leader and followers are expressed as follows:

[0063]

[0064] in, It is the leader's optimal decision set; S *F.i It is the optimal decision set for the i-th follower; s L It is the leader's decision; S L It is the set of optional decisions for the leader; S F.i U is the set of optional decisions for the i-th follower; L+F It is the total profit of leaders and followers; This is the best strategy for leaders; *F.i is the optimal strategy adopted by the i-th follower; n is the number of followers.

[0065] As a further improvement of the present invention, the execution module executes the optimal frequency regulation command by controlling the speed regulation mechanism of the thermal power unit, the unit controller, the virtual inertia and droop control system of the wind turbine, the photovoltaic load reduction control system, and the energy storage battery energy management system.

[0066] As a further improvement of the present invention, the execution process of the execution module includes:

[0067] In wind power systems, wind turbine generators combine inverters with virtual inertia control algorithms to regulate the frequency of synchronous generators. Virtual synchronous generators control synchronous generators by embedding the rotor motion equations, reactive power droop control, and electromagnetic control algorithms of synchronous generators into the inverters.

[0068] In photovoltaic systems, load shedding control is used to deviate from the maximum power point, thus ensuring that the photovoltaic system has reserve capacity.

[0069] In energy storage systems, the energy management system for lithium batteries is used for real-time monitoring, fault diagnosis, and charge / discharge control.

[0070] Secondly, the present invention provides a multi-source game-based joint frequency regulation system based on energy storage leadership, comprising: a data acquisition module, a decision-making module, and an execution module;

[0071] The data acquisition module includes a power grid status data acquisition device; the power grid status data acquisition device collects and calculates power grid frequency deviation and regional control error in real time.

[0072] The decision-making module is used to construct a game model based on real-time data transmitted by the data acquisition module, with energy storage as the leader and other frequency regulation sources as followers, dynamically allocate the total frequency regulation power command to each frequency regulation source, and input the optimal decision set into the execution module.

[0073] The execution module includes a thermal power unit frequency control system, a wind turbine virtual inertia control system, a photovoltaic system load shedding control system, and an energy storage battery energy management system. The execution module controls the frequency regulation output of the thermal power unit, wind turbine, photovoltaic system, and energy storage system based on the optimal decision set input by the decision module, and completes secondary frequency regulation optimization control.

[0074] Thirdly, the present invention provides a multi-source game-theoretic joint frequency regulation device based on energy storage leadership, comprising:

[0075] The module is used to determine the frequency modulation parameters of multiple frequency modulation sources and build a multi-source frequency modulation system model;

[0076] The acquisition module is used to acquire data from the power grid side.

[0077] The game theory module is used to select energy storage as the leader in the multi-source frequency regulation system model based on grid-side data and a game decision model to make an initial decision; other frequency regulation sources act as followers and make decisions based on the leader's decision; the leader predicts the followers' best decisions, changes the best decisions, and replaces the initial decisions; the followers change their own best decisions based on the leader's best decisions, and the game reaches Nash equilibrium, obtaining the frequency regulation instructions of the optimal decision set.

[0078] The output module is used to output the frequency modulation command of the optimal decision set to the execution module.

[0079] Fourthly, the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the multi-source game-theoretic joint frequency modulation method based on energy storage leadership.

[0080] Fifthly, the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the multi-source game-theoretic joint frequency modulation method based on energy storage leadership. Compared with the prior art, the beneficial effects of the present invention are as follows:

[0081] This invention presents a multi-source game-theoretic joint frequency regulation method based on energy storage leadership. This method, grounded in game theory, designates the energy storage system as the leader and other frequency regulation sources as followers. The optimal frequency regulation decision set is determined through sequential and simultaneous game-theoretic interactions between the leader and followers, optimizing the allocation of AGC (Automatic Generation Control) frequency regulation commands. An execution module controls the frequency regulation power among the various sources, reducing frequency regulation costs and increasing economic benefits. Attached Figure Description

[0082] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following description is provided with accompanying drawings of the relevant technical solutions in the embodiments of the present invention or the prior art. It should be understood that the accompanying drawings described below are only for the purpose of clearly illustrating some embodiments of the technical solutions of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0083] Figure 1 This is the overall workflow of the multi-source joint frequency regulation system with energy storage leadership in this invention;

[0084] Figure 2 This is the wiring diagram of the IEEE 39 model used in this embodiment of the invention;

[0085] Figure 3 This is a schematic diagram of the multi-source game-theoretic joint frequency regulation system structure led by the energy storage leader in this embodiment of the invention;

[0086] Figure 4 This is a schematic diagram of game theory in multi-source frequency modulation in an embodiment of the present invention;

[0087] Figure 5 This is a comparison of frequency modulation power allocation in an embodiment of the present invention (20MW);

[0088] Figure 6 This is the benefit curve of thermal power and multi-source frequency regulation in the embodiments of the present invention;

[0089] Figure 7 This is a schematic diagram of the frequency control system of a thermal power unit in an embodiment of the present invention;

[0090] Figure 8 This is a schematic diagram of the virtual synchronous machine topology in the virtual inertia control of wind turbine units in an embodiment of the present invention;

[0091] Figure 9 This is a schematic diagram of wind turbine sag control in an embodiment of the present invention;

[0092] Figure 10 This is a schematic diagram of the photovoltaic load reduction principle in an embodiment of the present invention;

[0093] Figure 11Here is a flowchart of a multi-source game-based joint frequency regulation method based on energy storage leadership, as provided in an embodiment of the present invention.

[0094] Figure 12 This invention provides a multi-source game-theoretic joint frequency modulation device based on energy storage leadership;

[0095] Figure 13 This is a schematic diagram of an electronic device provided by the present invention. Detailed Implementation

[0096] The embodiments of the present invention are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention. The step numbers in the following embodiments are set only for ease of explanation, and there is no limitation on the order between the steps. The execution order of each step in the embodiments can be adaptively adjusted according to the understanding of those skilled in the art.

[0097] In the description of this invention, "several" means one or more, "more than" means two or more, "greater than," "less than," and "exceeding" are understood to exclude the stated number, while "above," "below," and "within" are understood to include the stated number. The use of "first" and "second" in the description is merely for distinguishing technical features and should not be construed as indicating or implying relative importance, or implicitly indicating the number of indicated technical features, or implicitly indicating the order of the indicated technical features.

[0098] In the description of this invention, unless otherwise explicitly defined, terms such as "setting," "installing," and "connecting" should be interpreted broadly, and those skilled in the art can reasonably determine the specific meaning of the above terms in this invention in conjunction with the specific content of the technical solution.

[0099] like Figure 11 As shown, the first objective of this invention is to provide a multi-source game-theoretic joint frequency regulation method based on energy storage leadership, comprising:

[0100] S100, determine the frequency modulation parameters of the multiple frequency modulation sources and construct a multi-source frequency modulation system model;

[0101] S200, acquires grid-side data;

[0102] S300, based on grid-side data, uses a game-theoretic decision-making model to select energy storage as the leader in the multi-source frequency regulation system model and make an initial decision; other frequency regulation sources, as followers, make decisions based on the leader's decision; the leader predicts the followers' best decisions, changes the best decisions, and replaces the initial decisions; the followers change their own best decisions based on the leader's best decisions, and the game reaches a Nash equilibrium, obtaining the frequency regulation command of the optimal decision set.

[0103] S400, output the frequency modulation instruction of the optimal decision set to the execution module.

[0104] In the decision-making process, the energy storage system is regarded as the leader, and other frequency regulation sources such as wind, solar and thermal power are regarded as followers. The frequency regulation output allocation of the system is optimized through the sequential game between the leader and the followers and the simultaneous game between the followers, thereby increasing the economic benefits of the multi-source frequency regulation system.

[0105] In particular, it can control the frequency regulation power between various frequency regulation sources in multi-source frequency regulation system models that involve wind power, photovoltaic, thermal power and energy storage systems simultaneously.

[0106] The complete technical solution of the present invention will be described in detail below with reference to the accompanying drawings and embodiments:

[0107] This invention provides a multi-source game-theoretic joint frequency regulation method based on energy storage leadership, comprising the following steps:

[0108] Step S1: Determine the frequency modulation parameters of the multiple frequency modulation sources and construct a multi-source frequency modulation system model;

[0109] As an improvement of the present invention, in step S1, the frequency modulation parameters of the multiple frequency modulation sources include the unit frequency modulation cost, frequency modulation output upper and lower limits, output time period, energy storage SOC upper and lower limits, energy storage charging and discharging efficiency, and other parameters of each frequency modulation source.

[0110] The multi-source frequency regulation system model includes unit output constraints, output time constraints, energy storage SOC constraints, power flow constraints, and node voltage constraints.

[0111] In the multi-source frequency regulation system model, power flow constraints and node voltage constraints of the power grid system must also be considered.

[0112] The frequency regulation cost of thermal power units is mainly due to fuel losses caused by changes in rotor speed and deviation of the unit's output power from the optimal operating point during frequency regulation, leading to reduced cost-effectiveness. The unit frequency regulation cost is described using a quadratic function of unit offset power.

[0113] The cost of frequency regulation for wind turbines is primarily due to the need to change the rotor speed of the wind turbine to deviate from the fixed mechanical torque provided by the current wind speed for additional power. Generating this additional torque requires a corresponding energy supply and increases mechanical wear on the unit.

[0114] The frequency regulation cost of photovoltaic systems is mainly due to the decrease in battery utilization and accelerated aging caused by load shedding control.

[0115] The frequency regulation cost of energy storage systems mainly comes from the accelerated aging and lifespan reduction of batteries caused by large SOC deviations and high input and output power during battery operation.

[0116] Step S2: The data acquisition module acquires data from the power grid side;

[0117] As an improvement of the present invention, in step S2, the grid-side data includes automatic generation system frequency regulation commands, historical regional control errors, frequency deviations, and other data.

[0118] Step S3: In the game-theoretic decision-making model, Energy Storage, as the leader, first makes the initial decision s. L ;

[0119] As an improvement to this invention, in step S3, the game theory decision model optimizes the allocation of multi-source frequency regulation power using game theory. Since the energy storage system has high frequency regulation accuracy and fast response speed, it acts as the leader, coordinating the multi-source frequency regulation system model and making initial decisions. L s L ∈S L S L A set of alternative decisions for leaders;

[0120] Step S4: Other frequency modulation sources, acting as followers, make decisions based on the leader's decisions. F ;

[0121] As an improvement to the present invention, in step S4, other frequency modulation sources, as followers, make decisions based on the leader's decision. F The decision of the i-th follower frequency modulation source is s. F.i s F.i ∈S F.i， S F.i Let be the set of alternative decision sources for the i-th follower frequency modulation source. The policy set of the follower can be represented as:

[0122]

[0123] Among them, U F.i (s L ,s F.i Let x be the profit function of the i-th follower; L For leaders in decision-making L Frequency modulation power below; x F.i For the i-th follower in decision s F.i The frequency modulation power below; c F.i P(x) represents the unit frequency modulation cost of the i-th follower. L ,x F.iLet be the demand function, reflecting the relationship between the demand for a commodity and its price, expressed as:

[0124]

[0125] Where C1 and C2 are demand parameters, C1>0, C2>0; N F The number of followers. U F.i (s L ,s F.i Updated to:

[0126]

[0127] Among them, s F.i ' is the leader's prediction of the best decision for the i-th follower, s F.i ′∈S F.i The optimal frequency modulation power of the i-th follower. for:

[0128]

[0129] Step S5, the leader predicts the best decisions for the followers. F ′, change the best decision s L ′, replacing the initial decision;

[0130] In step S6, the followers change their own optimal decisions based on the leader's optimal decision, and the game reaches a Nash equilibrium.

[0131] As an improvement to the present invention, in step S5, the leader predicts in advance the optimal decision s of the i-th follower. F.i ′(s F.i ′∈S F.i ′) and profit function U F.i (s L ,s F.i Therefore, the leader is based on s F.i Make the best decision L ′(s L ′∈S L Replace previous decisions L At this point, the leader's profit function is:

[0132]

[0133] Among them, c L The unit frequency modulation cost for the leader. The optimal frequency modulation power for the leader is:

[0134]

[0135] Without considering power loss, the power balance constraint can be expressed as:

[0136]

[0137] Where u is the master frequency modulation command.

[0138] The best output of leaders Based on the above two equations, it can be expressed as:

[0139]

[0140] As an improvement to the present invention, in step S6, the i-th follower updates its optimal output according to the above formula as follows:

[0141]

[0142] When the leader and followers determine their outputs based on the above two equations, the game reaches a Nash equilibrium.

[0143] Game theory applies to power systems with multiple followers. The game process is divided into sequential game and simultaneous game. In sequential game, the energy storage system, as the sole leader, formulates its frequency regulation strategy based on the needs of the followers and the overall frequency regulation command. In simultaneous game, after the leader determines its frequency regulation output, the followers' frequency regulation sources have no order of precedence; all followers believe that the output of other followers is fixed, and their decision-making behavior is simultaneous and competitive.

[0144] Step S7: The execution module controls the wind, solar, hydro, thermal and storage systems to execute the frequency modulation command of the optimal decision set.

[0145] As an improvement of the present invention, in step S7, the execution module executes the optimal frequency regulation command by controlling the speed regulation mechanism of the thermal power unit, the unit controller, the virtual inertia and droop control system of the wind turbine, the photovoltaic load reduction control system, and the energy storage battery energy management system.

[0146] In wind power systems, to ensure sufficient rotational inertia, wind turbines combine inverters with virtual inertia control algorithms to achieve the frequency regulation function of synchronous machines. Virtual synchronous machines achieve similar control characteristics to synchronous generators by embedding the rotor motion equations, reactive power droop control, and electromagnetic control algorithms of synchronous generators into the inverter.

[0147] In photovoltaic (PV) systems, to ensure maximum power generation efficiency, PV systems typically operate in maximum power point tracking (MPPT) mode. However, in this mode, if the grid frequency drops, the PV system cannot provide active power support. Therefore, load shedding control is used to deviate from the maximum power point, allowing the PV system to maintain a certain reserve capacity.

[0148] In energy storage systems, the energy management system for lithium batteries is used for real-time monitoring, fault diagnosis, and charge / discharge control.

[0149] The second objective of this invention is to provide a multi-source game-theoretic joint frequency regulation system led by energy storage, which includes a data acquisition module, a decision-making module, and an execution module.

[0150] The data acquisition module includes a power grid status data acquisition device. This device collects and calculates data such as power grid frequency deviation and regional control error in real time.

[0151] Based on real-time data transmitted by the data acquisition module, the decision-making module constructs a game model with energy storage as the leader and other frequency regulation sources as followers, dynamically allocates the total frequency regulation power command to each frequency regulation source, and inputs the optimal decision set into the execution module.

[0152] The execution module includes a thermal power unit frequency control system, a wind turbine virtual inertia control system, a photovoltaic system load shedding control system, and an energy storage battery energy management system. Based on the optimal decision set input from the decision module, the execution module controls the frequency regulation output of the thermal power unit, wind turbine, photovoltaic system, and energy storage system, completing secondary frequency regulation optimization control and improving the frequency regulation accuracy and speed.

[0153] The system consists of a data acquisition module, a decision-making module, and an execution module. In the decision-making module, the energy storage system is regarded as the leader, and other frequency regulation sources such as wind, solar, and thermal power are regarded as followers. The frequency regulation output allocation of the system is optimized through sequential game between the leader and followers and simultaneous game between followers, thereby increasing the economic benefits of the multi-source frequency regulation system model.

[0154] like Figure 12 As shown, a third objective of this invention is to provide a multi-source game-theoretic joint frequency regulation device based on energy storage leadership, applied to the decision-making module, comprising:

[0155] The module is used to determine the frequency modulation parameters of multiple frequency modulation sources and build a multi-source frequency modulation system model;

[0156] The acquisition module is used to acquire data from the power grid side.

[0157] The game theory module is used to select energy storage as the leader in the multi-source frequency regulation system model based on grid-side data and a game decision model to make an initial decision; other frequency regulation sources act as followers and make decisions based on the leader's decision; the leader predicts the followers' best decisions, changes the best decisions, and replaces the initial decisions; the followers change their own best decisions based on the leader's best decisions, and the game reaches Nash equilibrium, obtaining the frequency regulation instructions of the optimal decision set.

[0158] The output module is used to output the frequency modulation command of the optimal decision set to the execution module.

[0159] like Figure 13 As shown, a fourth objective of this invention is to provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the multi-source game-theoretic joint frequency modulation method based on energy storage leadership.

[0160] A fifth objective of this invention is to provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the multi-source game-theoretic joint frequency regulation method based on energy storage leadership.

[0161] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0162] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0163] Embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0164] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0165] To facilitate understanding of the technical means and objectives of the multi-source game-theoretic joint frequency regulation method and system implementation proposed in this invention, specific details are provided in conjunction with embodiments and accompanying drawings. Obviously, the described embodiments are merely some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without inventive effort should fall within the scope of protection of this invention.

[0166] Figure 1 This describes the overall workflow of the multi-source game-theoretic joint frequency regulation system led by energy storage in this invention. For example... Figure 1 As shown, the multi-source game-theoretic joint frequency regulation method and system for energy storage leadership in this embodiment includes the following steps:

[0167] Step S1: Determine the frequency modulation parameters of the multiple frequency modulation sources and construct a multi-source frequency modulation system model.

[0168] Figure 2 This is the wiring diagram of the IEEE 39 model used in this embodiment of the invention.

[0169] In this embodiment, the multi-source frequency regulation system model selects thermal power units, wind power units, photovoltaic systems, hydropower units, and energy storage systems as frequency regulation sources. For example... Figure 2 As shown, a multi-source collaborative secondary frequency regulation model is constructed based on the IEEE 39-node model. The 10 generator units in the traditional IEEE 39-node model are replaced with 4 thermal power units, 3 wind farms, and 3 photovoltaic systems to form a multi-source collaborative secondary frequency regulation system, which is equipped with 2 energy storage systems.

[0170] In this embodiment, the frequency regulation parameters of the thermal power unit, wind power unit, photovoltaic system and energy storage system include the unit frequency regulation cost of each frequency regulation source, the upper and lower limits of frequency regulation output, the output period, the upper and lower limits of energy storage SOC, and the energy storage charging and discharging efficiency.

[0171] In this embodiment, the multi-source frequency regulation system model includes unit output constraints, output time constraints, and energy storage SOC constraints:

[0172]

[0173]

[0174]

[0175] Among them, P T P W PP P ESS These are the outputs of the thermal, wind, solar, and energy storage frequency modulation modules, respectively. P T , P W , P P , P ESS These are the lower limits of the output of the corresponding modules. These represent the upper limit of output for the corresponding module. t represents the output period of the photovoltaic system. s The time when the photovoltaic system begins to generate power; t e This refers to the time when the photovoltaic system stops outputting power. S and ΔS represent the SOC value and change of the energy storage unit, respectively; P c P d These represent the charging power and discharging power of the energy storage unit, respectively; η c η d These represent charging efficiency and discharging efficiency, respectively; Δt is the frequency modulation time step; E rate S represents the rated power of the energy storage unit. min S max These represent the lower and upper limits of SOC, respectively.

[0176] In the multi-source frequency regulation system model of this embodiment, power flow constraints and node voltage constraints of the power grid system must also be considered:

[0177]

[0178] -θ j.max ≤θ j,t ≤θ j.max

[0179] θ ref,t =0

[0180]

[0181] Where, θ l,t θ j,t Let θ be the voltage phase angle at points l and j; j,max The phase angle limit; θ ref,t f is the phase angle at the equilibrium node; lj,t D represents the power flow of line (l,j), with positive and negative values ​​indicating the direction of the power flow; j,t Let G be the power load demand of node j; G be the set of generating units connected to node j; and F and E be the sets of lines starting and ending at node j, respectively.

[0182] In this embodiment, the frequency regulation cost of thermal power units is mainly due to fuel loss caused by changes in rotor speed during frequency regulation, resulting in a deviation of the unit's output power from the optimal operating point and a reduction in cost-effectiveness. The unit frequency regulation cost is described using a quadratic function of unit bias power:

[0183]

[0184] Where a1 is the cost increase coefficient for thermal power unit power offset, a1 = 1.5; P g,t Let t be the frequency-regulated active power of the thermal power unit at time t.

[0185] The cost of frequency regulation for wind turbines is primarily due to the need to change the rotor speed of the wind turbine to deviate from the fixed mechanical torque provided by the current wind speed for additional power. Generating this additional torque requires a corresponding energy supply and increases mechanical wear on the unit.

[0186]

[0187] Where a2 is the cost increase coefficient for wind turbine power offset, a2 = 0.95; P wind,t Let t be the frequency-regulated active power of the wind turbine at time t.

[0188] The frequency regulation cost of photovoltaic systems is mainly due to the decrease in battery utilization and accelerated aging caused by load shedding control.

[0189]

[0190] Where a3 is the photovoltaic system power bias cost increase coefficient, a3=1; P PV,t Let t be the frequency-modulated active power supplied by the photovoltaic system at time t.

[0191] The frequency regulation cost of energy storage systems mainly comes from the accelerated aging and lifespan reduction of batteries caused by large SOC deviations and high input and output power during battery operation.

[0192]

[0193] Where a4 is the cost factor increased due to additional charging and discharging, a4 = 1.5; a5 is the cost factor increased due to SOC transfer, a5 = 1.5; P ESS,t The frequency-regulating active power supplied by the energy storage system at time t; SOC t Let SOC0 be the initial state of charge at time t, and SOC0 = 0.5.

[0194] In this embodiment, the charge / discharge efficiency η of the energy storage system c η dThe value is 0.94. The maximum charge / discharge capacity of the energy storage system is 50MW, and the maximum capacity is 100MWh. The frequency regulation capacity subsidy is 60 yuan / MW. The unit frequency regulation cost and upper and lower limits of frequency regulation output for various frequency regulation sources are set in the table below.

[0195] Table 1 Parameter settings for various frequency modulation sources

[0196]

[0197]

[0198] Figure 3 This is a schematic diagram of the multi-source game-theoretic joint frequency regulation system structure of the energy storage leader in this embodiment of the invention.

[0199] Step S2: The data acquisition module acquires the frequency modulation command of the AGC system.

[0200] In this embodiment, historical regional control error curves of the US PJM electricity market dataset are collected, with a time resolution of 5 minutes.

[0201] Step S3: Based on grid-side data, a game-theoretic decision-making model is adopted. In this model, energy storage, as the leader, makes the initial decision S. L .

[0202] Figure 4 This is a schematic diagram of game theory in multi-source frequency modulation in an embodiment of the present invention.

[0203] In this embodiment, as Figure 4 As shown, the game theory decision-making model uses game theory to optimize the allocation of multi-source frequency regulation power. Energy storage systems have high frequency regulation accuracy and fast response speed; therefore, the leader coordinates the multi-source frequency regulation system model and makes the initial decision s. L s L ∈S L S L A set of alternative decisions for leaders;

[0204] Step S4: Other frequency modulation sources, acting as followers, make decisions based on the leader's decisions. F .

[0205] In this embodiment, thermal power, wind power, photovoltaic power, and hydropower act as followers and make decisions based on the leader's decisions. F The decision of the i-th follower frequency modulation source is s. F.i s F.i ∈S F.i , i = 1, 2, 3, 4. S F.i Let be the set of alternative decision sources for the i-th follower frequency modulation source. The policy set of the follower can be represented as:

[0206]

[0207] Among them, U F.i (s L ,s F.i Let x be the profit function of the i-th follower; L For leaders in decision-making L Frequency modulation power below; x F.i For the i-th follower in decision s F.i The frequency modulation power below; c F.i P(x) represents the unit frequency modulation cost of the i-th follower. L ,x F.i Let be the demand function, reflecting the relationship between the demand for a commodity and its price, expressed as:

[0208]

[0209] Where C1 and C2 are demand parameters, C1>0, C2>0; N F The number of followers. U F.i (s L ,s F.i Updated to:

[0210]

[0211] Among them, s F.i ' is the leader's prediction of the best decision for the i-th follower, s F.i ′∈S F.i The optimal frequency modulation power of the i-th follower. for:

[0212]

[0213] Step S5, the leader predicts the best decisions for the followers. F ′, change the best decision s L ′, replacing the initial decision.

[0214] In this embodiment, the leader predicts in advance the optimal decision s of the i-th follower. F.i ′(s F.i ′∈S F.i ′) and profit function U F.i (s L ,s F.i Therefore, the leader is based on s F.i Make the best decision L ′(s L ′∈S L Replace previous decisions L At this point, the leader's profit function is:

[0215]

[0216] Among them, c L The unit frequency modulation cost for the leader. The optimal frequency modulation power for the leader is:

[0217]

[0218] Without considering power loss, the power balance constraint can be expressed as:

[0219]

[0220] Where u is the master frequency modulation command.

[0221] The best output of leaders Based on the above two equations, it can be expressed as:

[0222]

[0223] In step S6, the followers change their own optimal decisions based on the leader's optimal decision, and the game reaches a Nash equilibrium.

[0224] In this embodiment, the i-th follower updates its optimal output according to the above formula as follows:

[0225]

[0226] When the leader and followers determine their outputs based on the above two equations, the game reaches a Nash equilibrium.

[0227] In this embodiment, the game process is divided into sequential game and simultaneous game. In the sequential game, the energy storage system, as the sole leader, formulates its frequency regulation strategy based on the followers' needs and the overall frequency regulation command. In the simultaneous game, after the leader determines its frequency regulation output, the followers' frequency regulation sources have no sequential order; all followers believe that the output of other followers is fixed, and their decision-making behavior is simultaneous and competitive. The final decisions made by the leader and followers in the game can be expressed as:

[0228]

[0229] in, It is the leader's optimal decision set; S *F.i It is the optimal decision set for the i-th follower; s L It is the leader's decision; S L It is the set of optional decisions for the leader; S F.i U is the set of optional decisions for the i-th follower; L+F It is the total profit of leaders and followers; This is the best strategy for leaders;*F.i is the optimal strategy adopted by the i-th follower; n is the number of followers.

[0230] Step S7: The execution module controls the wind, solar, hydro, thermal and storage systems to execute the frequency modulation command of the optimal decision set.

[0231] Figure 5 This is a comparison of frequency modulation power allocation in an embodiment of the present invention (20MW); Figure 6 This is the benefit curve of thermal power and multi-source frequency regulation in the embodiments of the present invention; Figure 7 This is a schematic diagram of the frequency control system of a thermal power unit in an embodiment of the present invention. In this embodiment, the execution module executes the optimal frequency regulation command by controlling the speed regulation mechanism of the thermal power unit, the unit controller, the virtual inertia and droop control system of the wind turbine, the photovoltaic load reduction control system, and the energy storage battery energy management system.

[0232] Figure 8 This is a schematic diagram of the virtual synchronous machine topology in the virtual inertia control of wind turbine units in an embodiment of the present invention; Figure 9 This is a schematic diagram of wind turbine droop control in an embodiment of the present invention. In wind power systems, to ensure sufficient rotational inertia, wind turbines achieve frequency regulation functionality similar to synchronous machines by combining inverters with virtual inertia control algorithms. Virtual synchronous machines achieve control characteristics similar to synchronous generators by embedding the rotor motion equations, reactive power droop control, and electromagnetic control algorithms of synchronous generators into the inverter.

[0233] Figure 10 This is a schematic diagram of the photovoltaic load shedding principle in an embodiment of the present invention. In order to ensure maximum power generation efficiency, photovoltaic systems typically operate in maximum power point tracking (MPPT) mode. However, in this mode, if the grid frequency drops, the photovoltaic system cannot provide active power support. Therefore, load shedding control deviates from the maximum power point, allowing the photovoltaic system to retain a certain amount of reserve capacity.

[0234] In energy storage systems, the energy management system for lithium batteries is used for real-time monitoring, fault diagnosis, and charge / discharge control.

[0235] In industrial practice, frequency regulation power is generally allocated according to the proportion of the total installed capacity of each power station, i.e., proportional allocation of adjustable capacity (PROP). In this embodiment, when the secondary frequency regulation power command is 20MW, the results of the two optimized scheduling methods are compared as shown in the figure. Figure 5 As shown, compared with the PROP method, the master-slave game optimization scheduling method reduces the output of thermal power and increases the frequency regulation power of other energy sources, thus increasing the economic benefits of frequency regulation by 3.439%.

[0236] In this embodiment, to verify the superiority of the multi-source frequency regulation method, a comparison is set up between traditional thermal power frequency regulation and multi-source frequency regulation. The secondary frequency regulation requirements of 96 frequency regulation nodes per day are input. Figure 6 The comparison of the revenue curves for the two energy combinations participating in frequency regulation shows that the revenue curve for multi-source coordinated frequency regulation is above that of traditional thermal power. The average frequency regulation revenue of traditional thermal power is 17.334 yuan / h, while the average frequency regulation revenue of multi-source coordinated frequency regulation is 16.545 yuan / h. The revenue of multi-source coordinated frequency regulation is increased by 4.769%.

[0237] This invention employs game theory to optimize the allocation of multi-source frequency modulation power, with energy storage acting as the leader and other frequency modulation sources as followers. The key point of this invention is the idea of ​​obtaining the optimal frequency modulation decision through sequential and simultaneous game play between the leader and followers. It should be noted that the specific preferred embodiments of this invention are only used to clearly illustrate the implementation of the invention and are not intended to limit the scope of protection of this invention. Any improvements or modifications made based on the spirit of this invention should be within the scope of protection of this invention.

[0238] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A multi-source game-theoretic joint frequency regulation method based on energy storage leadership, characterized in that, include: Determine the frequency modulation parameters of the multiple frequency modulation sources and construct a multi-source frequency modulation system model; Acquire grid-side data; Based on grid-side data, a game-theoretic decision-making model is used to select energy storage as the leader in the multi-source frequency regulation system model and make an initial decision; other frequency regulation sources act as followers and make decisions based on the leader's decision; the leader predicts the followers' best decisions, changes the best decisions, and replaces the initial decisions; the followers change their own best decisions based on the leader's best decisions, and the game reaches a Nash equilibrium, obtaining the frequency regulation instructions of the optimal decision set. Output the frequency modulation command for the optimal decision set; The frequency modulation parameters of the multiple frequency modulation sources include the unit frequency modulation cost, upper and lower limits of frequency modulation output, output time period, upper and lower limits of energy storage SOC, and energy storage charging and discharging efficiency of each frequency modulation source. The unit frequency modulation cost of each frequency modulation source includes: The unit frequency regulation cost of thermal power units is described by a quadratic function of unit bias power: in, The factor that increases the cost of power offset in thermal power units; for t The frequency-regulated active power undertaken by the thermal power units at all times; The cost of frequency regulation for wind turbines is mainly due to the need to change the rotor speed of the wind turbine to deviate from the fixed mechanical torque provided by the current wind speed for additional power. The unit cost of frequency regulation is expressed as: in, The cost increase factor for wind turbine power offset; for t The frequency regulation active power undertaken by the wind turbine at any given time; The unit frequency regulation cost of a photovoltaic system is expressed as: in, This adds a factor to the power bias cost of the photovoltaic system; for t The frequency regulation active power undertaken by the photovoltaic system at any given time; The unit frequency regulation cost of an energy storage system is expressed as: in, This is due to the increased cost factor resulting from additional charging and discharging. This is the cost factor that increases due to the transfer of SOC; for t The frequency regulation active power undertaken by the energy storage system at any time; and They are respectively t Time and initial state of charge.

2. The multi-source game-based joint frequency regulation method based on energy storage leadership according to claim 1, characterized in that, The multi-source frequency regulation system model selects thermal power units, wind power units, photovoltaic systems, hydropower units, and energy storage systems as frequency regulation sources.

3. The multi-source game-based joint frequency regulation method based on energy storage leadership according to claim 1, characterized in that, The multi-source frequency regulation system model includes unit output constraints, output time constraints, energy storage SOC constraints, power flow constraints, and node voltage constraints. in, P For the output of the frequency modulation module, This represents the lower limit of the output of the corresponding module. This represents the maximum output capacity of the corresponding module; t This represents the power output period of the frequency modulation system. t s The time when the frequency modulation system begins to output power; t e This refers to the time when the frequency modulation system stops outputting power. and These represent the SOC value and change of the energy storage unit, respectively. P c , P d These represent the charging power and discharging power of the energy storage unit, respectively. η c , η d These represent charging efficiency and discharging efficiency, respectively; Δ t This is the frequency modulation time step; E rate This represents the rated power of the energy storage unit; S min , S max These represent the lower and upper limits of SOC, respectively. In the multi-source frequency regulation system model, power flow constraints and node voltage constraints of the power grid system are also considered: in, , For point l , j The voltage phase angle; Phase angle limit; The phase angle of the balancing node; For the line The power flow is represented by positive and negative values, indicating the direction of the power flow. For nodes j Electricity load demand; For nodes j The set of connected generating units; and Each is based on a node j A set of routes with a starting point and an ending point.

4. The multi-source game-based joint frequency regulation method based on energy storage leadership according to claim 1, characterized in that, The grid-side data includes automatic generation system frequency regulation commands, historical regional control errors, and frequency deviations.

5. The multi-source game-based joint frequency regulation method based on energy storage leadership according to claim 1, characterized in that, The game-theoretic decision-making model uses game theory to optimize the allocation of multi-source frequency regulation power. Energy storage acts as the leader, coordinating the multi-source frequency regulation system model and making initial decisions. s L , s L S L , S L This serves as a set of alternative decisions for leaders.

6. The multi-source game-based joint frequency regulation method based on energy storage leadership according to claim 1, characterized in that, The other frequency modulation sources, acting as followers, make decisions based on the leader's decisions, including: No. i The decision of a follower frequency source is s F.i , s F.i S F.i， S F.i For the first i The set of alternative decision points for each follower frequency source is represented as follows: in, U F.i ( s L , s F.i ) is the first i The profit function of each follower; x L For leaders in decision-making s L Frequency modulation power; x F.i For the first i A follower in decision-making s F.i Frequency modulation power; c F.i For the first i The unit frequency modulation cost per follower; P ( x L , x F.i Let be the demand function, reflecting the relationship between the demand for a commodity and its price, expressed as: in, C 1, C 2 represents the requirement parameter. C 1>0, C 2>0; N F The number of followers; U F.i ( s L , s F.i Updated to: Among them, s F.i ´The first prediction for leaders i The best decision for each follower, s F.i ´ S F.i ;No. i The best FM power for each follower x Fi is: 。 7. The multi-source game-based joint frequency regulation method based on energy storage leadership according to claim 1, characterized in that, The leader predicts the best decision for the followers, changes the best decision, and replaces the initial decision, including: The leader predicted the first i The best decisions for each follower F.i ´( s F.i ´ S F.i ´) and profit function U F.i ( s L , s F.i ´), the leader according to s F.i Make the best decision s L ´( s L ´ S L Replace previous decisions s L At this point, the leader's profit function is: in, c L The unit frequency modulation cost for the leader; the optimal frequency modulation power for the leader is: Without considering power losses, the power balance constraint is expressed as: in, u This is the master frequency modulation command; The best output of leaders x L can be expressed as follows based on the above two equations: 。 8. The multi-source game-based joint frequency regulation method based on energy storage leadership according to claim 7, characterized in that, The followers change their optimal decisions based on the leader's optimal decisions, and the game reaches a Nash equilibrium, including: i Each follower updates its optimal output according to the above formula: When the leader and followers determine their outputs based on the above two equations, the game reaches a Nash equilibrium.

9. The multi-source game-based joint frequency regulation method based on energy storage leadership according to claim 1, characterized in that, The game decision-making model is used in power systems with multiple followers. The game process is divided into sequential game and simultaneous game. In the sequential game, the energy storage system, as the sole leader, formulates a frequency regulation strategy based on the followers and the overall frequency regulation command requirements. In a simultaneous game, once the leader determines their frequency-modulated output, the followers' frequency-modulated sources have no prior order; all followers believe that the output of other followers is fixed, and their decision-making behavior is simultaneous and competitive. The final decisions made by the leader and followers in this game are represented as follows: in, It is the leader's optimal decision set; It is the first i The optimal decision set for each follower; s L It is the leader's decision; S L It is the set of optional decisions for leaders; S F.i It is the first i The set of optional decisions for each follower; U L+F It is the total profit of leaders and followers; n It refers to the number of followers.

10. A multi-source game-theoretic joint frequency regulation system based on energy storage leadership, characterized in that, include: Data acquisition module, decision-making module, and execution module; The data acquisition module includes a power grid status data acquisition device; The power grid status data acquisition device collects and calculates power grid frequency deviation and regional control error in real time. The decision module executes the multi-source game-theoretic joint frequency regulation method based on energy storage leadership as described in any one of claims 1-9. It is used to construct a game model based on real-time data transmitted by the data acquisition module, with energy storage as the leader and other frequency regulation sources as followers, dynamically allocate the total frequency regulation power command to each frequency regulation source, and input the optimal decision set into the execution module. The execution module includes a thermal power unit frequency control system, a wind turbine virtual inertia control system, a photovoltaic system load shedding control system, and an energy storage battery energy management system. The execution module controls the frequency regulation output of thermal power units, wind power units, photovoltaic systems and energy storage systems based on the optimal decision set input by the decision module, and completes secondary frequency regulation optimization control.

11. The multi-source game-theoretic joint frequency regulation system based on energy storage leadership according to claim 10, characterized in that, The execution module executes optimal frequency regulation commands by controlling the speed regulation mechanism and unit controller of the thermal power unit, the virtual inertia and droop control system of the wind turbine unit, the photovoltaic load reduction control system, and the energy storage battery energy management system.

12. The multi-source game-theoretic joint frequency regulation system based on energy storage leadership according to claim 10, characterized in that, The execution process of the execution module includes: In wind power systems, wind turbine generators combine inverters with virtual inertia control algorithms to regulate the frequency of synchronous generators. Virtual synchronous generators control synchronous generators by embedding the rotor motion equations, reactive power droop control, and electromagnetic control algorithms of synchronous generators into the inverters. In photovoltaic systems, load shedding control is used to deviate from the maximum power point, thus ensuring that the photovoltaic system has reserve capacity. In energy storage systems, the energy management system for lithium batteries is used for real-time monitoring, fault diagnosis, and charge / discharge control.

13. A multi-source game-theoretic joint frequency regulation device based on energy storage leadership, comprising the multi-source game-theoretic joint frequency regulation method based on energy storage leadership as described in any one of claims 1-9, characterized in that, include: The module is used to determine the frequency modulation parameters of multiple frequency modulation sources and build a multi-source frequency modulation system model; The acquisition module is used to acquire data from the power grid side. The game theory module is used to select energy storage as the leader in the multi-source frequency regulation system model based on grid-side data and a game decision model to make an initial decision; other frequency regulation sources act as followers and make decisions based on the leader's decision; the leader predicts the followers' best decisions, changes the best decisions, and replaces the initial decisions; the followers change their own best decisions based on the leader's best decisions, and the game reaches Nash equilibrium, obtaining the frequency regulation instructions of the optimal decision set. The output module is used to output the frequency modulation command of the optimal decision set to the execution module.

14. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the multi-source game-theoretic joint frequency regulation method based on energy storage leadership as described in any one of claims 1-9.

15. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the multi-source game-based joint frequency regulation method based on energy storage leadership as described in any one of claims 1-9.

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