Demand side response-oriented heterogeneous energy storage system distributed control method

Abstract

The invention relates to the field of heterogeneous energy storage system distributed control, in particular to a demand side response-oriented heterogeneous energy storage system distributed control method, which comprises the following steps of: clustering equipment units of a heterogeneous energy storage system according to electrical characteristics; setting the number of clusters, an adjacent matrix and a leader matrix; parameters and characteristic coefficients of the heterogeneous energy storage system are set; initializing parameters and states of follower agents in each cluster; setting parameters of each cluster leader agent; a system operator gives target power, and a leader agent judges a target power symbol; setting control parameters; each agent in each cluster regulates and controls the power of the equipment unit, and each agent updates the own state; through iteration for a certain time, a target power regulation and control task is completed, and the user experience in the power distribution network is improved while the electric energy quality is improved.

Description

Technical Field

[0001] The present invention relates to the field of distributed control of heterogeneous energy storage systems, and in particular to a distributed control method of heterogeneous energy storage systems oriented to demand-side response. Background Art

[0002] In recent years, with the rapid development of renewable energy, its environmental protection and sustainability advantages have been favored by urban distribution networks, and a considerable amount of renewable energy has been added to more and more distribution networks. However, due to the high penetration rate and instability of renewable energy, the power fluctuation of the distribution network will be aggravated. Therefore, it is necessary to design a reasonable energy storage system for power balance of the power grid. Previous studies have shown that adding energy storage batteries to the power grid can effectively alleviate the negative effects of renewable energy on the power grid. These energy storage batteries can artificially adjust the power according to the power supply and demand of the power grid. Through operator instructions, power can be input or output to the distribution network, thereby effectively reducing the power fluctuation of the power grid. On the other hand, many flexible loads in the power grid can also adjust their own energy consumption according to the power demand, reduce their own power demand during peak power consumption, and increase their own power demand during low power consumption, thereby effectively balancing the power of the power grid. In addition, some buildings with heat storage capacity can also be added to the distribution network as a special energy storage facility. These different types of batteries, flexible loads and buildings together constitute a heterogeneous energy storage system in the power grid. Reasonable control of heterogeneous energy storage systems can effectively improve power fluctuations in the power grid and enhance the stability and security of the power grid.

[0003] It is worth noting that the centralized control of traditional heterogeneous energy storage systems needs to rely on a centralized control center that can obtain global information. This center is not only costly to build, but also has low fault tolerance. When the centralized control center fails, the entire heterogeneous energy storage system will be paralyzed. At the same time, with the development of heterogeneous energy storage systems, the communication network topology of heterogeneous energy storage systems has become more and more complex. The traditional centralized control method can no longer meet the working requirements of heterogeneous energy storage systems. On the other hand, due to their own working parameters and other reasons, each energy storage battery and flexible load may have problems such as overcharge and over discharge under the traditional power control method. These problems greatly reduce the service life of these energy storage batteries and flexible loads, and cause a series of problems such as voltage anomalies and energy waste in the distribution network. On this basis, the distributed control of heterogeneous energy storage systems came into being. Compared with the traditional centralized method, this distributed control method does not require a centralized control center, has the advantages of more flexibility, high fault tolerance and high efficiency, can effectively reduce the operating cost of heterogeneous energy storage systems, and improve the efficiency of power resource scheduling. Summary of the invention

[0004] The purpose of the present invention is to provide a distributed control method for a heterogeneous energy storage system based on demand-side response to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0006] A distributed control method for a heterogeneous energy storage system for demand-side response, the method comprising:

[0007] S100, clustering each device unit of the heterogeneous energy storage system according to electrical characteristics; setting the number of clusters, adjacency matrix and leader matrix;

[0008] S200, setting parameters and characteristic coefficients of the heterogeneous energy storage system;

[0009] S300, initializing the parameters and states of the follower agents in each cluster;

[0010] S400, setting parameters of the leader agent of each cluster;

[0011] S500, the system operator gives a target power, and the leader agent determines the sign of the target power;

[0012] S600, setting control parameters;

[0013] S700, each intelligent agent in each cluster regulates the power of the equipment unit, and each intelligent agent updates its own state;

[0014] S800: After a certain period of iteration, the target power control task is completed.

[0015] Preferably, S100 includes:

[0016] S101, dividing the equipment units of the heterogeneous energy storage system into three homogeneous clusters according to their electrical characteristics, namely: a battery cluster, a flexible load cluster and a building cluster;

[0017] S102, equipping each heterogeneous energy storage system equipment unit with an intelligent agent, which can monitor and adjust the status of the heterogeneous energy storage system unit and perform communication functions, and the above intelligent agents serve as follower intelligent agents;

[0018] S103, each cluster sets a leader agent, which is responsible for collecting the status of follower agents, regulating its own status and performing communication functions;

[0019] S104, setting the number of energy storage batteries N1, the number of flexible loads N2 and the number of buildings N3;

[0020] S105, according to the communication topology within each cluster, set the adjacency matrix A of the agents within each cluster = [a ij ], if there is a communication connection between the i-th agent and the j-th agent, then a ij =1, otherwise a ij= 0; Set the leader matrix B = diag{a i0}, if the i-th agent can obtain information from the leader agent, then a i0 =1, otherwise a i0 =0.

[0021] Preferably, S200, setting parameters and characteristic coefficients of the heterogeneous energy storage system, includes:

[0022] Set the parameters and characteristic coefficients of the heterogeneous energy storage system,

[0023] in, are the capacity and coulomb efficiency of the i1th energy storage battery, is the operating voltage of the i1th energy storage battery; are the maximum input power and maximum output power of the i1th energy storage battery, respectively, and its characteristic coefficient is The i2th is the flexible load capacity; is its maximum working power, and its characteristic coefficient is and are the capacity and Coulomb efficiency of the i3th building, is the maximum operating power of the i3th building, and its characteristic coefficient is is the indoor temperature difference of the i3th building, in Set the maximum and minimum temperatures for the interior of the i3th building respectively.

[0024] Preferably, S300, initializing the parameters and states of the follower agents in each cluster, includes:

[0025] S301, obtain battery cluster intelligent body status in and Represent the state of charge and power of the i1th energy storage battery respectively, then set the initial state in is the initial charge state of the energy storage battery;

[0026] S302: Obtaining the state of the flexible load agent in and The energy state and power of the i2th flexible load are set as the initial state. in is the initial energy state of each flexible load i2;

[0027] S303, obtaining the initial state of the building complex intelligent body in

[0028] and are the temperature state and power of the i3th building respectively, and set the initial time in is the initial energy state of the i3th building.

[0029] Preferably, S400, setting parameters of each cluster leader agent, includes:

[0030] Set the control gain K of each cluster leader agent BESS , K FL , K BBESS ;

[0031] Among them, K BESS , K FL , K BBESS All are constants greater than 0;

[0032] Initialize the leader agent's state to the state of the first follower agent it communicates with;

[0033] The initial state of the leader agent of the battery cluster is: The initial state of the leader agent of the flexible load cluster is: The initial state of the building group leader is:

[0034] Preferably, in S500, the system operator gives a target power, and the leader agent determines the sign of the target power, including:

[0035] The system operator gives the target power P T , the leader agent determines the target power sign. If P T >0, it means that the heterogeneous energy storage system is in the charging state. At this time, each leader agent allocates the target power according to the regulation capability of each cluster. If P T <0, it means that the heterogeneous energy storage system is in a discharging state, and only the battery cluster is involved in the work. in are the total target power of battery cluster, flexible load and building cluster respectively;

[0036] Among them, each leader agent allocates the target power according to the adjustment capability of each cluster. The strategy is:

[0037]

[0038]

[0039] in The total target power is allocated to each cluster respectively, z is the regulation capacity of each heterogeneous energy storage system,

[0040] in is the maximum state of charge of the i1th battery energy storage;

[0041] in is the maximum energy state of the i2th flexible load;

[0042] in The maximum temperature state of the i3rd building.

[0043] Preferably, S600, setting control parameters, includes:

[0044] Set control parameters α1, β1, γ1, α2, β2, γ2, α3, β3, γ3;

[0045] S601, the α1, β1, γ1; Among them, M BESS =L BESS +B BESS , L BESS is the Laplace matrix of the battery cluster follower agent, B BESS is the battery cluster leader matrix, λ min (M BESS ) is the matrix M BESS Minimum eigenvalue;

[0046] S602, the α2, β2, γ2; Among them, M FL =L FL +B FL , L FL is the Laplace matrix of the flexible load follower, B FL is the flexible load leader matrix, λ min (M FL ) is the matrix M FL Minimum eigenvalue;

[0047] S603, the α3, β3, γ3; Among them, M BBESS =L BBESS +B BBESS , L BBESS is the Laplace matrix of the building group follower agent, B BBESS is the building cluster leader matrix, λ min (M BBESS ) is the matrix M BBESS Minimum eigenvalue.

[0048] Preferably, in S700, each agent in each cluster regulates the power of the equipment unit, and each agent updates its own state, including:

[0049] S701, obtain the total target power of the battery cluster, flexible load cluster and building complex obtained in S500, and the intelligent body of each equipment unit in the cluster updates its own state and adjusts the equipment unit power according to the algorithm, and sets the i1th energy storage battery power The power of the i2nd flexible load is The power of the i3th building is

[0050]

[0051] S702, each cluster leader agent updates its own state according to the algorithm:

[0052] A1. The state update rule of the leader agent of the battery cluster is:

[0053] in Can be directly measured by the intelligent agents of each equipment unit of the battery cluster;

[0054] The power control algorithm of the battery cluster follower agent is:

[0055]

[0056] A2. The state update rule of the flexible load leader agent is: in, It can be directly measured by the intelligent agents of each equipment unit of the flexible load cluster;

[0057] The power control algorithm of the flexible load follower agent is:

[0058]

[0059] A3. The update rule of the leader agent of the building group is:

[0060] in It can be directly measured by each intelligent agent in the building complex;

[0061] The power control algorithm of the building group follower agent is:

[0062]

[0063] Preferably, the target power control task in S800 includes:

[0064] Target Power Tracking: Among them, the power is distributed according to the characteristic coefficient ratio:

[0065] Equipment unit status balance:

[0066]

[0067] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the above-mentioned distributed control method for a heterogeneous energy storage system oriented to demand-side response;

[0068] A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps in the above-mentioned distributed control method for a heterogeneous energy storage system oriented to demand-side response are implemented.

[0069] Compared with the prior art, the beneficial effects achieved by the present invention are:

[0070] 1: In the present invention, the target power is allocated based on the adjustment capacity of each cluster of the heterogeneous energy storage system, which avoids overcharging and over-discharging of each equipment unit, realizes more scientific power allocation, and reduces unnecessary energy waste.

[0071] 2: The present invention proposes a distributed control method for a heterogeneous energy storage system oriented to demand-side response, which realizes the consistency of the charge state of each energy storage battery in the heterogeneous energy storage system, the consistency of the energy state of each flexible load and the consistency of the temperature state of each building, further improving the coordinated operation capability of the heterogeneous energy storage system.

[0072] 3: This invention proposes a distributed control method for heterogeneous energy storage systems for demand-side response, which allocates power in each cluster according to the characteristic coefficient ratio, focusing on the aging of equipment units and their own parameters. This power control method improves the stability of heterogeneous energy storage systems, improves the power quality, and improves the user experience in the distribution network. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0074] Figure 1 It is a flow chart of a distributed control method of a heterogeneous energy storage system for demand-side response according to the present invention;

[0075] Figure 2 is a topological diagram of the communication network of the heterogeneous energy storage system described in a specific implementation manner;

[0076] Figure 3 is a trend chart of the regulation capacity of each cluster of the heterogeneous energy storage system in a specific implementation method;

[0077] Figure 4 It is a target power allocation diagram based on the adjustment capacity of each cluster in a specific implementation mode;

[0078] Figure 5 is a state trend diagram of each cluster device unit described in a specific implementation manner;

[0079] Figure 6 It is a power trend diagram of each cluster device unit described in a specific implementation manner. DETAILED DESCRIPTION

[0080] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0081] See also Figure 1-Figure 6 , the present invention provides a technical solution:

[0082] Embodiment 1:

[0083] The present invention assumes that there are three different clusters in a heterogeneous energy storage system, where the number of device units and the communication topology of the three clusters are as follows: Figure 2 The specific implementation steps are as shown in Figure 1 shown.

[0084] (1) Set the communication network topology according to the communication status of the intelligent agents in each cluster, such as Figure 2 The adjacency matrices of the three clusters shown are:

[0085]

[0086] The three leadership matrices are:

[0087]

[0088] (2) Set the parameters and characteristic coefficients of the heterogeneous energy storage system: Set the parameters of each energy storage battery in the battery pack as follows:

[0089] The characteristic coefficients of energy storage batteries are:

[0090] The flexible load characteristic coefficients are: ΔT1=2℃, ΔT2=2℃, ΔT3=2℃, ΔT4=3℃, ΔT5=3℃, The characteristic coefficients of each building are:

[0091] (3) Set the initial state of charge of each energy storage battery in the battery cluster to SOC(0) = [35, 35.5, 36, 36.5] T , the highest state of charge is SOC max =[80,80,90,90] T , initialize the battery cluster agent to the initial state x BESS (0)=SOC(0)=[35,35.5,36,36.5] T ; Set the initial energy state of the flexible load cluster to SOE(0) = [33,33.5,34,34.5] T , the highest energy state is SOE max =[80,80,85,85] T , initialize the initial state of the flexible load cluster agent to x FL (0)=SOE(0)=[33,33.5,34,34.5] T ; Set the initial temperature state of the building complex to SOT(0) = [40, 40.2, 40.8, 41, 41.9] T , the highest temperature state is SOT max =[80,90,90,95,95] T , initialize the building complex agent state x BBESS (0)=SOT(0)=[40,40.2,40.8,41,41.9] T .

[0092] (4) Set the leader control gain: K BESS =0.01, K FL =0.01, K BBESS =0.02. Initialize the state of each cluster leader to

[0093] (5) This method assumes that the system operator gives 6 power signals, each signal has a time interval of 30 minutes, and the first power signal is given at the initial moment. According to the power allocation principle in step 5, when the first power signal When the heterogeneous energy storage system is in the charging state, the power is allocated according to the regulation capability, that is,

[0094] On the contrary, it means that the system is in a discharging state, and only the battery cluster participates in power distribution, that is,

[0095] (6) Set the control parameters as follows:

[0096] γ1=1 / 8, α1=8, β1=2.1, γ2=1 / 5, α2=5, β2=2, γ3=1 / 4, α3=4, β3=2.2.

[0097] (7) Each energy storage battery agent updates its own state according to the following algorithm:

[0098]

[0099] Each intelligent agent regulates the power of the energy storage battery to The leader agent of the battery cluster updates its state according to the following rules:

[0100] Each flexible load agent updates its own state according to the following algorithm:

[0101]

[0102] The power of flexible load controlled by each intelligent agent is: The leader agent of the flexible load cluster updates its state according to the following rules:

[0103] Each building agent updates its own status according to the following algorithm:

[0104]

[0105]

[0106] Each intelligent agent controls the building power as follows: The leader agent of the building group updates its status according to the following rules:

[0107] (8) After time iteration, the target power control task is completed.

[0108] In the above, (5) to (7) is a cyclic process. Different target powers are given in (5), and the same steps are completed in (6) and (7) to achieve the final target task.

[0109] In order to verify the effectiveness of the present invention, a simulation experiment was carried out.

[0110] Figure 3 It shows the regulation capacity of each cluster at each time stage.

[0111] Figure 4 It represents the total target power of each cluster after allocating it by adjusting the capacity of each cluster. Figure 4 It can be seen that the proposed power allocation method can well track the operator's dispatch target power and meet the power supply and demand balance requirements. Figure 3 and Figure 4 It can be seen that the total target power of each cluster is allocated according to the adjustment capacity of each cluster to meet the system requirements.

[0112] Figure 5 It is the status diagram of each cluster device unit. Figure 5 It can be seen that under the proposed distributed control strategy, the states of each device unit in each cluster of the heterogeneous energy storage system can reach a good consensus and meet the system requirements.

[0113] Figure 6 This is a power diagram of each cluster device unit. It can be seen that under the present invention, the power of each device unit strictly abides by its maximum power limit requirement during regulation. After the regulation is completed, each device unit strictly distributes power according to its characteristic coefficient ratio, meeting the safe and scientific regulation requirements for power resources.

[0114] The present invention can ensure that in a heterogeneous energy storage system, each device unit of the system can distribute power strictly in accordance with the characteristic coefficient ratio while taking into account its own parameters and component aging, effectively preventing the system from overcharging and over-discharging, achieving scientific regulation of power resources, and ensuring the smooth and safe operation of the heterogeneous energy storage system.

[0115] Embodiment 2:

[0116] The computer-readable storage medium of this embodiment stores a computer program thereon, and when the program is executed by a processor, the steps in the distributed control method of a heterogeneous energy storage system oriented to demand-side response in Embodiment 1 are implemented.

[0117] The computer-readable storage medium of this embodiment may be an internal storage unit of the terminal, such as a hard disk or memory of the terminal; the computer-readable storage medium of this embodiment may also be an external storage device of the terminal, such as a plug-in hard disk, a smart memory card, a secure digital card, a flash memory card, etc. equipped on the terminal; further, the computer-readable storage medium may also include both an internal storage unit of the terminal and an external storage device.

[0118] The computer-readable storage medium of this embodiment is used to store computer programs and other programs and data required by the terminal. The computer-readable storage medium can also be used to temporarily store data that has been output or is to be output.

[0119] Embodiment 3:

[0120] The computer device of this embodiment includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the steps of a distributed control method for a heterogeneous energy storage system oriented to demand-side response in Embodiment 1 are implemented.

[0121] In this embodiment, the processor may be a central processing unit, or other general-purpose processors, digital signal processors, application-specific integrated circuits, readily available programmable gate arrays or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The memory may include a read-only memory and a random access memory, and provide instructions and data to the processor. A portion of the memory may also include a non-volatile random access memory. For example, the memory may also store information about the device type.

[0122] Those skilled in the art will appreciate that the disclosed content of the embodiments may be provided as methods, systems, or computer program products. Therefore, the present solution may adopt the form of hardware embodiments, software embodiments, or embodiments combining software and hardware. Moreover, the present solution may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) containing computer-usable program codes.

[0123] The present solution is described with reference to the method according to the embodiment of the present solution and the flowchart and / or block diagram of the computer program product. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions; these computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 one or more processes and / or methods Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0124] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 one or more processes and / or methods Figure 1 A function specified in one or more boxes.

[0125] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 one or more processes and / or methods Figure 1 A step that specifies a function in one or more boxes.

[0126] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing related hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM).

[0127] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A distributed control method for heterogeneous energy storage systems oriented to demand-side response, characterized in that: The method comprises: S100, clustering each device unit of the heterogeneous energy storage system according to electrical characteristics; setting the number of clusters, adjacency matrix and leader matrix; S200, setting parameters and characteristic coefficients of the heterogeneous energy storage system; S300, initializing the parameters and states of the follower agents in each cluster; S400, setting parameters of the leader agent of each cluster; S500, the system operator gives a target power, and the leader agent determines the sign of the target power; S600, setting control parameters; S700, each intelligent agent in each cluster regulates the power of the equipment unit, and each intelligent agent updates its own state; S800: After a certain period of iteration, the target power control task is completed.

2. A distributed control method for heterogeneous energy storage systems oriented to demand-side response according to claim 1, characterized in that: The S100 includes: S101, dividing the equipment units of the heterogeneous energy storage system into three homogeneous clusters according to their electrical characteristics, namely: a battery cluster, a flexible load cluster and a building cluster; S102, equipping each heterogeneous energy storage system equipment unit with an intelligent agent, which can monitor and adjust the status of the heterogeneous energy storage system unit and perform communication functions, and the above intelligent agents serve as follower intelligent agents; S103, each cluster sets a leader agent, which is responsible for collecting the status of follower agents, regulating its own status and performing communication functions; S104, setting the number of energy storage batteries N1, the number of flexible loads N2 and the number of buildings N3; S105, according to the communication topology within each cluster, set the adjacency matrix A of the agents within each cluster = [a ij ], if there is a communication connection between the i-th agent and the j-th agent, then a ij =1, otherwise a ij = 0; Set the leader matrix B = diag{a i0 }, if the i-th agent can obtain information from the leader agent, then a i0 =1, otherwise a i0 =0.

3. A distributed control method for heterogeneous energy storage systems oriented to demand-side response according to claim 1, characterized in that: The step S200, setting parameters and characteristic coefficients of the heterogeneous energy storage system, includes: Set the parameters and characteristic coefficients of the heterogeneous energy storage system, in, are the capacity and coulomb efficiency of the i1th energy storage battery, is the operating voltage of the i1th energy storage battery; are the maximum input power and maximum output power of the i1th energy storage battery, respectively, and its characteristic coefficient is The i2th is the flexible load capacity; is its maximum working power, and its characteristic coefficient is and are the capacity and Coulomb efficiency of the i3th building, is the maximum operating power of the i3th building, and its characteristic coefficient is is the indoor temperature difference of the i3th building, in Set the maximum and minimum temperatures for the interior of the i3th building respectively.

4. A distributed control method for heterogeneous energy storage systems oriented to demand-side response according to claim 1, characterized in that: The step S300, initializing the parameters and states of the follower agents in each cluster, includes: S301, obtain battery cluster intelligent body status in and Represent the state of charge and power of the i1th energy storage battery respectively, then set the initial state in is the initial charge state of the energy storage battery; S302: Obtaining the state of the flexible load agent in and The energy state and power of the i2th flexible load are set as the initial state. in is the initial energy state of each flexible load i2; S303, obtaining the initial state of the building complex intelligent body in and are the temperature state and power of the i3th building respectively, and set the initial time in is the initial energy state of the i3th building.

5. A distributed control method for heterogeneous energy storage systems oriented to demand-side response according to claim 1, characterized in that: The step S400, setting parameters of each cluster leader agent, includes: Set the control gain K of each cluster leader agent BESS , K FL , K BBESS ; Among them, K BESS , K FL , K BBESS All are constants greater than 0; Initialize the leader agent's state to the state of the first follower agent it communicates with; The initial state of the leader agent of the battery cluster is: The initial state of the leader agent of the flexible load cluster is: The initial state of the building group leader is:

6. A distributed control method for heterogeneous energy storage systems oriented to demand-side response according to claim 1, characterized in that: In S500, the system operator gives a target power, and the leader agent determines the sign of the target power, including: The system operator gives the target power P T , the leader agent determines the target power sign. If P T >0, it means that the heterogeneous energy storage system is in the charging state. At this time, each leader agent allocates the target power according to the regulation capability of each cluster. If P T <0, it means that the heterogeneous energy storage system is in a discharging state, and only the battery cluster is involved in the work. in are the total target power of battery cluster, flexible load and building cluster respectively; Among them, each leader agent allocates the target power according to the adjustment capability of each cluster. The strategy is: in The total target power is allocated to each cluster respectively, z is the regulation capacity of each heterogeneous energy storage system, in is the maximum state of charge of the i1th battery energy storage; in is the maximum energy state of the i2th flexible load; in The maximum temperature state of the i3rd building.

7. A distributed control method for heterogeneous energy storage systems oriented to demand-side response according to claim 1, characterized in that: The step S600, setting control parameters, includes: Set control parameters α1, β1, γ1, α2, β2, γ2, α3, β3, γ3; S601, the α1, β1, γ1; Among them, M BESS =L BESS +B BESS , L BESS is the Laplace matrix of the battery cluster follower agent, B BESS is the battery cluster leader matrix, λ min (M BESS ) is the matrix M BESS Minimum eigenvalue; S602, the α2, β2, γ2; Among them, M FL =L FL +B FL , L FL is the Laplace matrix of the flexible load follower, B FL is the flexible load leader matrix, λ min (M FL ) is the matrix M FL Minimum eigenvalue; S603, the α3, β3, γ3; Among them, M BBESS =L BBESS +B BBESS , L BBESS is the Laplace matrix of the building group follower agent, B BBESS is the building cluster leader matrix, λ min (M BBESS ) is the matrix M BBESS Minimum eigenvalue.

8. A distributed control method for heterogeneous energy storage systems oriented to demand-side response according to claim 1, characterized in that: In S700, each intelligent agent in each cluster regulates the power of the equipment unit, and each intelligent agent updates its own state, including: S701, obtain the total target power of the battery cluster, flexible load cluster and building complex obtained in S500, and the intelligent body of each equipment unit in the cluster updates its own state and adjusts the equipment unit power according to the algorithm, and sets the i1th energy storage battery power The power of the i2nd flexible load is The power of the i3th building is S702, each cluster leader agent updates its own state according to the algorithm: A1. The state update rule of the leader agent of the battery cluster is: in Can be directly measured by the intelligent agents of each equipment unit of the battery cluster; The power control algorithm of the battery cluster follower agent is: A2. The state update rule of the flexible load leader agent is: in, It can be directly measured by the intelligent agents of each equipment unit of the flexible load cluster; The power control algorithm of the flexible load follower agent is: A3. The update rule of the leader agent of the building group is: in It can be directly measured by each intelligent agent in the building complex; The power control algorithm of the building group follower agent is:

9. A distributed control method for heterogeneous energy storage systems oriented to demand-side response according to claim 1, characterized in that: The target power control task in S800 includes: Target Power Tracking: Among them, the power is distributed according to the characteristic coefficient ratio: Equipment unit status balance:

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps in a distributed control method for a heterogeneous energy storage system oriented to demand-side response according to any one of claims 1 to 9 are implemented; A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps in the distributed control method of a heterogeneous energy storage system oriented to demand-side response are implemented as described in any one of claims 1-9.

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