Coupling multiplexing regulation and control method and device for enabling stored energy to participate in active and reactive services

Abstract

The invention relates to the technical field of energy storage, and discloses a coupling multiplexing regulation and control method and device for energy storage to participate in active and reactive services, and the method comprises the steps: carrying out the active and reactive decoupling control analysis based on an actual physical structure of an energy storage converter, and building a target coupling regulation and control model for an energy storage system to participate in the active and reactive services; the reactive power regulation and control capability of the energy storage converter is considered, the voltage stability of a power system can be effectively improved, and the operation reliability of a power grid is enhanced. Meanwhile, through the active frequency modulation service of the energy storage system, the load fluctuation of the power system can be better balanced, and the stability of the power system is improved. Furthermore, the target coupling regulation and control model is solved through an enhanced depth algorithm, and charging operation or discharging operation is performed on active and reactive power services by using the solved charging power and discharging power of the energy storage system under different power services, so that the regulation and control precision and the response speed of the energy storage system are further improved.

Description

Technical Field

[0001] The present invention relates to the field of energy storage technology, and in particular to a coupling multiplexing control method and device for energy storage participating in active and reactive services. Background Art

[0002] With the increasing attention paid to the sustainability of energy systems and the stability of power grids, traditional energy production and consumption patterns are facing problems such as unstable energy supply, energy waste, and carbon emissions. These challenges have driven the need for effective integration and volatility management of renewable energy sources such as solar and wind power. Energy storage technology, as a key means to solve the volatility problem of renewable energy, has received extensive attention and research. Energy storage facilities can store excess energy when there is excess energy and release energy when demand peaks to achieve balanced energy allocation. However, energy storage regulation not only involves the storage and release of energy, but also needs to consider factors such as the interaction of power systems, energy market operations, technical feasibility, and economic benefits. In this context, researchers have begun to explore methods to optimize energy storage regulation, intelligent management systems, improve the performance of energy storage equipment, and the potential for energy storage to participate in multiple services. Current energy storage systems mainly focus on the regulation of active power to meet the power system's energy balance needs. However, power systems require not only active power but also reactive power to maintain voltage stability and power factor regulation. With the continuous improvement of power service mechanisms, energy storage systems are expected to participate in reactive voltage regulation services on the basis of participating in active services to provide more comprehensive power support. Therefore, studying the active and reactive coupling control mode of energy storage systems is of great significance for improving the utilization efficiency and economic benefits of energy storage systems. Summary of the invention

[0003] In view of this, the present invention provides a coupling multiplexing control method and device for energy storage to participate in active and reactive services, so as to solve the problem that the current energy storage system mainly focuses on the regulation of active power to meet the electric energy balance requirements of the power system. However, the power system requires not only active power, but also reactive power to maintain voltage stability and power factor regulation.

[0004] In a first aspect, the present invention provides a coupling multiplexing control method for energy storage participating in active and reactive services, the method comprising:

[0005] Obtain the energy storage type of the energy storage system, the actual physical structure of the energy storage converter in the energy storage system, and the real-time energy storage data set of the energy storage system participating in active and reactive services; based on the actual physical structure and energy storage type, analyze the active and reactive decoupling control process and the energy storage operation process in the energy storage system respectively, and establish a target coupling regulation model for the energy storage system participating in active and reactive services; based on the real-time energy storage data set, use the enhanced deep algorithm to solve the target coupling regulation model to obtain the charging power and discharging power of the energy storage system under different power services; based on the charging power and discharging power, use the energy storage system to perform charging or discharging operations on different power services.

[0006] The coupling multiplexing control method for energy storage participating in active and reactive services provided by the present invention performs active and reactive decoupling control analysis based on the actual physical structure of the energy storage converter and establishes a target coupling control model for the energy storage system participating in active and reactive services, taking into account the reactive control capability of the energy storage converter. By incorporating the reactive control capability of the energy storage system into the voltage regulation service of the power system, the voltage stability of the power system can be effectively improved and the operational reliability of the power grid can be enhanced. At the same time, through the active frequency regulation service of the energy storage system, the load fluctuations of the power system can be better balanced and the stability of the power system can be improved. Furthermore, the target coupling control model is solved by strengthening the deep algorithm, and the charging power and discharging power of the energy storage system obtained by the solution under different power services are used to perform charging operations or discharging operations on active and reactive power services, thereby further improving the control accuracy and response speed of the energy storage system.

[0007] In an optional implementation, according to the actual physical structure and energy storage type, the active and reactive decoupling control process and the energy storage operation process in the energy storage system are analyzed respectively, and a target coupling regulation model for the energy storage system to participate in active and reactive services is established, including:

[0008] According to the actual physical structure, the active and reactive decoupling control process in the energy storage system is analyzed and an initial coupling control model of the energy storage system participating in active and reactive services is established; according to the energy storage type and the initial coupling control model, the energy storage operation process is analyzed and a cluster energy storage control model is established; with the benefit of the energy storage system as the goal, the target coupling control model of the energy storage system participating in active and reactive services is determined based on the initial coupling control model and the energy storage control model.

[0009] The coupling multiplexing control method for energy storage participating in active and reactive services provided by the present invention can determine the target coupling control model for the corresponding energy storage system to participate in active and reactive services by combining the initial coupling control model that reflects the decoupling and coordinated control of active and reactive power within the energy storage system and the cluster energy storage control model that reflects the operation of energy storage, thereby providing support for the subsequent improvement of the voltage stability of the power system and the enhancement of the operational reliability of the power grid.

[0010] In an optional implementation, according to the actual physical structure, the active and reactive decoupling control process in the energy storage system is analyzed and an initial coupling regulation model of the energy storage system participating in active and reactive services is established, including:

[0011] According to the actual physical structure, the service type and power constraint set of the energy storage system participating in active and reactive power are determined; based on the service type, the active and reactive power decoupling control mechanism of the energy storage converter is determined according to the actual physical structure; based on the power constraint set, the active and reactive power decoupling control mechanism is used to establish the initial coupling regulation model of the energy storage system participating in active and reactive power services.

[0012] The coupling multiplexing control method for energy storage participating in active and reactive services provided by the present invention analyzes the mechanism and precise control of active and reactive decoupling control of the energy storage converter by considering the actual physical structure of the energy storage converter, and then optimizes its energy constraints from a model perspective. In combination with other conventional constraints of energy storage control, an initial coupling control model for the energy storage system participating in active and reactive services is established, which provides support for the determination of the subsequent target coupling control model.

[0013] In an optional implementation, according to the energy storage type and the initial coupling control model, the energy storage operation process is analyzed and a cluster energy storage control model is established, including:

[0014] Based on the initial coupling control model, the single energy storage operation process is analyzed and a single energy storage control model is established; based on the single energy storage control model and the initial coupling control model, the cluster energy storage operation process is analyzed and a cluster energy storage control model is established.

[0015] The coupling multiplexing control method for energy storage participating in active and reactive services provided by the present invention can realize the energy allocation strategy in energy storage of different specifications and types and establish a corresponding cluster energy storage control model by analyzing the control strategy from battery cells to cluster energy storage, thereby providing support for the safe and stable operation of the subsequent power system.

[0016] In an optional implementation, the power constraint condition set includes SoC constraints, energy storage charging and discharging constraints, and energy storage converter capacity constraints.

[0017] In a second aspect, the present invention provides a coupling multiplexing control device for energy storage to participate in active and reactive services, the device comprising:

[0018] An acquisition module is used to obtain the energy storage type of the energy storage system, the actual physical structure of the energy storage converter in the energy storage system, and the real-time energy storage data set of the energy storage system participating in active and reactive services; an analysis and establishment module is used to analyze the active and reactive decoupling control process and the energy storage operation process in the energy storage system based on the actual physical structure and energy storage type, and establish a target coupling regulation model for the energy storage system participating in active and reactive services; a solution module is used to solve the target coupling regulation model based on the real-time energy storage data set using an enhanced deep algorithm to obtain the charging power and discharging power of the energy storage system under different power services; an operation module is used to use the energy storage system to perform charging or discharging operations on different power services based on the charging power and discharging power.

[0019] In an optional embodiment, the analysis and establishment module includes:

[0020] The first analysis and establishment submodule is used to analyze the active and reactive decoupling control process in the energy storage system according to the actual physical structure and establish an initial coupling control model for the energy storage system to participate in active and reactive services; the second analysis and establishment submodule is used to analyze the energy storage operation process and establish a cluster energy storage control model according to the energy storage type and the initial coupling control model; the determination submodule is used to determine the target coupling control model for the energy storage system to participate in active and reactive services according to the initial coupling control model and the energy storage control model, with the benefit of the energy storage system as the target.

[0021] In a third aspect, the present invention provides a computer device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the coupling multiplexing control method of energy storage participating in active and reactive services of the above-mentioned first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0022] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the coupling multiplexing control method for energy storage participating in active and reactive services of the above-mentioned first aspect or any corresponding embodiment thereof.

[0023] In a fifth aspect, the present invention provides a computer program product, including computer instructions, which are used to enable a computer to execute the coupling multiplexing control method of energy storage participating in active and reactive services of the above-mentioned first aspect or any corresponding embodiment. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0025] Figure 1 It is a flow chart of a coupling multiplexing control method for energy storage participating in active and reactive services according to an embodiment of the present invention;

[0026] Figure 2 is a flow chart of another coupling multiplexing control method for energy storage participating in active and reactive services according to an embodiment of the present invention;

[0027] Figure 3 is a schematic diagram of an energy storage converter system participating in active and reactive service collaborative coupling according to an embodiment of the present invention;

[0028] Figure 4 is a cluster energy storage power distribution control block diagram according to an embodiment of the present invention;

[0029] Figure 5 is a schematic diagram of active and reactive coupling multiplexing coordination based on the actual physical structure of the energy storage converter according to an embodiment of the present invention;

[0030] Figure 6 is a structural block diagram of a coupling multiplexing control device for energy storage participating in active and reactive services according to an embodiment of the present invention;

[0031] Figure 7 It is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0032] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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 those skilled in the art without creative work are within the scope of protection of the present invention.

[0033] The embodiment of the present invention provides a coupling multiplexing control method for energy storage to participate in active and reactive services, taking into account the active and reactive control capabilities of the energy storage converter. By incorporating the reactive control capability of the energy storage system into the voltage regulation service of the power system, the voltage stability of the power system can be effectively improved and the operational reliability of the power grid can be enhanced.

[0034] According to an embodiment of the present invention, an embodiment of a coupling multiplexing control method for energy storage participating in active and reactive services is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0035] In this embodiment, a coupling multiplexing control method for energy storage to participate in active and reactive services is provided, which can be used in electronic devices such as computers, mobile phones, tablet computers, etc. Figure 1 FIG. 1 is a flow chart of a coupling multiplexing control method for energy storage participating in active and reactive services according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0036] Step S101, obtaining the energy storage type of the energy storage system, the actual physical structure of the energy storage converter in the energy storage system, and the real-time energy storage data set of the energy storage system participating in active and reactive services.

[0037] Specifically, energy storage types may include single-cell energy storage and cluster energy storage.

[0038] Furthermore, the actual physical structure of the energy storage converter may include power conversion devices, control systems, filters, and the like.

[0039] Furthermore, the real-time energy storage data set of the energy storage system participating in active and reactive services is used to reflect the real-time price signal of the energy storage system participating in active and reactive services.

[0040] Step S102: Based on the actual physical structure and energy storage type, the active and reactive decoupling control process and the energy storage operation process in the energy storage system are analyzed respectively, and a target coupling regulation model for the energy storage system to participate in active and reactive services is established.

[0041] Specifically, the active and reactive power decoupling control process and the energy storage operation process in the energy storage system are analyzed respectively in combination with the actual physical structure and energy storage type, and a target coupling regulation model for the energy storage system participating in active and reactive services is established based on the analysis structure. By establishing this target coupling regulation model, the energy storage system can dynamically adjust between active power and reactive power, realizing the comprehensive utilization of the energy storage system in a variety of power services.

[0042] Step S103, based on the real-time energy storage data set, the target coupling control model is solved using an enhanced deep algorithm to obtain the charging power and discharging power of the energy storage system under different power services.

[0043] Specifically, reinforcement learning is a machine learning method that gradually optimizes the decision-making strategy of the intelligent agent through trial and error and reward mechanism in the environment. The intelligent agent learns how to take the best actions in different situations to maximize the cumulative reward through interaction with the environment. DQN is a reinforcement learning method, which is an algorithm that maximizes the cumulative reward by continuously learning the benefits under different action states. The DQN algorithm contains two networks, the evaluation network and the target network. The evaluation network selects actions and updates the state, and the target network calculates the Q value. Then a deep neural network is used to gradually approximate the true value of the Q function to solve the problem of large state space size. The specific formula is shown in the following relationship (1):

[0044]

[0045] Where: s t represents the state at time t; a t represents the action at time t; θ - represents the network parameters; α represents the learning rate; Q(s t ,a t θ t ) represents the Q value of the evaluation network taking action a in state s at time t, with parameter θ; r t represents the immediate reward obtained after taking action a in state s at time t; γ represents the discount factor; s t+1 Represents the state at time t+1. Indicates that the target network is in state s t+1 The maximum Q value among all possible actions, parameter is θ - .

[0046] Furthermore, after the Q value iteration is completed, DQN trains the evaluation network according to the temporal difference deviation, as shown in the following equation (2):

[0047]

[0048] Furthermore, Q-learning performs learning and state iteration, and uses the ε greedy strategy for action selection to explore and utilize. It randomly extracts from several states with a probability of ε, so that each state has a chance to be explored, improving the continuous exploration, as shown in the following relationship (3):

[0049]

[0050] Where: π(a,s) represents the probability of action a being selected in state s; ε represents the probability of randomly selecting an action (ε≠0); A represents all selectable actions.

[0051] Furthermore, combined with the DQN algorithm, the acquired real-time energy storage data set is input into the target coupling control model for solution, and the charging power and discharging power of the energy storage system under different power services can be obtained.

[0052] Step S104: Based on the charging power and the discharging power, the energy storage system is used to perform charging operations or discharging operations on different power services.

[0053] Specifically, the energy storage system can use the obtained charging power and discharging power to perform corresponding charging operations or discharging operations according to different power service requirements.

[0054] The coupling multiplexing control method for energy storage participating in active and reactive services provided in this embodiment performs active and reactive decoupling control analysis based on the actual physical structure of the energy storage converter and establishes a target coupling control model for the energy storage system participating in active and reactive services. The reactive control capability of the energy storage converter is taken into account. By incorporating the reactive control capability of the energy storage system into the voltage regulation service of the power system, the voltage stability of the power system can be effectively improved and the operational reliability of the power grid can be enhanced. At the same time, through the active frequency regulation service of the energy storage system, the load fluctuations of the power system can be better balanced and the stability of the power system can be improved. Furthermore, the target coupling control model is solved by strengthening the deep algorithm, and the charging power and discharging power of the energy storage system under different power services obtained by the solution are used to perform charging operations or discharging operations on active and reactive power services, which further improves the control accuracy and response speed of the energy storage system.

[0055] In this embodiment, a coupling multiplexing control method for energy storage to participate in active and reactive services is provided, which can be used in electronic devices such as computers, mobile phones, tablet computers, etc. Figure 2 FIG. 1 is a flow chart of a coupling multiplexing control method for energy storage participating in active and reactive services according to an embodiment of the present invention. Figure 2 As shown, the process includes the following steps:

[0056] Step S201, obtain the energy storage type of the energy storage system, the actual physical structure of the energy storage converter in the energy storage system, and the real-time energy storage data set of the energy storage system participating in active and reactive services. Figure 1 Step S101 of the illustrated embodiment will not be described in detail here.

[0057] Step S202: Based on the actual physical structure and energy storage type, the active and reactive decoupling control process and the energy storage operation process in the energy storage system are analyzed respectively, and a target coupling regulation model for the energy storage system to participate in active and reactive services is established.

[0058] Specifically, the above step S202 includes:

[0059] Step S2021: Analyze the active and reactive decoupling control process in the energy storage system according to the actual physical structure and establish an initial coupling regulation model for the energy storage system to participate in active and reactive services.

[0060] Specifically, as the types and rules of power services continue to improve, energy storage can participate in the reuse of power services and obtain compensation from a variety of power services. The existing model often regulates the reuse of multiple services dominated by active power for energy storage based on the time scale or type of power services, but there must be a certain degree of reactive power in the power system, which can be used to participate in voltage regulation services, etc. Therefore, after considering the active power coupling of the power system, as the power service mechanism is further improved, it can be considered to include reactive power in the reuse of energy storage.

[0061] Therefore, the actual physical structure of the energy storage converter is considered to conduct active and reactive decoupling control analysis and establish a target coupling regulation model for the energy storage system to participate in active and reactive services. The active and reactive regulation capabilities of the energy storage converter are taken into account. By incorporating the reactive regulation capability of the energy storage system into the voltage regulation service of the power system, the voltage stability of the power system can be effectively improved and the operational reliability of the power grid can be enhanced.

[0062] In some optional implementations, the above step S2021 includes:

[0063] Step a1: Determine the service type and power constraint set of the energy storage system participating in active and reactive power according to the actual physical structure.

[0064] Step a2: Based on the service type, determine the active and reactive decoupling control mechanism of the energy storage converter according to the actual physical structure.

[0065] Step a3: Based on the power constraint condition set, an initial coupling regulation model for the energy storage system to participate in active and reactive services is established by utilizing the active and reactive decoupling control mechanism.

[0066] The power constraint condition set may include SoC constraints, energy storage charging and discharging constraints, and energy storage converter capacity constraints.

[0067] Furthermore, active power mainly participates in the frequency regulation service among electric energy services and auxiliary services, while reactive power mainly participates in the voltage regulation service among auxiliary services, and obtains profits from them.

[0068] Specifically, the energy storage converter realizes the conversion and regulation of active power and reactive power through its physical structure and control strategy. Among them, the active power is realized by the rectifier and inverter, and the reactive power conversion is realized by electronic devices such as IGBT and MOSFET to realize phase regulation and voltage control, and realize PQ decoupling control and vector control. Specifically speaking of active and reactive power constraints, since the reactive power is subject to the constraints of the active power, there is no need to add constraints for the reactive service, and the proportion of participating in different active services needs to satisfy the constraints shown in the following relationships (4) to (6):

[0069] 0≤ΔP t =P c,t -P d,t ≤ΔP max (4)

[0070]

[0071] Where: P c,t P represents the charging power of the energy storage station at time t; d,t Indicates the discharge power of the energy storage station at time t; ΔP t represents the actual active power at time t; S ini,t Represents the total capacity of the energy storage station; ΔQ t Represents the actual reactive power at time t.

[0072] Furthermore, the above equation (4) indicates that the upper and lower limits of the active power of the converter need to be satisfied within the maximum power limit; the above equation (5) indicates that the reactive power regulation of the converter needs to use the remaining capacity of the converter after frequency regulation; the above equation (6) indicates that the active and reactive power of the converter need to satisfy the capacity constraints of the converter.

[0073] Furthermore, when energy storage participates in the coordinated regulation of active and reactive power, its reactive part mainly utilizes reactive power to participate in voltage regulation services, while the active part can simultaneously participate in multiple power services such as frequency regulation and electric energy.

[0074] Furthermore, when energy storage participates in the coordinated regulation of active and reactive power, active power mainly participates in the frequency regulation service among electric energy services and auxiliary services, and reactive power mainly participates in the voltage regulation service among auxiliary services, and obtains revenue from it. The capacity of active and reactive power is determined by the price incentives of each link. The size of active and reactive power can be freely allocated according to the compensation price while meeting the capacity constraints. When controlling energy storage, in addition to taking profit maximization as the objective function, it is also necessary to meet constraints such as SoC constraints and energy storage charging and discharging constraints.

[0075] Specifically, the SoC constraints are shown in the following equations (7) and (8):

[0076] SOC min ≤SOC t≤SOC max (7)

[0077] SOC(24)=SOC(1) (8)

[0078] Where: SOC min Indicates the minimum limit of SoC; SOC max Indicates the maximum limitation of the SoC.

[0079] Furthermore, the above relational expression (8) indicates that the SoC at the first moment of the operation day (SOC(1)) and the SoC at the last moment (SOC(24)) are required to be equal.

[0080] Furthermore, the energy storage charging and discharging constraints are shown in the following equations (9) to (12):

[0081]

[0082] Where: Indicates the lower limit of the energy storage system charging power; Indicates the upper limit of the energy storage system charging power; P c,t represents the charging power of the energy storage system at time t; Indicates the lower limit of the energy storage system discharge power; Indicates the upper limit of the energy storage system discharge power; P d,t A represents the discharge power of the energy storage system at time t; E Represents a binary variable with a value of 0 or 1.

[0083] Furthermore, the above equations (9) and (10) respectively represent the charging and discharging constraints of the energy storage system; the above equations (11) and (12) represent the constraint that the energy storage can only be in the charging or discharging state at the same time.

[0084] Further, if Figure 3 As shown in the figure, based on the actual physical structure and internal control devices of the energy storage converter, the mechanism and precise control of the active and reactive decoupling control of the energy storage converter are analyzed, and then its energy constraints are optimized from the model perspective. In combination with other conventional constraints of energy storage regulation, an initial coupling regulation model of the energy storage converter system participating in active and reactive services is established.

[0085] Step S2022: Analyze the energy storage operation process and establish a cluster energy storage control model based on the energy storage type and the initial coupling control model.

[0086] Specifically, based on the initial coupling control model obtained, it is also necessary to study the impact of energy storage of different sizes on the control and establish a corresponding cluster energy storage control model.

[0087] In some optional implementations, the above step S2022 includes:

[0088] Step b1, based on the initial coupling control model, the single energy storage operation process is analyzed and a single energy storage control model is established.

[0089] Step b2: Based on the single energy storage control model and the initial coupling control model, the cluster energy storage operation process is analyzed and a cluster energy storage control model is established.

[0090] When it comes to the charge and discharge regulation of battery cells, since the energy storage cell has only one battery cluster, the energy storage state can be adjusted directly according to the charge and discharge instructions. However, since the SoC states of different cells in cluster energy storage are different, power allocation needs to be performed on different battery cells.

[0091] Specifically, before calculating the SoC of large-scale energy storage, since the energy storage system has a life loss after being put into use, it is necessary to measure the energy storage system according to the actual SoH level to obtain the true capacity of the energy storage system. The SoH performance level of the battery module calculated based on the UGF method is shown in the following relationship (13):

[0092]

[0093] Where: n represents the number of battery modules in the energy storage system; Indicates the SoH performance level of each battery module of the energy storage system; It represents the SoH level probability corresponding to the battery module in state i.

[0094] Furthermore, by taking the first-order derivative of the UGF of the corresponding battery cluster and setting the variable Z to 1, the expected value of the SoH of the battery cluster can be obtained, as shown in the following equation (14):

[0095]

[0096] Furthermore, the actual capacity of the battery cluster can be obtained as S ini ×E t (z) is the capacity of energy storage that can participate in frequency and voltage regulation.

[0097] Furthermore, for single energy storage control: at any time, the energy storage can be charged / discharged, and its power change is ΔP i,t =P c,i,t -P d,i,t , so the recursive formula of the battery cluster SoC can be obtained as shown in the following relationship (15):

[0098]

[0099] Where: η c Indicates charging efficiency; η dIndicates the discharge efficiency.

[0100] Furthermore, when clustering energy storage, due to the different charging and discharging times of multiple energy storage power stations, there is a certain gap in their SoC states and their actual capacities. If the energy storage system continues to work when the SoC charge state is not balanced, some energy storage units will be overcharged or over-discharged, and will exit the system prematurely, affecting the stability of the energy storage system and even the power grid. Therefore, when clustering energy storage devices composed of multiple boxes, it is necessary to coordinate and balance the SoC of each unit.

[0101] First, the SoC value of each battery cell is uploaded to the cluster controller, which calculates the actual SoC value of each battery cell and the average SoC value of the cluster, and uses the average value as the reference value SOC of SoC in the power distribution control link. ref The actual SOC of the battery cell is then i With SOC ref The difference is made, and the power reference value for cluster SoC balancing is obtained through the proportional link P. Adding the average value of cluster energy storage output power, the reference value of the actual output power of the single cell at time t is obtained, as shown in the following relationship (16):

[0102]

[0103] Where: represents the average value of cluster energy storage output power; k p It represents the proportionality coefficient, and its value is the average actual capacity of the energy storage unit. The control block diagram of the power distribution link is as follows: Figure 4 shown.

[0104] Furthermore, at any moment, the energy storage can be charged / discharged, and the power change for each cell is ΔP i,t =P c,i,t -P d,i,t , the power change for the entire cluster is ΔP t =P c,t -P d,t , therefore, the battery cell SOC can be obtained i and cluster energy storage SOC ref The recursive formulas are shown in the following equations (17) and (18):

[0105]

[0106] Where: E i,t (z) represents the expected value of SoH calculated according to the above equations (13) and (14) for the single-cell energy storage; E t (z) represents the expected SoH value of the cluster energy storage calculated according to the above equations (13) and (14).

[0107] Therefore, cluster energy storage can realize autonomous distribution of power between different battery cells while meeting the power requirements of the load or grid, so as to achieve SoC balance during charging and discharging, avoid overcharging or over-discharging of single cells due to different SoC states, maximize the life and operating efficiency of the cluster energy storage system, and ensure the safety of the grid.

[0108] Step S2023, taking the benefit of the energy storage system as the target, and according to the initial coupling control model and the energy storage control model, determining the target coupling control model for the energy storage system to participate in active and reactive services.

[0109] Specifically, taking the benefit of the energy storage system as the target, the initial coupling control model and the energy storage control model are combined to form a corresponding target coupling control model for the energy storage system to participate in active and reactive services.

[0110] According to the description of step S103 above, based on the DQN algorithm, the design of energy storage participating in active and reactive coordination mainly includes four parts: state, action, reward function, and objective function, and the maximum benefit is achieved through continuous iterative learning.

[0111] Specifically, the state of energy storage is the state information contained in the intelligent agent, as shown in the following equation (19):

[0112] s t =(L t ,λ t ,SoC t ) (19)

[0113] Where: L t Indicates time; t Represents price signal; SoC t Indicates the current capacity of the energy storage device at time t.

[0114] Furthermore, the active and reactive charging and discharging actions of the energy storage are the action information contained in the intelligent agent, as shown in the following equation (20):

[0115] a t =(P t ,Q t ) (20)

[0116] Where: P t Indicates the charging and discharging power of the energy storage system.

[0117] Furthermore, the next state of the energy storage device is transformed according to the state and action at time t, as shown in the following equation (21):

[0118] s t+1 =(s t,a t ) (twenty one)

[0119] Furthermore, the reward for energy storage is the reward information for energy storage in environmental operation, as shown in the following equation (22):

[0120] r t =(P sys,t+1 λ P,t+1 +Q sys,t+1 λ Q,t+1 )Δt-C t+1 (twenty two)

[0121] Where: Δt represents the unit time interval; C t+1 represents the energy storage operation cost; P sys,t+1 Indicates the active power of energy storage; Q sys,t+1 Represents the reactive power of energy storage.

[0122] Furthermore, the control goal of the intelligent agent is to maximize the economic benefits in active and reactive services, and the reward function will produce a certain discount due to the distance in time. Therefore, the objective function is the sum of the discount factor and the reward product, as shown in the following relationship (23):

[0123] Obj(f)=max∑γr t (twenty three)

[0124] Step S203, based on the real-time energy storage data set, the target coupling control model is solved using an enhanced deep algorithm to obtain the charging power and discharging power of the energy storage system under different power services.

[0125] Specifically, combined with the description of the construction of the enhanced deep algorithm and the target coupling control model in the above steps S103 and S2023, the real-time energy storage data set obtained in real time is input into the target coupling control model for solution, so that the charging power and discharging power of the energy storage system under different power services can be obtained.

[0126] Step S204: Based on the charging power and the discharging power, the energy storage system is used to perform charging or discharging operations on different power services. Figure 1 Step S104 of the illustrated embodiment will not be described in detail here.

[0127] The coupling multiplexing control method for energy storage participating in active and reactive services provided in this embodiment considers the actual physical structure of the energy storage converter to analyze the mechanism and precise control of the energy storage converter for active and reactive decoupling control, and then optimizes its energy constraints from the model perspective, and combines other conventional constraints of energy storage control to establish an initial coupling control model for the energy storage system to participate in active and reactive services. At the same time, by analyzing the control strategy from battery cells to cluster energy storage, the energy allocation strategy in energy storage of different specifications and types can be implemented and the corresponding cluster energy storage control model can be established. Further, by combining the initial coupling control model reflecting the active and reactive decoupling coordinated control in the energy storage system and the cluster energy storage control model reflecting the operation of energy storage, the target coupling control model for the corresponding energy storage system to participate in active and reactive services can be determined, taking into account the active and reactive control capabilities of the energy storage converter. By incorporating the reactive control capability of the energy storage system into the voltage regulation service of the power system, the voltage stability of the power system can be effectively improved and the operational reliability of the power grid can be enhanced. At the same time, through the active frequency regulation service of the energy storage system, the load fluctuation of the power system can be better balanced and the stability of the power system can be improved. Furthermore, the target coupling control model is solved by strengthening the deep algorithm, and the charging power and discharging power of the energy storage system under active and reactive power services are used to perform charging or discharging operations on different power services, further improving the control accuracy and response speed of the energy storage system.

[0128] In one example, an active and reactive coupling multiplexing coordination mode based on the actual physical structure of the energy storage converter is provided, and an energy storage multiplexing control model of active and reactive coupling of the power system is established through a deep reinforcement learning algorithm. The mode first defines the service types and power constraints of its active and reactive participation based on the actual physical structure of the energy storage converter; then establishes cluster control models for single energy storage and multi-box energy storage respectively; finally, a deep reinforcement learning algorithm is introduced to model the benefit-cost model, and the active and reactive coupling multiplexing solution algorithm of energy storage is designed with the benefit maximization as the reward function. Through the active and reactive coupling multiplexing coordination mode of this example, the energy storage system can dynamically adjust between active power and reactive power, and realize the comprehensive utilization of the energy storage system in a variety of power services. Among them, the active power mainly participates in the frequency regulation service in the electric energy service and the auxiliary service, and the reactive power mainly participates in the voltage regulation service in the auxiliary service, and obtains benefits from it. The active and reactive capacity of the energy storage system is determined by the price incentives of each link. Under the condition of meeting the capacity constraint, the size of the active and reactive power is freely allocated according to the compensation price to ensure the maximum benefit of the energy storage system. Through the active and reactive coupling multiplexing coordination mode of the energy storage system proposed in this example, the energy storage system can obtain maximum benefits from a variety of power services and improve the economic benefits of the energy storage system. At the same time, through the active frequency regulation service and reactive voltage regulation service of the energy storage system, the voltage stability and operation reliability of the power system are improved. In addition, by introducing deep reinforcement learning to train the control strategy, the control accuracy and response speed of the energy storage system are further improved, the control strategy of the energy storage system is optimized, and the safe and stable operation of the power grid is ensured.

[0129] Specifically, Figure 5 As shown in the figure, firstly, based on the actual physical structure and internal control devices of the energy storage converter, the mechanism and precise control of the active and reactive decoupling control of the energy storage converter are analyzed, and then its energy constraints are optimized from the model perspective. In combination with other conventional constraints of energy storage regulation, a coupling regulation model of the energy storage converter system participating in active and reactive services is established. Secondly, on the basis of determining the reuse mode participating in the active and reactive coordinated regulation, the control strategy from battery cells to cluster energy storage is studied from the perspective of SoC constraints to realize the energy allocation strategy in energy storage of different specifications and types. Finally, an operating data set of energy storage in the active and reactive service coupling operation mode is established, and the energy storage regulation model established in the previous step is accelerated and optimized based on the deep reinforcement learning method, and the energy storage capacity is put into operation according to the discharge calculation results.

[0130] Exemplarily, the active / reactive coupling multiplexing coordination mode based on the actual physical structure of the energy storage converter provided in this example specifically includes:

[0131] Step 1: As the types and rules of power services continue to improve, energy storage can participate in the reuse of power services and obtain compensation from a variety of power services. The existing model often multiplexes and regulates energy storage to participate in multiple services dominated by active power according to the time scale or type of power services, but there must be a certain degree of reactive power in the power system, which can be used to participate in voltage regulation services, etc. Therefore, after considering the active coupling of the power system, as the power service mechanism is further improved, reactive power can also be considered to be included in the reuse of energy storage. Therefore, this reuse model will start with the internal active and reactive coupling of the energy storage converter to introduce the active and reactive reuse method of energy storage.

[0132] The energy storage converter realizes the conversion and regulation of active power and reactive power through its physical structure and control strategy. Among them, the active power is realized by the rectifier and inverter, and the reactive power conversion is realized by electronic devices such as IGBT and MOSFET to realize phase regulation and voltage control, and realize PQ decoupling control and vector control. Specifically speaking of active and reactive power constraints, since the reactive power is subject to the constraints of the active power, there is no need to add constraints to the reactive service, and the proportion of participating in different active services needs to meet the constraints shown in the above equations (4) to (6).

[0133] Furthermore, when energy storage participates in the coordinated regulation of active and reactive power, its reactive part mainly utilizes reactive power to participate in voltage regulation services, while the active part can participate in multiple power services at the same time.

[0134] Furthermore, when energy storage participates in the coordinated regulation of active and reactive power, active power mainly participates in the frequency regulation service among electric energy services and auxiliary services, and reactive power mainly participates in the voltage regulation service among auxiliary services, and obtains benefits from them. The capacity of active and reactive power is determined by the price incentives of each link. Under the condition of meeting the capacity constraint, the size of active and reactive power can be freely allocated according to the compensation price. When controlling energy storage, in addition to taking the maximization of benefits as the objective function, it is also necessary to meet the constraints such as SoC constraints and energy storage charging and discharging constraints, as shown in the above equations (7) to (12).

[0135] Step 2: Based on the general control model of energy storage participating in active and reactive power in step 1, it is also necessary to study the impact of energy storage of different sizes on regulation. When it comes to the charge and discharge regulation of battery cells, since there is only one battery cluster in the energy storage cell, the energy storage state can be adjusted directly according to the charge and discharge instructions. However, since the SoC states of different cells in the cluster energy storage are different, power allocation needs to be performed on different battery cells. The following will explain the SoC calculation methods of energy storage of different sizes.

[0136] Before calculating the SoC of large-scale energy storage, since the energy storage system has a life loss after being put into use, it is necessary to measure the energy storage system according to the actual SoH level to obtain the true capacity of the energy storage system. The SoH performance level of the battery module calculated based on the UGF method is shown in the above-mentioned equations (13) to (14).

[0137] Furthermore, the regulation of single-cell energy storage and cluster energy storage refers to the description in the above step S2022. Through regulation, cluster energy storage can realize autonomous distribution of power between different battery cells while meeting the power requirements of the load or grid, so as to achieve SoC balance during charging and discharging, avoid overcharging or over-discharging of single cells due to different SoC states, maximize the life and operating efficiency of the cluster energy storage system, and ensure the safety of the grid.

[0138] Step 3: Obtain price signals of the participating active and reactive power services from the system, and then use deep reinforcement learning to optimize and solve based on the energy storage model and regulation model in the previous step, obtain the power of energy storage under different services, and perform charging and discharging operations based on the results.

[0139] The active / reactive coupling multiplexing coordination mode based on the actual physical structure of the energy storage converter provided in this example has the following beneficial effects:

[0140] (1) Taking into account the physical characteristics of the energy storage converter, the active and reactive power are coordinated and regulated. In addition to the active power participating in the electric energy service, this design enables the energy storage to participate in the voltage regulation service using the remaining reactive power to obtain additional compensation, thereby increasing the overall benefits of the energy storage.

[0141] (2) Based on the actual physical structure of the energy storage converter, the active and reactive power regulation capabilities of the energy storage converter are considered. By incorporating the reactive power regulation capability of the energy storage system into the voltage regulation service of the power system, the voltage stability of the power system can be effectively improved and the operational reliability of the power grid can be enhanced. At the same time, through the active frequency regulation service of the energy storage system, the load fluctuations of the power system can be better balanced, further improving the stability of the power system.

[0142] (3) By learning and optimizing the actual operating data of the energy storage system, the active and reactive power output of the energy storage system can be dynamically adjusted to achieve the optimal control strategy of the energy storage system. Under the premise of meeting the energy constraints and SoC constraints, the energy storage system can be monitored and adjusted in real time by the intelligent control system, further improving the control accuracy and response speed of the energy storage system.

[0143] In this embodiment, a coupling multiplexing control device for energy storage to participate in active and reactive services is also provided, which is used to implement the above embodiments and preferred implementations, and will not be repeated here. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0144] This embodiment provides a coupling multiplexing control device for energy storage to participate in active and reactive services, such as Figure 6 As shown, the device comprises:

[0145] The acquisition module 601 is used to acquire the energy storage type of the energy storage system, the actual physical structure of the energy storage converter in the energy storage system, and the real-time energy storage data set of the energy storage system participating in active and reactive services.

[0146] The analysis and establishment module 602 is used to analyze the active and reactive decoupling control process and the energy storage operation process in the energy storage system based on the actual physical structure and energy storage type, and to establish a target coupling regulation model for the energy storage system to participate in active and reactive services.

[0147] The solution module 603 is used to solve the target coupling control model based on the real-time energy storage data set using an enhanced deep algorithm to obtain the charging power and discharging power of the energy storage system under different power services.

[0148] The operation module 604 is used to perform charging operations or discharging operations on different power services using the energy storage system based on the charging power and the discharging power.

[0149] In some optional implementations, the analysis establishment module 602 includes:

[0150] The first analysis and establishment submodule is used to analyze the active and reactive decoupling control process in the energy storage system according to the actual physical structure and establish an initial coupling regulation model for the energy storage system to participate in active and reactive services.

[0151] The second analysis and establishment submodule is used to analyze the energy storage operation process and establish a cluster energy storage control model according to the energy storage type and the initial coupling control model.

[0152] The determination submodule is used to determine the target coupling control model for the energy storage system to participate in active and reactive services based on the initial coupling control model and the energy storage control model, taking the benefit of the energy storage system as the target.

[0153] In some optional embodiments, the first analysis establishment submodule includes:

[0154] The first determination unit is used to determine the service type and power constraint condition set of the energy storage system participating in active and reactive power according to the actual physical structure.

[0155] The second determination unit is used to determine the active and reactive decoupling control mechanism of the energy storage converter based on the service type and the actual physical structure.

[0156] A unit is established for establishing an initial coupling regulation model for the energy storage system to participate in active and reactive services based on a power constraint condition set and utilizing an active and reactive decoupling control mechanism.

[0157] In some optional embodiments, the second analysis establishment submodule includes:

[0158] The first analysis and establishment unit is used to analyze the single energy storage operation process and establish a single energy storage regulation model based on the initial coupling regulation model.

[0159] The second analysis and establishment unit is used to analyze the cluster energy storage operation process and establish a cluster energy storage regulation model based on the single energy storage regulation model and the initial coupling regulation model.

[0160] In some optional implementations, the power constraint condition set includes SoC constraints, energy storage charging and discharging constraints, and energy storage converter capacity constraints.

[0161] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0162] The coupling multiplexing control device for energy storage participating in active and reactive services in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0163] The embodiment of the present invention also provides a computer device having the above Figure 6 The energy storage shown participates in the coupling multiplexing control device of active and reactive services.

[0164] See also Figure 7 , Figure 7 is a schematic diagram of the structure of a computer device provided by an optional embodiment of the present invention, such as Figure 7As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 7 A processor 10 is taken as an example.

[0165] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0166] The memory 20 stores instructions executable by at least one processor 10, so that at least one processor 10 executes the method shown in the above embodiment.

[0167] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0168] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0169] The computer device further comprises a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0170] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0171] A part of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the existence of the computer program instruction in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc., and accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium accessible to the computer.

[0172] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A coupling multiplexing control method for energy storage to participate in active and reactive services, characterized in that: The method comprises: Acquire the energy storage type of the energy storage system, the actual physical structure of the energy storage converter in the energy storage system, and the real-time energy storage data set of the energy storage system participating in active and reactive services; Based on the actual physical structure and the energy storage type, the active and reactive decoupling control process and the energy storage operation process in the energy storage system are analyzed respectively, and a target coupling regulation model for the energy storage system to participate in active and reactive services is established; Based on the real-time energy storage data set, the target coupling control model is solved using an enhanced deep algorithm to obtain the charging power and discharging power of the energy storage system under different power services; Based on the charging power and the discharging power, the energy storage system is used to perform charging operations or discharging operations on different power services.

2. The method according to claim 1, characterized in that: According to the actual physical structure and the energy storage type, the active and reactive decoupling control process and the energy storage operation process in the energy storage system are analyzed respectively, and a target coupling regulation model for the energy storage system to participate in active and reactive services is established, including: According to the actual physical structure, the active and reactive decoupling control process in the energy storage system is analyzed and an initial coupling regulation model of the energy storage system participating in active and reactive services is established; According to the energy storage type and the initial coupling control model, analyzing the energy storage operation process and establishing a cluster energy storage control model; Taking the revenue of the energy storage system as a target, the target coupling regulation model for the energy storage system to participate in active and reactive services is determined according to the initial coupling regulation model and the energy storage regulation model.

3. The method according to claim 2, characterized in that According to the actual physical structure, the active and reactive decoupling control process in the energy storage system is analyzed and an initial coupling regulation model of the energy storage system participating in active and reactive services is established, including: Determining, according to the actual physical structure, a service type and a power constraint condition set of active and reactive power participation of the energy storage system; Based on the service type, determining the active and reactive decoupling control mechanism of the energy storage converter according to the actual physical structure; Based on the power constraint condition set, the active and reactive power decoupling control mechanism is utilized to establish the initial coupling regulation model for the energy storage system to participate in active and reactive power services.

4. The method according to claim 2, characterized in that: According to the energy storage type and the initial coupling control model, the energy storage operation process is analyzed and a cluster energy storage control model is established, including: Based on the initial coupling control model, the single energy storage operation process is analyzed and a single energy storage control model is established; Based on the single energy storage regulation model and the initial coupling regulation model, the cluster energy storage operation process is analyzed and the cluster energy storage regulation model is established.

5. The method according to claim 3, characterized in that: The power constraint condition set includes SoC constraint, energy storage charging and discharging constraint and energy storage converter capacity constraint.

6. A coupling multiplexing control device for energy storage to participate in active and reactive services, characterized in that: The device comprises: An acquisition module, used to acquire the energy storage type of the energy storage system, the actual physical structure of the energy storage converter in the energy storage system, and a real-time energy storage data set of the energy storage system participating in active and reactive services; An analysis and establishment module, for analyzing the active and reactive decoupling control process and the energy storage operation process in the energy storage system based on the actual physical structure and the energy storage type, and establishing a target coupling regulation model for the energy storage system to participate in active and reactive services; A solution module, used to solve the target coupling control model based on the real-time energy storage data set using an enhanced deep algorithm to obtain the charging power and discharging power of the energy storage system under different power services; An operation module is used to perform charging operations or discharging operations on different power services using the energy storage system based on the charging power and the discharging power.

7. The device according to claim 6, characterized in that The analysis and establishment module includes: A first analysis and establishment submodule is used to analyze the active and reactive decoupling control process in the energy storage system according to the actual physical structure and establish an initial coupling regulation model for the energy storage system to participate in active and reactive services; The second analysis and establishment submodule is used to analyze the energy storage operation process and establish a cluster energy storage control model according to the energy storage type and the initial coupling control model; A determination submodule is used to determine the target coupling regulation model for the energy storage system to participate in active and reactive services based on the initial coupling regulation model and the energy storage regulation model, with the revenue of the energy storage system as the target.

8. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the coupling multiplexing control method for energy storage participating in active and reactive services as described in any one of claims 1 to 5 by executing the computer instructions.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the coupling multiplexing control method for energy storage participating in active and reactive services according to any one of claims 1 to 5.

10. A computer program product, characterized in that The method comprises computer instructions for causing a computer to execute the coupling multiplexing control method for energy storage participating in active and reactive services as described in any one of claims 1 to 5.

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