Battery energy storage health management method and system based on energy sharing

Abstract

The invention relates to the technical field of battery health management, in particular to a battery energy storage health management method and system based on energy sharing, and the method comprises the steps that an aggregator obtains the current charging and discharging data of energy storage equipment of all user sides in real time, and obtains the current battery health state of the energy storage equipment according to the current charging and discharging data and initial data; the aggregator inputs the current battery health state of the energy storage equipment into the equivalent circuit model to obtain the current system efficiency and power capacity of the energy storage equipment; and the aggregator performs energy sharing on all the energy storage devices based on a preset health awareness energy management strategy according to the current battery health states, efficiencies and power capacities of all the energy storage devices, generates an energy scheduling scheme corresponding to each user side and sends the energy scheduling scheme to the corresponding user side. The system has the beneficial effects that energy sharing in a large range is realized on the basis of sensing the health state of the battery in real time, so that unnecessary cost and energy waste are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of battery health management, and in particular to a battery energy storage health management method and system based on energy sharing. Background Art

[0002] In recent years, the power grid has developed rapidly, bringing many changes. Energy revolution and digital revolution are the trends of future industrial development. Internet of Things technology has achieved remarkable achievements in recent years.

[0003] The development of the Internet of Things provides an interconnection platform for the power grid and also provides conditions for the interconnection between energy storage systems. Energy storage has developed rapidly in recent years because it can effectively match distributed energy. However, the current energy storage system does not perceive the health information of the battery in real time, which causes frequent accidents; and at this stage, this "large-scale energy storage" is provided by many users, and little attention is paid to how energy sharing affects battery health and how battery degradation costs distort operating strategies, resulting in unnecessary cost increases and energy waste.

[0004] Therefore, how to achieve large-scale energy sharing based on real-time perception of battery health status, thereby reducing unnecessary cost increases and energy waste, is an issue that needs to be urgently addressed at this stage. Summary of the invention

[0005] 1. Technical issues to be resolved

[0006] In view of the above-mentioned shortcomings and deficiencies of the prior art, the present invention provides a battery energy storage health management method and system based on energy sharing, which solves the technical problem of how to achieve energy sharing over a large range based on real-time perception of battery health status, thereby reducing unnecessary cost increases and energy waste.

[0007] (II) Technical solution

[0008] In order to achieve the above object, the main technical solutions adopted by the present invention include:

[0009] In a first aspect, an embodiment of the present invention provides a battery energy storage health management method based on energy sharing, the method is based on an aggregator and at least one user end, and an energy storage device corresponding to each user end, including:

[0010] S11, the aggregator obtains the current charging and discharging data of all user-side energy storage devices in real time, and obtains the current battery health status of each energy storage device based on the current charging and discharging data of each energy storage device and the preset initial data of the energy storage device;

[0011] S12, the aggregator inputs the current battery health status of each energy storage device into a preset equivalent circuit model to obtain the current system efficiency and power capacity of each energy storage device;

[0012] S13. The aggregator shares energy among all energy storage devices according to the current battery health status, efficiency and power capacity of all energy storage devices and based on a pre-set health-conscious energy management strategy, generates an energy scheduling plan corresponding to each user end and sends it to the corresponding user end; the health-conscious energy management strategy is a strategy for minimizing the total cost of the group by sharing and scheduling energy among user-end energy storage devices.

[0013] Optionally, the initial data of each energy storage device includes initial capacity, rated capacity, power limit, initial internal resistance, final internal resistance, battery initial health state, battery final health state and initial power capacity.

[0014] Optionally, before S11, the step further includes:

[0015] S10. Any user terminal inputs the energy storage voltage and energy storage current of the energy storage device detected in real time into a preset nonlinear state space model to obtain the current state of charge and charging and discharging power of the energy storage device, and sends the current charging and discharging data of the energy storage device to the aggregator; the charging and discharging data includes energy storage voltage, energy storage current, charging and discharging power and state of charge.

[0016] Optionally, the S11 further includes:

[0017] Whenever the aggregator obtains the charging and discharging data of any energy storage device, the device code, charging and discharging data and corresponding time of the energy storage device are saved as the historical charging and discharging data corresponding to the energy storage device.

[0018] Optionally, the charging and discharging data includes energy storage voltage and energy storage current;

[0019] The S11 includes:

[0020] The aggregator obtains the current power of each energy storage device based on the historical charge and discharge data and current charge and discharge data corresponding to each energy storage device and a preset formula 1; the formula 1 is:

[0021]

[0022] Among them, Q(t) is the current amount of the energy storage device, and I(t) is the current at time t;

[0023] According to the power of any energy storage device at the current moment, the initial capacity and rated capacity of the energy storage device, and a preset formula 2, the current battery health status of the energy storage device is obtained; the formula 2 is:

[0024]

[0025] Among them, S t is the current battery health status of the energy storage device, E 0 is the initial capacity of the energy storage device, and C is the rated capacity of the energy storage device.

[0026] Optionally, the S11 further includes:

[0027] The aggregator obtains the current total charge and discharge capacity of each energy storage device based on the historical charge and discharge data corresponding to the energy storage device;

[0028] And according to the current battery health state, the starting battery health state, the ending battery health state and the total charge and discharge amount of the energy storage, and the preset formula three, the change of the battery health state corresponding to the energy storage device is obtained;

[0029]

[0030] Among them, S Δ is the change of the battery health status corresponding to the energy storage device, S 0 and S 1 are the initial health state of the battery and the final health state of the battery, D is the current total charge and discharge capacity of the energy storage device, θ k is the actual DoD set in advance, n t,θ The preset transformation DoD depth.

[0031] Optionally, the charging and discharging data includes energy storage voltage and energy storage current;

[0032] Then the S12 includes:

[0033] Input the current battery health status of each energy storage device into a preset equivalent circuit model to obtain the current efficiency and power capacity of each energy storage device;

[0034] During this period, the aggregator obtains the current system efficiency of each energy storage device based on the current charging and discharging data of each energy storage device acquired in real time, the current battery health status and the preset initial data of the energy storage device, as well as the preset formula 4; the formula 4 is:

[0035]

[0036] Among them, Z 0 is the initial internal resistance of the energy storage device, Z1 is the end internal resistance of the energy storage device, S 0 is the initial health state of the battery of the energy storage device, S 1 The battery ends the health state, S t is the current battery health status of the energy storage device, I is the energy storage current of the energy storage device, and U is the energy storage voltage of the energy storage device;

[0037] The current power capacity is obtained according to the preset initial data and the preset formula 5; the formula 5 is:

[0038]

[0039] Among them, Z 0 is the initial internal resistance of the energy storage device, Z 1 is the end internal resistance of the energy storage device, S 0 is the initial health state of the battery of the energy storage device, S 1 The battery ends the health state, S t is the current battery health status of the energy storage device, P 0 is the initial power capacity.

[0040] Optionally, the S12 further includes:

[0041] The aggregator obtains the current open circuit voltage of each energy storage device based on the current battery health status and charge and discharge data of each energy storage device, as well as the preset battery initial health status, battery final health status, initial internal resistance and final internal resistance, based on the preset formula 6; the formula 6 is:

[0042]

[0043] Among them, V oc is the current open circuit voltage of the energy storage device, V t and I t are the voltage and current of the energy storage device at the current moment, Z t is the current internal resistance of the energy storage device, Z 0 is the initial internal resistance of the energy storage device, Z 1 is the end internal resistance of the energy storage device, S 0 is the initial health state of the battery of the energy storage device, S 1 End health status for the battery;

[0044] According to the current open circuit voltage of each energy storage device and the pre-established voltage-SoC relationship curve, the current state of charge of each energy storage device is obtained;

[0045] The charging and discharging power is obtained according to the energy storage current and energy storage voltage of each energy storage device and the preset formula 7; the formula 7 is:

[0046] P t =I t V t ;

[0047] Where V t and I t are the voltage and current of the energy storage device at the current moment respectively.

[0048] Optionally, the group total cost includes: battery degradation cost, aggregator net cost and user net cost of all user terminals;

[0049] The health-conscious energy management strategies are:

[0050]

[0051] where f A is the aggregator net cost, is the battery degradation cost of user terminal i at time t, is the net cost of user at user terminal i.

[0052] In a first aspect, an embodiment of the present invention provides a battery energy storage health management system based on energy sharing, comprising a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the battery energy storage health management method based on energy sharing as described in any one of claims 1 to 9.

[0053] (III) Beneficial effects

[0054] The beneficial effects of the present invention are as follows: a battery energy storage health management method based on energy sharing of the present invention incorporates the accelerated degradation and health status caused by quantitative storage sharing into shared management, and realizes energy sharing over a large range based on real-time perception of battery health status, thereby reducing unnecessary costs and energy waste. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 A flow chart of a battery energy storage health management method based on energy sharing;

[0056] Figure 2 This is the structural diagram of the equivalent circuit model. DETAILED DESCRIPTION

[0057] In order to better explain the present invention and facilitate understanding, the present invention is described in detail below through specific implementation modes in conjunction with the accompanying drawings.

[0058] A battery energy storage health management method based on energy sharing proposed in an embodiment of the present invention incorporates the accelerated degradation and health status caused by quantified storage sharing into shared management, and realizes energy sharing over a large range based on real-time perception of battery health status, thereby reducing unnecessary costs and energy waste.

[0059] In order to better understand the above technical solution, exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided to enable a clearer and more thorough understanding of the present invention and to fully convey the scope of the present invention to those skilled in the art.

[0060] Example 1

[0061] This embodiment provides a battery energy storage health management method based on energy sharing, which is based on an aggregator and at least one user end; during operation, the more the battery is used, the more serious the battery health state (SoH) of the energy storage system is degraded. In an aggregator, N user ends are organized in the distribution network, each of which has an energy storage device, a photovoltaic (PV) system and a local load, and the aggregator generally includes a storage module, a cloud module and an analysis module. The user end and the aggregator make decisions as a whole. The aggregator charges the user a net load fee at a retail price and pays the user for excess electricity at a net metering price. At the user end, the user needs to perceive the operation data and charge and discharge data of the energy storage device through a monitor, and upload the operation data and charge and discharge data to the cloud module. The initial data of the energy storage device is usually written on the nameplate, including the initial capacity, rated capacity, power limit, initial internal resistance, end internal resistance, battery initial health state, battery end health state and initial power capacity of the energy storage device. Usually, it is uploaded to the aggregator in advance for storage, and for the energy storage device in the location state, a complete charge and discharge cycle can be performed to save the obtained data as the initial data. Optionally, during actual operation, the user side measures the energy storage voltage and energy storage current of the energy storage device through a monitor, and indirectly calculates the real-time charge state of the battery with the help of a nonlinear state space model, and the charging and discharging power of the energy storage can also be obtained.

[0062] The user-side measurement data is uploaded to the network through the CAN bus protocol and then uploaded to the terminal through the commonly used ISM (industrial science and medical) frequency band. The data is analyzed and processed in the cloud module. The aggregator processes the data with the goal of minimizing the group cost (total group cost), obtains the operation strategy of each user, and passes these strategies (energy scheduling plans) to the user side, and continues this cycle at the beginning of the next time period.

[0063] In general, the user-edge server-cloud server architecture is used between N user terminals and aggregators, in which a large number of user terminals are tasked with collecting data in the entire target perception area. After initiating a request on the aggregator side, they generate data and interact with the edge server and aggregator, mainly responsible for data collection on the user side. The edge server is a computing node deployed at the edge of the network. It is close to the user terminal and can be a local data center, network equipment, or a dedicated edge computing device. Function: Mainly responsible for the preliminary processing and data processing of user requests, including caching, data preprocessing, real-time data analysis, etc. The edge server aims to reduce latency, improve response speed, and reduce the burden on the cloud server. The aggregator is responsible for large-scale data storage and analysis. Specifically, all data can be compressed in the edge server to reduce the amount of data transmitted to the aggregator and relieve the pressure on the aggregator. In general, the data in the area can be compressed at the edge layer through the idea of ​​compressed sensing, that is, the complete data of all users from the first moment to the tth moment can be compressed. For a single user p, the perception data obtained after t moments is When using the principle of compressed sensing for data collection, it is necessary to p The sparsity of the collected perception data is analyzed to determine whether the collected data is compressible. In general, the discrete cosine transform can be used to analyze the sparsity of the collected data. When the perception data can be compressed, some time points can be selected through the row vectors in the observation matrix. The weighted measurement value of the collected perception data multiplied by the corresponding element in the observation matrix at the selected time point is generated on the edge server. The measurement value submitted by a single user can be expressed as in is the collection coefficient.

[0064] In the data compression process of the user end, the data collected by the edge node is the weighted sum of the perception data of all perception moments, rather than simply superimposing all the perception data. Compressing the data in this way can reduce the amount of data transmitted to the aggregator. In this process, the observation matrix usually selects a Gaussian random matrix. At different perception moments, the user end uses t* different acquisition coefficients to weight the perception data collected at the current moment to form t* observation values ​​for storage. After that, t* observation values ​​are formed each time a perception moment passes, and are added to the observation values ​​stored at the previous moment to become new t* observation values, until the user end forms the final t* observation values ​​at the moment when the data needs to be collected, and then the entire data is compressed at the edge server.

[0065] The observation value collected by the edge node for a single user is User in t1 The sensory data x collected at all times 1 Multiply by the collection factor Then send the data to t 2 time; t 2 Time will be t 1 The observed value at time t 2 The perception data x collected by the user at the moment 2 Multiply by the collection factor The sum of the weighted values ​​is sent to the next moment until the user end has collected the data within its perception time and has observed t* times. The observation value of user p at the moment t* is Where t*< <t。

[0066] A battery energy storage health management method based on energy sharing, such as Figure 1 As shown, including:

[0067] The aggregator obtains the current charge and discharge data of all user-side energy storage devices in real time, and whenever the aggregator obtains the charge and discharge data of any energy storage device, it saves the device code, charge and discharge data and corresponding time of the energy storage device as the historical charge and discharge data corresponding to the energy storage device, and obtains the current battery health status of each energy storage device based on the current charge and discharge data of each energy storage device and the preset initial data of the energy storage device. The charge and discharge data include energy storage voltage and energy storage current. Specifically, the aggregator obtains the current power of the energy storage device based on the historical charge and discharge data and current charge and discharge data corresponding to each energy storage device, as well as the preset formula one; the formula one is:

[0068]

[0069] Among them, Q(t) is the current amount of the energy storage device, and I(t) is the current at time t;

[0070] According to the power of any energy storage device at the current moment, the initial capacity and rated capacity of the energy storage device, and a preset formula 2, the current battery health status of the energy storage device is obtained; the formula 2 is:

[0071]

[0072] Among them, S t is the current battery health status of the energy storage device, E 0 is the initial capacity of the energy storage device, and C is the rated capacity of the energy storage device.

[0073] The aggregator obtains the current total charge and discharge capacity of each energy storage device based on the historical charge and discharge data corresponding to the energy storage device;

[0074] And according to the current battery health state, the starting battery health state, the ending battery health state and the total charge and discharge amount of the energy storage, and the preset formula three, the change of the battery health state corresponding to the energy storage device is obtained;

[0075]

[0076] Among them, S Δ is the change of the battery health status corresponding to the energy storage device, S 0 and S 1 are the initial health state of the battery and the final health state of the battery, D is the current total charge and discharge capacity of the energy storage device, θ k is the actual DoD set in advance, n t,θ The preset transformation DoD depth.

[0077] The current battery health status of each energy storage device is input into a preset equivalent circuit model to obtain the current efficiency and power capacity of each energy storage device; the equivalent circuit model is as follows Figure 2 shown.

[0078] During this period, the aggregator obtains the current system efficiency of each energy storage device based on the current charging and discharging data of each energy storage device acquired in real time, the current battery health status and the preset initial data of the energy storage device, as well as the preset formula 4; the formula 4 is:

[0079]

[0080] Among them, Z 0 is the initial internal resistance of the energy storage device, Z 1 is the end internal resistance of the energy storage device, S 0 is the initial health state of the battery of the energy storage device, S 1 The battery ends the health state, S t is the current battery health status of the energy storage device, I is the energy storage current of the energy storage device, and U is the energy storage voltage of the energy storage device;

[0081] The current power capacity is obtained according to the preset initial data and the preset formula 5; the formula 5 is:

[0082]

[0083] Among them, Z 0 is the initial internal resistance of the energy storage device, Z 1 is the end internal resistance of the energy storage device, S 0 is the initial health state of the battery of the energy storage device, S 1 The battery ends the health state, St is the current battery health status of the energy storage device, P 0 is the initial power capacity.

[0084] The aggregator obtains the current open circuit voltage of each energy storage device based on the current battery health status and charge and discharge data of each energy storage device, as well as the preset battery initial health status, battery final health status, initial internal resistance and final internal resistance, based on the preset formula 6; the formula 6 is:

[0085]

[0086] Among them, V oc is the current open circuit voltage of the energy storage device, V t and I t are the voltage and current of the energy storage device at the current moment, Z t is the current internal resistance of the energy storage device, Z 0 is the initial internal resistance of the energy storage device, Z 1 is the end internal resistance of the energy storage device, S 0 is the initial health state of the battery of the energy storage device, S 1 End health status for the battery;

[0087] According to the current open circuit voltage of each energy storage device and the pre-established voltage-SoC relationship curve, the current state of charge of each energy storage device is obtained;

[0088] The charging and discharging power is obtained according to the energy storage current and energy storage voltage of each energy storage device and the preset formula 7; the formula 7 is:

[0089] P t =I t V t ;

[0090] Where V t and I t are the voltage and current of the energy storage device at the current moment respectively.

[0091] Optionally, the current state of charge of the energy storage device can be calculated by the user end. That is, any user end will input the energy storage voltage and energy storage current of the energy storage device detected in real time into a preset nonlinear state space model to obtain the current state of charge and charging and discharging power of the energy storage device, and send the current charging and discharging data of the energy storage device to the aggregator; the charging and discharging data includes energy storage voltage, energy storage current, charging and discharging power and state of charge.

[0092] The aggregator shares energy among all energy storage devices according to their current battery health status, efficiency and power capacity, and based on a preset health-conscious energy management strategy, generates an energy scheduling plan for each user end and sends it to the corresponding user end; the health-conscious energy management strategy is a strategy that achieves the minimum total cost of the group by sharing and scheduling energy among user-end energy storage devices.

[0093] Specifically, in order to describe the uncertainty of load (load) and solar energy (photovoltaic system), scenario-based stochastic programming is adopted. Here, it is assumed that the influence of distribution network and power loss is not considered. Therefore, the degradation cost of the battery can be quantified as follows: In the formula, is the battery degradation cost of user i in scenario s at time interval t, r s is the occurrence probability of scenario s, S i,t,s is the battery SoH of user i at time t in scenario s, The cost of purchasing a battery for a pre-set user i is assumed to be fully incurred at the end of the battery life.

[0094] The net cost to the aggregator is as follows:

[0095]

[0096] where

[0097]

[0098] in, and are the net load and net surplus power of user i respectively, and are the net load and net excess power of all users respectively, is the energy price (constant), is the electricity transaction cost with the grid, For retail profits to users, The cost of purchasing excess electricity from users.

[0099] The net cost of one user in the user net cost is as follows:

[0100]

[0101] subject to

[0102] To balance the rights;

[0103] is the power constraint of the energy storage device;

[0104] E min ≤e i,t,s ≤E i,t,s , is the capacity constraint of the energy storage device;

[0105] Real-time iteration of battery capacity;

[0106] e 0 =e T , to ensure that the actual SoC and the final SoC are equal;

[0107] The sum of the shared power of all users is zero;

[0108] are the upper and lower limits of the shared power.

[0109] in, is the utility function, a quadratic concave function. and They represent the load of user i and the power of PV respectively, and are the charging and discharging power of the energy storage device of user i, The energy shared by user i, and E i,t,s is the upper limit of battery power and capacity. i,t,s and η i,t,s are the energy storage SoC and efficiency of user i, E min For the smallest battery SoC, This is the transmission power limit of the fuse in the building. is the user's net load cost, The net power income of the user. During the optimization process, the battery (energy storage device) will operate with the goal of reducing costs, and the cost changes caused by charging and discharging are opposite, so no additional constraints are required to avoid charging and discharging the battery at the same time.

[0110] The aggregator and the user make decisions as a whole. The goal is to minimize the total cost of the entire group, which includes: battery degradation cost, aggregator net cost and user net cost of all user terminals;

[0111] The health-conscious energy management strategies are:

[0112]

[0113] where f A is the aggregator net cost, is the battery degradation cost of user terminal i at time t, is the net cost of user at user terminal i.

[0114] This embodiment proposes a battery energy storage health management method based on energy sharing, which incorporates the accelerated degradation and health status caused by quantitative storage sharing into shared management, and realizes energy sharing over a large range based on real-time perception of battery health status, thereby reducing unnecessary costs and energy waste.

[0115] Example 2

[0116] An embodiment of the present invention provides a battery energy storage health management system based on energy sharing, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the battery energy storage health management method based on energy sharing described in Example 1.

[0117] In the description of the present invention, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0118] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium; it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0119] In the present invention, unless otherwise clearly specified and limited, when a first feature is “on” or “below” a second feature, it may be that the first and second features are in direct contact, or that the first and second features are in indirect contact through an intermediate medium. Moreover, when a first feature is “above”, “above” or “above” a second feature, it may be that the first feature is directly above or obliquely above the second feature, or it may simply mean that the first feature is higher in level than the second feature. When a first feature is “below”, “below” or “below” a second feature, it may be that the first feature is directly below or obliquely below the second feature, or it may simply mean that the first feature is lower in level than the second feature.

[0120] In the description of this specification, the description of the terms "one embodiment", "some embodiments", "embodiment", "example", "specific example" or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are contradictory.

[0121] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may alter, modify, replace and modify the above embodiments within the scope of the present invention.

Claims

1. A battery energy storage health management method based on energy sharing, the method is based on an aggregator and at least one user end, and an energy storage device corresponding to each user end, characterized in that: include: S11, the aggregator obtains the current charging and discharging data of all user-side energy storage devices in real time, and obtains the current battery health status of each energy storage device based on the current charging and discharging data of each energy storage device and the preset initial data of the energy storage device; S12, the aggregator inputs the current battery health status of each energy storage device into a preset equivalent circuit model to obtain the current system efficiency and power capacity of each energy storage device; S13. The aggregator shares energy among all energy storage devices according to the current battery health status, efficiency and power capacity of all energy storage devices and based on a pre-set health-conscious energy management strategy, generates an energy scheduling plan corresponding to each user end and sends it to the corresponding user end; the health-conscious energy management strategy is a strategy for minimizing the total cost of the group by sharing and scheduling energy among user-end energy storage devices.

2. The battery energy storage health management method based on energy sharing according to claim 1 is characterized in that: The initial data of each energy storage device includes initial capacity, rated capacity, power limit, initial internal resistance, final internal resistance, battery initial health state, battery final health state and initial power capacity.

3. The battery energy storage health management method based on energy sharing according to claim 1 is characterized in that: The S11 and before also include: S10. Any user terminal inputs the energy storage voltage and energy storage current of the energy storage device detected in real time into a preset nonlinear state space model to obtain the current state of charge and charging and discharging power of the energy storage device, and sends the current charging and discharging data of the energy storage device to the aggregator; the charging and discharging data includes energy storage voltage, energy storage current, charging and discharging power and state of charge.

4. The battery energy storage health management method based on energy sharing according to claim 2 is characterized in that: The S11 further includes: Whenever the aggregator obtains the charging and discharging data of any energy storage device, the device code, charging and discharging data and corresponding time of the energy storage device are saved as the historical charging and discharging data corresponding to the energy storage device.

5. The battery energy storage health management method based on energy sharing according to claim 4 is characterized in that: The charging and discharging data include energy storage voltage and energy storage current; The S11 includes: The aggregator obtains the current power of each energy storage device based on the historical charge and discharge data and current charge and discharge data corresponding to each energy storage device and a preset formula 1; the formula 1 is: Among them, Q(t) is the current amount of the energy storage device, and I(t) is the current at time t; According to the power of any energy storage device at the current moment, the initial capacity and rated capacity of the energy storage device, and a preset formula 2, the current battery health status of the energy storage device is obtained; the formula 2 is: Among them, S t is the current battery health status of the energy storage device, E0 is the initial capacity of the energy storage device, and C is the rated capacity of the energy storage device.

6. The battery energy storage health management method based on energy sharing according to claim 5 is characterized in that: The S11 further includes: The aggregator obtains the current total charge and discharge capacity of each energy storage device based on the historical charge and discharge data corresponding to the energy storage device; And according to the current battery health state, the starting battery health state, the ending battery health state and the total charge and discharge amount of the energy storage, and the preset formula three, the change of the battery health state corresponding to the energy storage device is obtained; Among them, S Δ is the change of the battery health status corresponding to the energy storage device, S0 and S1 are the battery start health status and battery end health status respectively, D is the current total charge and discharge capacity of the energy storage device, θ k is the actual DoD set in advance, n t,θ The preset transformation DoD depth.

7. The battery energy storage health management method based on energy sharing according to claim 2 is characterized in that: The charging and discharging data include energy storage voltage and energy storage current; Then the S12 includes: Input the current battery health status of each energy storage device into a preset equivalent circuit model to obtain the current efficiency and power capacity of each energy storage device; During this period, the aggregator obtains the current system efficiency of each energy storage device based on the current charging and discharging data of each energy storage device acquired in real time, the current battery health status and the preset initial data of the energy storage device, as well as the preset formula 4; the formula 4 is: Among them, Z0 is the initial internal resistance of the energy storage device, Z1 is the final internal resistance of the energy storage device, S0 is the initial health state of the battery of the energy storage device, S1 is the final health state of the battery, S t is the current battery health status of the energy storage device, I is the energy storage current of the energy storage device, and U is the energy storage voltage of the energy storage device; The current power capacity is obtained according to the preset initial data and the preset formula 5; the formula 5 is: Among them, Z0 is the initial internal resistance of the energy storage device, Z1 is the final internal resistance of the energy storage device, S0 is the initial health state of the battery of the energy storage device, S1 is the final health state of the battery, S t is the current battery health status of the energy storage device, and P0 is the initial power capacity.

8. The battery energy storage health management method based on energy sharing according to claim 7 is characterized in that: The S12 further includes: The aggregator obtains the current open circuit voltage of each energy storage device based on the current battery health status and charge and discharge data of each energy storage device, as well as the preset battery initial health status, battery final health status, initial internal resistance and final internal resistance, based on the preset formula 6; the formula 6 is: Among them, V oc is the current open circuit voltage of the energy storage device, V t and I t are the voltage and current of the energy storage device at the current moment, Z t is the current internal resistance of the energy storage device, Z0 is the initial internal resistance of the energy storage device, Z1 is the final internal resistance of the energy storage device, S0 is the initial health state of the battery of the energy storage device, and S1 is the final health state of the battery; According to the current open circuit voltage of each energy storage device and the pre-established voltage-SoC relationship curve, the current state of charge of each energy storage device is obtained; The charging and discharging power is obtained according to the energy storage current and energy storage voltage of each energy storage device and the preset formula 7; the formula 7 is: P t =I t V t ; Where V t and I t are the voltage and current of the energy storage device at the current moment respectively.

9. The battery energy storage health management method based on energy sharing according to claim 1 is characterized in that: The total group cost includes: battery degradation cost, aggregator net cost and user net cost of all user terminals; The health-conscious energy management strategies are: where f A is the aggregator net cost, is the battery degradation cost of user terminal i at time t, is the net cost of user at user terminal i.

10. A battery energy storage health management system based on energy sharing, comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the battery energy storage health management method based on energy sharing as described in any one of claims 1 to 9.

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