Power control method and system based on energy storage unit adjustment priority evaluation

Abstract

The power control method and system based on energy storage unit adjustment priority evaluation, the energy storage unit calibrates its state of charge, battery capacity and health state and feeds back to the battery management system, the battery management system verifies the battery state estimation model built in the battery management system by using the calibrated state of charge and health state; based on the calibrated state of charge and battery capacity, the energy state difference is calibrated; based on the measurement accuracy of the sensor, the voltage standard deviation coefficient, voltage difference and temperature difference are calibrated; the weighted sum of the scores of the evaluation indexes of the calibrated energy storage unit is taken as the comprehensive evaluation score; the adjustment priority of the allowed adjustment energy storage unit is determined by using the comprehensive evaluation score and the number of charge and discharge cycles of the allowed adjustment energy storage unit; the energy storage unit with the highest adjustment priority is selected as the execution unit to respond to the scheduling target power instruction, while ensuring the safe and stable operation of the energy storage system.

Description

Technical Field

[0001] The present invention belongs to the technical field of control of energy storage power stations, and in particular relates to a power control method and system for an energy storage power station based on energy storage unit regulation priority evaluation. Background Art

[0002] Energy storage power stations are a crucial technology for maintaining the safe operation of power grids. By storing energy and releasing it when needed, they can effectively balance grid load fluctuations and mitigate operational instability issues arising from the integration of renewable energy sources. Furthermore, they provide ancillary services such as peak shaving, frequency regulation, backup, and black start, improving the overall performance and reliability of the grid. The safe and stable operation of energy storage systems is fundamental to their effectiveness. Unstable operation can lead to power system failures and even grid accidents, negatively impacting the economy and society. Therefore, improving the safety of energy storage power stations is an urgent issue.

[0003] In the existing technology, when energy storage power stations participate in regulation, the power instructions for each energy storage unit are not distributed reasonably, which can easily lead to damage to battery performance, failure, and even safety accidents. At present, the main basis for evaluating the regulation priority of energy storage units is SOC (state of charge) and SOH (state of health), but the actual unit status is affected by many factors, and a comprehensive evaluation must be completed by combining multiple factors. In addition, SOC and SOH are core indicators for unit status evaluation, and the accuracy of the estimated values ​​must be improved to ensure accurate status evaluation. In addition, the energy storage system needs to respond to multiple scheduling goals, and there are many constraints when participating in regulation. When each energy storage unit executes the scheduling instruction, if a simple full output and fixed coefficient allocation strategy is adopted, the maintenance effect on battery life and performance will be insufficient, affecting the safe operation of the energy storage system. Summary of the Invention

[0004] In order to address the deficiencies in the prior art, the present invention provides a power control method and system based on energy storage unit regulation priority evaluation, which optimizes the power instruction allocation effect based on the energy storage unit regulation priority. First, six key indicators are screened out to construct a comprehensive evaluation model for the energy storage unit status, while improving the estimation accuracy of core indicators to achieve accurate status evaluation; then, the energy storage unit regulation priority is evaluated in combination with PCS monitoring data and the number of charge and discharge cycles; finally, the scheduling target and the energy storage unit regulation priority evaluation results are comprehensively utilized to dynamically divide the regulation execution domain, thereby ensuring the safe and stable operation of the energy storage system while achieving the scheduling target.

[0005] The present invention adopts the following technical solutions.

[0006] The present invention proposes a power control method based on energy storage unit regulation priority evaluation, comprising:

[0007] The characteristic data of the operating state of the energy storage unit is acquired to establish evaluation indexes of the state of the energy storage unit, including state of charge, state of health, energy state range, voltage standard deviation coefficient, voltage range and temperature range;

[0008] The state of charge and the state of health of the energy storage unit are calibrated by the energy storage unit; the calibrated state of charge and the state of health of the energy storage unit are fed back to the battery management system, and the calibrated state of charge and the state of health are used to verify the built-in battery state estimation model of the battery management system to obtain a verified battery state estimation model;

[0009] The energy state range is calibrated based on the calibrated state of charge and the battery capacity; the voltage standard deviation coefficient, the voltage range and the temperature range are calibrated based on the measurement accuracy of the sensor;

[0010] The weighted sum of the scores of the calibrated evaluation indexes of the energy storage unit is taken as a comprehensive evaluation score; the energy storage units allowed to be adjusted are screened according to the monitoring data, and the comprehensive evaluation score and the number of charge and discharge cycles of the energy storage units allowed to be adjusted are used to determine the adjustment priority of the energy storage units allowed to be adjusted;

[0011] When the scheduling target power is less than the rated power of the energy storage units allowed to be adjusted, the energy storage unit allowed to be adjusted with the highest adjustment priority is selected as an execution unit for responding to the scheduling target power instruction;

[0012] When the scheduling target discharge power is not less than the rated power of the energy storage units allowed to be adjusted and less than 90% of the rated power of the energy storage power station, the energy storage units allowed to be adjusted are selected in turn as execution units for responding to the scheduling target discharge power instruction in order of the adjustment priority of the energy storage units allowed to be adjusted from high to low; the state of charge target value of each execution unit is calculated by the battery management system according to the state of charge and the state of health of each execution unit output by the verified battery state estimation model; the scheduling target discharge power is distributed to the execution units satisfying the joint constraint condition based on the state of charge target value of each execution unit, and the execution units failing to satisfy the joint constraint condition respond to the scheduling target discharge power instruction at the rated power;

[0013] When the scheduling target charge power is not less than 90% of the rated power of the energy storage power station, all the energy storage units allowed to be adjusted are execution units for responding to the scheduling target power instruction; the state of charge target value of each execution unit is calculated by the battery management system according to the state of charge and the state of health of each execution unit output by the verified battery state estimation model; the scheduling target charge power is distributed to the execution units satisfying the joint constraint condition based on the state of charge target value of each execution unit, and the execution units failing to satisfy the joint constraint condition respond to the scheduling target discharge power instruction at the rated power.

[0014] Preferably, the characteristic data of the operating state of the energy storage unit is acquired, and an evaluation index of the state of the energy storage unit is constructed using the characteristic data, including:

[0015] The monitoring data of the battery management system and the energy storage converter is collected, and the characteristic data related to the operating state of the energy storage unit is extracted from the monitoring data sent by the battery management system;

[0016] The evaluation index of the state of the energy storage unit is selected from the characteristic data, including the state of charge, the state of health, the energy state range, the voltage standard deviation coefficient, the voltage range and the temperature range.

[0017] Preferably, the Kalman filtering method based on the center error entropy criterion is used for each energy storage unit, and the state of charge, the battery capacity and the state of health of the energy storage unit are calibrated based on the equivalent circuit of the battery, including:

[0018] Based on the second-order RC circuit of the battery, the state of charge is calibrated using the Kalman filtering method based on the center error entropy criterion, taking the state of charge as the state variable and the battery voltage as the observation variable, and the difference between the calibrated state of charge and the state of charge estimated by the battery management system is taken as the state of charge estimation error;

[0019] Based on the second-order RC circuit of the battery, the battery capacity is calibrated using the Kalman filtering method based on the center error entropy criterion, taking the battery capacity as the state variable and the state of charge estimation error as the observation variable, and the state of health is calibrated based on the calibrated battery capacity;

[0020] The calibrated state of charge, battery capacity and state of health are fed back to the battery management system of the energy storage unit.

[0021] Preferably, the calibrated state of charge and the state of health of the energy storage unit are fed back to the battery management system, and the battery state estimation model built-in the battery management system is verified using the calibrated state of charge and the state of health, to obtain a verified battery state estimation model, including:

[0022] The calibrated state of charge and the state of health of the energy storage unit are fed back to the battery management system, and the collected data of the energy storage unit is fused with the calibrated state of charge and the state of health to form a battery state data set;

[0023] The battery management system uses the battery status data set to verify the battery status estimation model built into the battery management system. When the error between the state of charge and health status output by the battery status estimation model and the state of charge and health status after calibration of the energy storage unit is not greater than the set limit, the battery status estimation model at this time is used as the verified battery status estimation model; when the error between the state of charge and health status output by the battery status estimation model and the state of charge and health status after calibration is greater than the set limit, the battery management system sends a signal to the corresponding energy storage unit to recalibrate the state of charge and health status.

[0024] Preferably, the weighted sum of the scores of the calibrated evaluation indicators of the energy storage unit is used as the comprehensive evaluation score, including:

[0025] The subjective weights of the calibrated evaluation indicators are calculated using a quantitative method, and the objective weights of the calibrated evaluation indicators are calculated using a principal component analysis method. The subjective weights and objective weights of the evaluation indicators are proportionally integrated to obtain the weights of the calibrated evaluation indicators. Based on the set scoring rules, each calibrated evaluation indicator is scored separately.

[0026] Using the calibrated scores and weights of each evaluation indicator, the comprehensive evaluation score K of the energy storage unit is calculated using the following relationship:

[0027]

[0028] Where α, β, χ, φ, η, and θ are the voltage range difference U after calibration. r Rating R(U r ), voltage standard deviation after calibration U d Rating R(U d ), the temperature range after calibration T r Rating R(T r ), the score R(SOC) of the state of charge SOC after calibration, and the extreme energy state SOE after calibration r Rating R(SOE r ) and the weight coefficient corresponding to the calibrated health status SOH score R(SOH).

[0029] Preferably, the energy storage units that are allowed to be adjusted are screened out based on the monitoring data, and the adjustment priority of the energy storage units that are allowed to be adjusted is determined using the comprehensive evaluation scores and the number of charge and discharge cycles of the energy storage units that are allowed to be adjusted, including:

[0030] The monitoring data is used to determine whether each energy storage unit is an allowed adjustment energy storage unit, and the allowed adjustment energy storage units are sorted in descending order of the comprehensive evaluation scores; the non-allowed adjustment energy storage units are arranged at the end of the sorting result of the allowed adjustment energy storage units, and the adjustment priority of the non-allowed adjustment energy storage units is zero;

[0031] Based on the sorting result of the allowed adjustment energy storage units, among any two allowed adjustment energy storage units, the adjustment priority of the allowed adjustment energy storage unit with a larger comprehensive evaluation score is high, and the adjustment priority of the allowed adjustment energy storage unit with a smaller comprehensive evaluation score is low;

[0032] Based on the sorting result of the allowed adjustment energy storage units, when the jth allowed adjustment energy storage unit and the j+1th allowed adjustment energy storage unit have the same comprehensive evaluation score, the comprehensive evaluation scores of the j-1th allowed adjustment energy storage unit and the j+2th allowed adjustment energy storage unit are obtained, and the charge and discharge cycle numbers of the jth allowed adjustment energy storage unit and the j+1th allowed adjustment energy storage unit are obtained; the adjustment priorities of the jth allowed adjustment energy storage unit and the j+1th allowed adjustment energy storage unit are respectively calculated according to the following relationship:

[0033]

[0034] In the formula, M j and M j+1 are the adjustment priorities of the jth allowed adjustment energy storage unit and the j+1th allowed adjustment energy storage unit, respectively, K j-1 and K j+2 are the comprehensive evaluation scores of the j-1th allowed adjustment energy storage unit and the j+2th allowed adjustment energy storage unit, respectively, C j and C j+1 are the charge and discharge cycle numbers of the jth allowed adjustment energy storage unit and the j+1th allowed adjustment energy storage unit, respectively.

[0035] Among the multiple allowed adjustment energy storage units with the same comprehensive evaluation score, the allowed adjustment energy storage unit with a smaller charge and discharge cycle number has a higher corresponding adjustment priority.

[0036] Preferably, the battery management system estimates the state of charge and the state of health of each execution unit according to the verified battery state estimation model output, and calculates the state of charge target value of each execution unit according to the following relationship:

[0037]

[0038] In the formula, SOC ref,i,T is the state of charge target value of the ith execution unit at time T; SOC ideal is the calibrated state of charge of the execution unit; SOC i,T and SOHi,T are the state of charge and health status of the ith execution unit at time T output by the battery management system based on the verified battery state estimation model; SOC min , SOC max They are the lower limit and upper limit of the state of charge of the energy storage unit; SOH min,T 、SOH max,T are the lower limit and upper limit of the health state of the energy storage unit at time T respectively;

[0039] Based on the target state of charge of each execution unit, the ideal discharge power of each execution unit is calculated using the following relationship:

[0040]

[0041] Where, is the ideal discharge power of the i-th execution unit at time T; P i rated is the rated power of the i-th energy storage unit;

[0042] Based on the target state of charge of each execution unit, the ideal discharge power of each execution unit is calculated using the following relationship:

[0043]

[0044] Where, is the ideal charging power of the i-th execution unit at time T.

[0045] Preferably, based on the proportion of the ideal discharge power of each execution unit in the sum of the ideal discharge powers of all execution units and according to the scheduling target discharge power, the discharge power allocated to each execution unit is calculated using the following relationship:

[0046]

[0047] Where, P dis,i,T is the discharge power allocated to the i-th execution unit at time T; N is the number of execution units, is the dispatch target discharge power at time T;

[0048] Based on the proportion of the ideal charging power of each execution unit in the sum of the ideal charging powers of all execution units and the scheduling target charging power, the charging power allocated to each execution unit is calculated using the following relationship:

[0049]

[0050] Where, P ch,i,T is the charging power allocated to the i-th execution unit at time T; N is the number of execution units; the scheduling target charging power for time T; the ideal charging power for the i-th execution unit at time T.

[0051] Preferably, the execution units satisfying the joint constraint condition respond to the scheduling target discharging power instruction according to the allocated discharging power; the execution units failing to satisfy the joint constraint condition respond to the scheduling target discharging power instruction according to the rated power;

[0052] The joint constraint condition of each execution unit is as follows:

[0053] The SOC constraint condition of the execution unit is as follows:

[0054] SOC min <SOC i,T <SOC max

[0055] The discharging power constraint condition of the execution unit is as follows:

[0056] 0≤P dis,i,T ≤P i rated

[0057] The SOC change constraint condition of the execution unit during discharging is as follows:

[0058]

[0059] wherein ΔT is a set time period, is the current capacity of the i-th execution unit;

[0060] The execution units satisfying the joint constraint condition respond to the scheduling target charging power instruction according to the allocated charging power; the execution units failing to satisfy the joint constraint condition respond to the scheduling target charging power instruction according to the rated power;

[0061] The joint constraint condition of each execution unit is as follows:

[0062] The SOC constraint condition of the execution unit is as follows:

[0063] SOC min <SOC i,T <SOC max

[0064] The charging power constraint condition of the execution unit is as follows:

[0065] 0≤P ch,i,T ≤P i rated

[0066] The SOC change constraint condition of the execution unit during charging is as follows:

[0067]

[0068] wherein, ΔT is a set time period, is the current capacity of the i th execution unit.

[0069] The application further provides a power control system based on energy storage unit adjustment priority evaluation, comprising:

[0070] The evaluation index establishing module is configured to obtain feature data of the operating state of the energy storage unit to establish evaluation indexes of the state of the energy storage unit, including the state of charge, the state of health, the energy state range, the voltage standard deviation coefficient, the voltage range and the temperature range.

[0071] The energy storage unit calibration module is configured to calibrate the state of charge, the battery capacity and the state of health of the energy storage unit by the energy storage unit; feed back the calibrated state of charge and the state of health of the energy storage unit to the battery management system, verify the built-in battery state estimation model of the battery management system by using the calibrated state of charge and the state of health, and obtain the verified battery state estimation model; and calibrate the energy state range based on the calibrated state of charge and the battery capacity; calibrate the voltage standard deviation coefficient, the voltage range and the temperature range based on the measurement accuracy of the sensor.

[0072] The adjustment priority calculation module is configured to take the weighted sum of the scores of the calibrated evaluation indexes of the energy storage unit as the comprehensive evaluation score; select the energy storage units allowed to be adjusted according to the monitoring data, and determine the adjustment priority of the energy storage units allowed to be adjusted by using the comprehensive evaluation score and the number of charge and discharge cycles of the energy storage units allowed to be adjusted.

[0073] The scheduling target power instruction response module is configured to select the energy storage unit allowed to be adjusted with the highest adjustment priority as the execution unit when the scheduling target power is less than the rated power of the energy storage unit allowed to be adjusted, and respond to the scheduling target power instruction.

[0074] When the scheduling target discharge power is not less than the rated power of the energy storage unit allowed to be adjusted and less than 90% of the rated power of the energy storage power station, the energy storage units allowed to be adjusted are selected in turn as the execution units for responding to the scheduling target discharge power instruction in the order from high to low according to the adjustment priority of each energy storage unit allowed to be adjusted; the battery management system calculates the state of charge target value of each execution unit according to the state of charge and the state of health of each execution unit output by the verified battery state estimation model; and the scheduling target discharge power is distributed to the execution units satisfying the joint constraint condition based on the state of charge target value of each execution unit, and the execution units failing to satisfy the joint constraint condition respond to the scheduling target discharge power instruction at the rated power.

[0075] When the scheduled target charging power is not less than 90% of the rated power of the energy storage power station, all the allowed adjustment energy storage units are execution units to respond to the scheduled target power instruction, the battery management system calculates the state of charge target value of each execution unit according to the state of charge and the state of health of each execution unit output by the verified battery state estimation model; based on the state of charge target value of each execution unit, the scheduled target charging power is distributed to the execution units that meet the joint constraint condition, and the execution units that cannot meet the joint constraint condition respond to the scheduled target discharging power instruction according to the rated power.

[0076] The beneficial effects of the present application at least include that, compared with the prior art, when evaluating the state of the energy storage unit, not only the two core indicators of SOC and SOH are considered, but also auxiliary indicators such as SOE range, voltage standard deviation coefficient, voltage range and temperature range are introduced, forming a more comprehensive evaluation system, ensuring accurate evaluation of the state of the energy storage unit.

[0077] When performing battery compartment level calibration, the present application improves the calibration accuracy of SOC and SOH, more accurately evaluates the actual state of the energy storage unit, and thus realizes more optimal power control instruction distribution, which helps to optimize the operation efficiency of the energy storage system, reduces energy loss, and improves overall energy utilization, optimizes power distribution and operation efficiency. Accurate SOC and SOH evaluation can provide more accurate data for the battery management system, thereby optimizing the charging and discharging strategy of the battery, reducing overcharging or overdischarging, and prolonging the service life of the battery. Through comprehensive calibration at the battery compartment level, overconsumption of individual battery modules can be effectively prevented, further prolonging the overall life of the battery system. BRIEF DESCRIPTION OF DRAWINGS

[0078] Figure 1 is a flowchart of a power control method based on energy storage unit adjustment priority evaluation proposed by the present application;

[0079] Figure 2 is a comparison chart of the model voltage of the energy storage unit battery cluster calculated based on the Kalman filtering of the center error entropy criterion and the voltage uploaded by the BMS in the embodiment of the present application;

[0080] Figure 3 is a comparison chart of the overall cumulative output of the energy storage power station when the power control strategy proposed by the present application is applied to power distribution and the commonly used strategy in the embodiment of the present application. DETAILED DESCRIPTION

[0081] In order to make the objects, technical solutions and advantages of the present application clearer, the technical solutions of the present application will be described clearly and completely below in conjunction with the accompanying drawings of the embodiments of the present application. The embodiments described in the present application are only a part of the embodiments of the present application, rather than all the embodiments. Based on the spirit of the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the protection scope of the present application.

[0082] The present application provides a power control method based on energy storage unit adjustment priority evaluation, as shown in Figure 1 The present application provides a power control method based on energy storage unit adjustment priority evaluation, as shown in

[0083] Step 1, obtaining characteristic data of the operating state of the energy storage unit to establish evaluation indexes of the state of the energy storage unit, including: state of charge, state of health, energy state range, voltage standard deviation coefficient, voltage range and temperature range.

[0084] Specifically, step 1 includes:

[0085] Step 1.1, collecting monitoring data of the battery management system (BMS) and the energy storage converter (PCS), and extracting characteristic data related to the operating state of the energy storage unit from the monitoring data sent by the BMS;

[0086] Specifically, the collected monitoring data of the BMS includes but is not limited to: voltage, temperature, state of charge (SOC), state of health (SOH), state of energy (SOE), charging and discharging current and cycle number of the battery, and the characteristic related to the operating state of the battery is extracted therefrom.

[0087] The collected monitoring data of the PCS includes but is not limited to: available power, actual power and adjustment state.

[0088] Step 1.2, screening evaluation indexes of the state of the energy storage unit from the characteristic data;

[0089] Specifically, the evaluation indexes screened from the characteristic include but are not limited to: SOC, SOH, SOE range, voltage standard deviation coefficient, voltage range and temperature range; wherein, SOC and SOH are monitoring data sent by the BMS; SOE range is calculated according to SOE data sent by the BMS; voltage standard deviation coefficient U d and voltage range U r are calculated according to voltage data sent by the BMS; temperature range T r is calculated according to temperature data sent by the BMS.

[0090] Among them, SOC and SOH represent the adjustment capacity of the energy storage unit, SOE range and voltage standard deviation coefficient represent the consistency between each energy storage unit, and voltage range and temperature range represent the working performance of the energy storage unit.

[0091] In the evaluation of the state of the energy storage unit, not only the two core indicators of SOC and SOH are considered, but also auxiliary indicators such as SOE range, voltage standard deviation coefficient, voltage range and temperature range are introduced, forming a more comprehensive evaluation system to ensure accurate evaluation of the state of the energy storage unit. Among them, SOC and SOH directly reflecting the regulation ability of the energy storage unit are used as core evaluation indicators.

[0092] Step 2, the energy storage unit calibrates its state of charge, battery capacity and health status; the calibrated state of charge and health status of the energy storage unit are fed back to the battery management system, and the battery management system verifies the built-in battery state estimation model of the battery management system using the calibrated state of charge and health status, to obtain the verified battery state estimation model.

[0093] Specifically, step 2 includes:

[0094] Step 2.1, each energy storage unit uses a Kalman filtering method based on a center error entropy criterion to calibrate the state of charge, battery capacity and health status of the energy storage unit based on the equivalent circuit of the battery.

[0095] The present application optimizes the parameter adjustment of the Kalman filtering algorithm by introducing the center error entropy criterion, thereby improving the estimation accuracy and stability of SOC and SOH. This method not only improves the real-time monitoring capability of the battery management system for the energy storage unit, but also effectively solves the problem of accuracy decline that may occur in the traditional filtering method in high dynamic environment, and realizes more accurate and reliable evaluation and control of the battery performance.

[0096] Specifically, based on the equivalent circuit of the battery, the energy storage unit uses a Kalman filtering method based on a center error entropy criterion to calibrate the state of charge and health status of the energy storage unit, including:

[0097] Based on the second-order RC circuit of the battery, the SOC is calibrated using a Kalman filtering method based on a center error entropy criterion, taking SOC as a state variable and battery voltage as an observation variable, and the difference between the calibrated SOC and the SOC estimated by the BMS system is used as the SOC estimation error; based on the second-order RC circuit of the battery, the battery capacity is calibrated using a Kalman filtering method based on a center error entropy criterion, taking the battery capacity as a state variable and the SOC estimation error as an observation variable, and the SOH is calibrated based on the calibrated battery capacity.

[0098] In the non-limiting preferred embodiment, the second-order RC circuit of the battery is used as the equivalent circuit of the battery, and those skilled in the art can select different circuits as the equivalent circuit of the battery according to the requirements of SOC and SOH calibration accuracy.

[0099] In the prior art, the BMS built-in battery state estimation model calibrates the SOC and SOH at the BMS level. The BMS level can only collect parameters such as voltage, current and temperature of the energy storage unit to estimate the SOC and SOH through the battery state estimation model. In addition to the fact that these collected parameters are affected by factors such as battery aging, environmental temperature and battery operating state, more importantly, the measurement accuracy of the battery monitor and the estimation accuracy of the power meter used by the BMS level will affect the estimation accuracy of the SOC and SOH. With the increase of running time, the error of the calibrated SOC and SOH at the BMS level gradually increases, resulting in a non-optimal distribution of the power control instructions of the energy storage power station. Therefore, the present application proposes to regard the entire battery cabin as a large battery, based on the equivalent circuit of the battery, and to calibrate the SOC and SOH at the battery cabin level by using the Kalman filtering method based on the center error entropy criterion. This can more accurately evaluate the SOC and SOH of the entire battery cabin, and this battery cabin level calibration can help identify potential problems of individual battery modules or battery packs in the battery cabin, find signs of failure in advance, and reduce the probability of system-level failure of the energy storage station, thereby improving the reliability of the entire energy storage station operation and the fault diagnosis capability of the energy storage station system level. In addition, the battery cabin level calibration is not affected by environmental condition uncertainties such as temperature changes and load fluctuations. Since the battery cabin level calibration considers the overall effect of the entire battery cabin, environmental condition uncertainties will not affect the overall effect, so the stability and robustness of the system can be improved, and the adaptability and stability of the system can be enhanced. The method proposed in the present application effectively avoids the influence of the measurement accuracy of the battery monitor and the estimation accuracy of the power meter on the calibration results of the SOC and SOH, and improves the accuracy and reliability of the calibration results.

[0100] Step 2.2, the state of charge and health state of the energy storage unit after calibration are fed back to the battery management system, the battery management system fuses the collected energy storage unit data with the calibrated state of charge and health state to form a battery state data set; the battery state data set is used to verify the battery state estimation model, when the error between the state of charge and health state output by the battery state estimation model and the state of charge and health state after calibration of the energy storage unit is not greater than the set limit value, the verified battery state estimation model is determined; when the error between the state of charge and health state output by the battery state estimation model and the state of charge and health state after calibration is greater than the set limit value, the battery management system sends a signal to the corresponding energy storage unit to recalibrate the state of charge and health state.

[0101] Specifically, step 2.2 includes:

[0102] Step 2.2.1, the state of charge, battery capacity and health state of the energy storage unit after calibration are transmitted to the BMS;

[0103] In a non-limiting preferred embodiment, the SOC and SOH data obtained based on the battery compartment level calibration are transmitted to the BMS through a communication network; wherein the communication network includes but is not limited to: CAN bus, RS-485.

[0104] Step 2.2.2, the BMS fuses the collected energy storage unit data with the calibrated SOC and SOH data of the energy storage unit to form a battery state data set;

[0105] In a non-limiting preferred embodiment, the energy storage unit data collected by the BMS itself includes but is not limited to: voltage, current, temperature.

[0106] Step 2.2.3, the battery state estimation model is verified using the battery state data set, and when the error between the SOC and SOH output by the battery state estimation model and the calibrated SOC and SOH of the energy storage unit is not greater than the set limit value, the battery state estimation model at this time is used as the verified battery state estimation model;

[0107] When the model is verified, based on the energy storage unit data and the calibrated SOC and SOH data of the energy storage unit, the parameters of the battery state estimation model in the BMS will be self-adaptively adjusted, and when the error between the SOC and SOH output by the battery state estimation model and the calibrated SOC and SOH of the energy storage unit is not greater than the set limit value, the parameters of the battery state estimation model at this time reach the optimal value, thereby obtaining the verified battery state estimation model, and the BMS uses the verified battery state estimation model to improve the estimation accuracy of the SOC and SOH.

[0108] When the error between the SOC and SOH output by the battery state estimation model and the calibrated SOC and SOH of the energy storage unit is greater than the set limit value, the battery management system sends a signal to the corresponding energy storage unit to recalibrate the state of charge and health; wherein the set limit value is 0.05.

[0109] In the method proposed in the present application, when the model is verified, there is a large deviation between the calibrated SOC and SOH data of the energy storage unit and the SOC and SOH estimation value of the BMS, and a signal will be sent to the corresponding energy storage unit to recalibrate the state of charge and health, thereby forming a closed-loop control of SOC and SOH calibration.

[0110] The battery management system performs charging or discharging control according to the state of charge and health output by the verified battery state estimation model.

[0111] In non-limiting preferred embodiments, based on the SOC and SOH estimation values output by the verified battery state estimation model, the BMS can optimize the charging and discharging strategies of the battery, for example, adjust the charging limit, discharge depth, prevent overcharging or overdischarging, to protect the battery. Based on the SOC and SOH estimation values output by the verified battery state estimation model, update the fault detection and early warning algorithm to improve the detection ability of potential faults of the battery. At the same time, periodically evaluate the long-term health of the battery, and perform life prediction and health analysis based on SOH data.

[0112] In the method proposed by the present application, the Kalman filter method based on the center error entropy criterion configures a feedback link, and the calibrated SOC and SOH are fed back to the BMS level. The BMS updates the built-in SOC and SOH estimation model using the calibrated SOC and SOH, so that the SOC and SOH estimation model is refined. This feedback mechanism can significantly improve the estimation accuracy of the battery state by the BMS, especially under complex or dynamic load conditions, and optimizes the battery management strategy. The feedback of the calibrated SOC and SOH can enable the BMS to adjust its estimation model in real time, improving the adaptive ability of the BMS. This dynamic adjustment mechanism enables the system to respond more quickly to changes in battery performance, such as aging and environmental temperature fluctuations, thereby maintaining high-precision battery state monitoring. Based on the updated SOC and SOH estimation model, the BMS estimates accurate SOC and SOH to optimize charging and discharging strategies, especially when the battery is aging or performance is declining, more intelligently adjusting the charging rate and discharge depth, thereby reducing stress and wear on the battery, prolonging battery life, and improving energy use efficiency. Moreover, the feedback mechanism can enhance the system's fault prediction capability. By obtaining accurate SOC and SOH data in real time, the BMS can identify potential faults earlier and take preventive measures, such as adjusting power output or issuing warnings, thereby reducing the risk of unexpected downtime or failure of the battery system and improving the system's fault prediction capability.

[0113] The present application realizes joint calibration of SOC and SOH from the battery compartment level and from the BMS level, effectively improving the calibration accuracy of SOC and SOH and ensuring accurate evaluation of the operating state of the energy storage unit. After each overall power adjustment of the energy storage power station, the battery compartment data periodically collected by the BMS will be updated, and the equivalent circuit model of the battery used for calibration will also be updated simultaneously. Therefore, the calibration process of adjusting SOC and SOH is fed back based on the updated battery compartment data and the equivalent circuit model of the battery. Feedback of the calibrated state of charge (SOC) and state of health (SOH) to the battery management system (BMS) of the energy storage unit is a key step that includes multiple operations and functions to ensure that the system can fully utilize these calibration results to optimize battery management and performance.

[0114] Step 3, calibrating the energy state margin based on the calibrated state of charge and the battery capacity; and calibrating the voltage standard deviation coefficient, the voltage margin and the temperature margin based on the measurement accuracy of the sensor.

[0115] The energy state is dynamically updated according to the real-time changes of the SOC and the battery capacity, and the accuracy of the SOE margin depends on the accuracy of the SOC and the battery capacity. Therefore, the SOE margin is calibrated based on the calibrated SOC and the calibrated battery capacity. On the basis of the improved accuracy of the SOC and the battery capacity, the accuracy of the SOE margin is also improved.

[0116] The errors of the voltage and the temperature are only related to the measurement accuracy of the sensor, and the voltage standard deviation coefficient, the voltage margin and the temperature margin are also only related to the measurement accuracy of the sensor. Therefore, the voltage standard deviation coefficient, the voltage margin and the temperature margin are calibrated based on the measurement accuracy of the sensor.

[0117] Step 4, taking the weighted sum of the calibrated evaluation index scores of the energy storage unit as the comprehensive evaluation score; and screening the energy storage units allowed to be adjusted according to the monitoring data, and determining the adjustment priority of the energy storage units allowed to be adjusted by using the comprehensive evaluation scores and the charge and discharge cycle numbers of the energy storage units allowed to be adjusted.

[0118] Taking the weighted sum of the calibrated evaluation index scores of the energy storage unit as the comprehensive evaluation score includes:

[0119] The subjective weight of the calibrated evaluation index is calculated by using the quantitative method, the objective weight of the calibrated evaluation index is calculated by using the principal component analysis method, and the subjective weight and the objective weight of the evaluation index are proportionally fused to obtain the weight of the calibrated evaluation index.

[0120] Specifically, the subjective weight of the calibrated evaluation index is calculated by using the quantitative method, which includes:

[0121] 1) Comparing the evaluation indexes two by two, using a 9-level quantitative method, and obtaining a 1-9 numerical grading quantification according to the importance between the two indexes; and constructing a weight evaluation matrix by using the obtained grading quantification, the weight evaluation matrix being a positive reciprocal matrix with diagonal elements being 1.

[0122] 2) Calculating a consistency index to check the consistency of the weight evaluation matrix. Due to many influencing factors, in order to avoid one-sidedness, subjectivity and major logical errors caused by human definition, the consistency of the weight evaluation matrix is checked to ensure its effectiveness. When the consistency index is less than or equal to 0.1, it is determined that the consistency of the weight evaluation matrix meets the requirements, otherwise it is considered that the weight evaluation matrix has logical problems and does not meet the theoretical requirements, and needs to be re-constructed.

[0123] 3), calculate the maximum eigenvalue of the weight evaluation matrix meeting the consistency requirement and the corresponding eigenvector, normalize the eigenvector, and obtain the subjective weight of each evaluation index.

[0124] Specifically, the objective weight of each evaluation index after calibration is calculated by using the principal component analysis method, including:

[0125] 1), normalize each evaluation index to reduce the influence of dimension;

[0126] 2), calculate the standardized covariance matrix to reflect the correlation between each evaluation index;

[0127] 3), perform eigenvalue decomposition on the standardized covariance matrix to obtain a plurality of eigenvalues;

[0128] 4), calculate the contribution rate of each eigenvalue as the objective weight of each evaluation index.

[0129] The present application adopts the combined weighting method to determine the weight of each evaluation index after calibration, and improves the accuracy of the comprehensive evaluation score.

[0130] Based on the set scoring rules, each evaluation index after calibration is scored.

[0131] According to the set scoring rules, each evaluation index is scored to eliminate the influence of dimension.

[0132] Specifically, the set scoring rules include:

[0133] 1), the value of the calibrated SOC is used as the corresponding score, and the value of the calibrated SOH is used as the corresponding score;

[0134] 2), the scoring rules of SOE range, voltage standard deviation coefficient, voltage range and temperature range are shown in Table 1:

[0135] Table 1 Scoring rules

[0136]

[0137] The scoring and corresponding weight of each evaluation index after calibration are used to calculate the comprehensive evaluation score K of the energy storage unit by the following relationship:

[0138]

[0139] In the formula,

[0140] α, β, χ, φ, η, θ are respectively the score R(U r ) of the calibrated voltage range, the score R(U d), the temperature extreme difference score R(T r ), the score of SOC after calibration R(SOC), the score of SOE extreme after calibration R(SOE r ) and the weight coefficient corresponding to the calibrated SOH score R(SOH).

[0141] Since the present invention calibrates various evaluation indicators and improves the accuracy of the indicators, the scores, weights and comprehensive evaluation scores determined based on the calibrated evaluation indicators can accurately evaluate the adjustment priority of each energy storage unit according to the operating status of the energy storage unit.

[0142] The comprehensive evaluation score of the energy storage unit and the number of charge and discharge cycles are used to determine the adjustment priority of each energy storage unit according to the following rules, including:

[0143] 1) Determine whether each energy storage unit is an adjustable energy storage unit based on the monitoring data, and sort the adjustable energy storage units from largest to smallest according to their comprehensive evaluation scores;

[0144] In a non-limiting preferred embodiment, the monitoring data comes from the PCS. All energy storage units that are not allowed to be adjusted are sorted at the end of the sorting result of the energy storage units that are allowed to be adjusted, and the adjustment priority of the energy storage units that are not allowed to be adjusted is zero.

[0145] 2) Based on the ranking results of the energy storage units allowed to be adjusted, among any two energy storage units allowed to be adjusted, the energy storage unit with a larger comprehensive evaluation score that is allowed to be adjusted has a higher adjustment priority, and the energy storage unit with a smaller comprehensive evaluation score that is allowed to be adjusted has a lower adjustment priority;

[0146] 3) Based on the ranking results of the energy storage units allowed to be adjusted, when the jth energy storage unit allowed to be adjusted and the j+1th energy storage unit allowed to be adjusted have the same comprehensive evaluation score, obtain the comprehensive evaluation score of the j-1th energy storage unit allowed to be adjusted and the comprehensive evaluation score of the j+2th energy storage unit allowed to be adjusted, and obtain the number of charge and discharge cycles of the jth energy storage unit allowed to be adjusted and the j+1th energy storage unit allowed to be adjusted; calculate the adjustment priority of the jth energy storage unit allowed to be adjusted and the j+1th energy storage unit allowed to be adjusted respectively according to the following relationship:

[0147]

[0148]

[0149] Where M j and M j+1 are the adjustment priorities of the jth energy storage unit allowed to be adjusted and the j+1th energy storage unit allowed to be adjusted, respectively, K j-1 and K j+2respectively, are the comprehensive evaluation scores of the j-1th and j+2th adjustable energy storage units, C j and C j+1 respectively, are the charge-discharge cycle numbers of the jth and j+1th adjustable energy storage units.

[0150] Therefore, among the multiple adjustable energy storage units with the same comprehensive evaluation score, the adjustable energy storage unit with the fewer charge-discharge cycle numbers has a higher adjustment priority, thereby achieving power balance allocation.

[0151] Step 5, when the scheduling target power is less than the rated power of the adjustable energy storage unit, the adjustable energy storage unit with the highest adjustment priority is selected as the execution unit for responding to the scheduling target power instruction.

[0152] When the scheduling target discharge power is not less than the rated power of the adjustable energy storage unit and less than 90% of the rated power of the energy storage power station, the adjustable energy storage units for responding to the scheduling target discharge power instruction are selected in order of the adjustment priority of each adjustable energy storage unit from high to low as execution units, and the battery management system calculates the state of charge target value of each execution unit according to the state of charge and the state of health of each execution unit output by the verified battery state estimation model; based on the state of charge target value of each execution unit, the scheduling target discharge power is allocated to the execution units that meet the joint constraint condition, and the execution units that cannot meet the joint constraint condition respond to the scheduling target discharge power instruction according to the rated power.

[0153] When the scheduling target charge power is not less than 90% of the rated power of the energy storage power station, all adjustable energy storage units are execution units to respond to the scheduling target power instruction, and the battery management system calculates the state of charge target value of each execution unit according to the state of charge and the state of health of each execution unit output by the verified battery state estimation model; based on the state of charge target value of each execution unit, the scheduling target charge power is allocated to the execution units that meet the joint constraint condition, and the execution units that cannot meet the joint constraint condition respond to the scheduling target discharge power instruction according to the rated power.

[0154] Specifically, step 5 includes:

[0155] Step 5.1, when the scheduling target power is less than the rated power of the adjustable energy storage unit, the adjustable energy storage unit with the highest adjustment priority is selected as the execution energy storage unit for responding to the scheduling target power instruction.

[0156] In the embodiment, the rated power of the energy storage converter constructed in the engineering site is different. Based on the partition control requirement, response time requirement and operation management requirement, the rated power of the energy storage converters in the same region must be the same. Therefore, the rated power of each energy storage unit in each region of the energy storage power station is the same.

[0157] Step 5.2, when the scheduled target discharge power is not less than the rated power of the allowed adjustment energy storage unit and less than 90% of the rated power of the energy storage power station, the allowed adjustment energy storage unit for responding to the scheduled target discharge power instruction is selected as an execution unit in order according to the adjustment priority of each allowed adjustment energy storage unit from high to low, and the battery management system calculates the state of charge target value of each execution unit according to the state of charge and the state of health of each execution unit output by the verified battery state estimation model; the scheduled target discharge power is distributed to the execution unit satisfying the joint constraint condition based on the state of charge target value of each execution unit, and the execution unit unable to satisfy the joint constraint condition responds to the scheduled target discharge power instruction according to the rated power;

[0158] When the scheduled target discharge power is not less than the rated power of the allowed adjustment energy storage unit and less than 90% of the rated power of the energy storage power station, the allowed adjustment energy storage unit for responding to the scheduled target power instruction is selected as an execution unit in order according to the adjustment priority of each allowed adjustment energy storage unit from high to low; the present application distributes the scheduled target discharge power to the selected energy storage unit based on the adjustment priority of the energy storage unit, so that the bidirectional adjustment capability of the energy storage power station is the strongest, and the state of health of the energy storage unit is also considered.

[0159] Specifically, step 5.2 includes:

[0160] Step 5.2.1, the battery management system calculates the state of charge target value of each execution unit according to the state of charge and the state of health of each execution unit output by the verified battery state estimation model, and the relationship is as follows:

[0161]

[0162] In the formula, SOC ref,i,T is the state of charge target value of the i th execution unit at time T; SOC ideal is the calibrated state of charge of the execution unit; SOC i,T and SOH i,T are the state of charge and the state of health of the i th execution unit at time T output by the battery management system based on the verified battery state estimation model; SOC min , SOC max are the lower limit and the upper limit of the state of charge of the energy storage unit; SOH min,T , SOH max,Trespectively, are the lower and upper limits of the SOH of the energy storage unit at time T;

[0163] In the first and third items, when SOC i,T <SOC min or SOC i,T >SOC max Targeting at the recovery SOC, set the SOC reference value of all the executing energy storage units to the ideal SOC value.

[0164] In the second item, when SOC i,T is within the interval [SOC min , SOC max ], perform power distribution based on the SOH of each executing energy storage unit, and deep charge and deep discharge the executing energy storage units with good health status, and shallow charge and shallow discharge the executing energy storage units with poor health status.

[0165] Step 5.2.2, based on the state of charge target value of each executing unit, calculate the ideal discharge power of each executing unit according to the following relationship:

[0166]

[0167] In the formula, P i rated is the rated power of the i-th energy storage unit;

[0168] Step 5.2.3, based on the proportion of the ideal discharge power of each executing unit in the sum of the ideal discharge powers of all the executing units, calculate the discharge power allocated to each executing unit according to the dispatch target discharge power according to the following relationship:

[0169]

[0170] In the formula, P dis,i,T is the discharge power allocated to the i-th executing unit at time T; N is the number of executing units, is the dispatch target discharge power at time T;

[0171] Step 5.2.4, the executing units meeting the joint constraint condition respond to the dispatch target discharge power instruction according to the allocated discharge power; the executing units failing to meet the joint constraint condition respond to the dispatch target discharge power instruction according to the rated power.

[0172] Wherein, the joint constraint condition of each executing unit is as follows:

[0173] SOC constraint condition of the executing unit:

[0174] SOC min <SOCi,T SOC max

[0175] The charge-discharge power constraint condition of the execution unit:

[0176] 0≤P dis,i,T ≤P i rated

[0177] The SOC change constraint condition of the execution unit:

[0178]

[0179] wherein, ΔT is a set time period, is the current capacity of the i-th execution unit.

[0180] The execution units satisfying the joint constraint condition simultaneously perform corresponding operations according to the allocated discharge power to respond to the scheduling target discharge power instruction, and the execution units with power margins send a signal that the first power allocation has been completed and requests the second power allocation to the battery management system, thereby providing conditions for the secondary allocation of the scheduling target discharge power;

[0181] wherein, the power margins of the execution units satisfying the joint constraint condition satisfy the following relationship:

[0182]

[0183] wherein, is the power margin of the s-th execution unit satisfying the joint constraint condition at time T, P dis,s,T is the discharge power allocated to the s-th execution unit satisfying the joint constraint condition at time T, is the rated power of the s-th execution unit satisfying the joint constraint condition.

[0184] The execution units failing to satisfy the joint constraint condition perform corresponding operations according to the rated power to respond to the scheduling target discharge power instruction and calculate the power shortage;

[0185] wherein, the power shortage of the execution units failing to satisfy the joint constraint condition satisfies the following relationship:

[0186]

[0187] wherein, is the power shortage of the m-th execution unit failing to satisfy the joint constraint condition at time T, P dis,m,T is the discharge power allocated to the m-th execution unit failing to satisfy the joint constraint condition at time T, is the rated power of the m-th execution unit failing to satisfy the joint constraint condition.

[0188] The power shortage is allocated to the execution units with power margin to implement the second power allocation, satisfying the following relationship:

[0189]

[0190] In the formula, P d ′ is,s,T is the updated discharge power of the s-th execution unit satisfying the joint constraint condition at time T, S is the number of execution units satisfying the joint constraint condition, and M is the number of execution units that cannot satisfy the joint constraint condition.

[0191] The power shortage and the power margin are both determined based on the rated power of the energy storage units. When the rated powers of the energy storage units are equivalent, the dispatch target power can be evenly allocated to the energy storage units after being preferentially allocated to the energy storage units with high adjustment priority.

[0192] Step 5.3, when the dispatch target charging power is not less than 90% of the rated power of the energy storage power station, all the allowed adjustment energy storage units are execution units to respond to the dispatch target power instruction, the battery management system calculates the state of charge target value of each execution unit according to the state of charge and the state of health of each execution unit output by the verified battery state estimation model; based on the state of charge target value of each execution unit, the dispatch target charging power is allocated to the execution units satisfying the joint constraint condition, and the execution units that cannot satisfy the joint constraint condition respond to the dispatch target discharge power instruction according to the rated power;

[0193] Specifically, step 5.3 includes:

[0194] Step 5.3.1, the battery management system calculates the state of charge target value of each execution unit according to the state of charge and the state of health of each execution unit output by the verified battery state estimation model, and the relationship is as follows:

[0195]

[0196] In the formula, SOC ref,i,T is the state of charge target value of the i-th execution unit at time T; SOC ideal is the calibrated state of charge of the execution unit; SOC i,T and SOH i,T are the state of charge and the state of health of the i-th execution unit at time T output by the battery management system based on the verified battery state estimation model; SOC min , SOC max are the lower limit and the upper limit of the state of charge of the energy storage unit; SOH min,T , SOH max,Trespectively are the lower limit and upper limit of the state of health of the energy storage unit at time T;

[0197] Step 5.3.2, based on the state of charge target value of each execution unit, the ideal discharge power of each execution unit is calculated according to the following relationship:

[0198]

[0199] In the formula, is the ideal charging power of the i th execution unit at time T; P i rated is the rated power of the i th energy storage unit;

[0200] Step 5.3.3, based on the proportion of the ideal charging power of each execution unit in the sum of the ideal charging power of all execution units, the charging power allocated to each execution unit is calculated according to the dispatch target charging power according to the following relationship:

[0201]

[0202] In the formula, P ch,i,T is the charging power allocated to the i th execution unit at time T; N is the number of execution units; is the dispatch target charging power at time T; is the ideal charging power of the i th execution unit at time T.

[0203] The execution unit meeting the joint constraint condition responds to the dispatch target charging power instruction according to the allocated charging power; the execution unit unable to meet the joint constraint condition responds to the dispatch target charging power instruction according to the rated power;

[0204] Wherein, the joint constraint condition of each execution unit is as follows:

[0205] The SOC constraint condition of the execution unit:

[0206] SOC min <SOC i,T <SOC max

[0207] The charging power constraint condition of the execution unit:

[0208] 0≤P ch,i,T ≤P i rated

[0209] The SOC change constraint condition of the execution unit during charging:

[0210]

[0211] In the formula, ΔT is a set time period, Qi present The current capacity of the ith execution unit.

[0212] The execution units satisfying the joint constraint condition perform corresponding operations according to the allocated charging power to respond to the scheduling target charging power instruction, and the execution units with power margins send a signal to the battery management system that the first power allocation has been completed and request the second power allocation, thereby providing conditions for the secondary allocation of the scheduling target charging power;

[0213] Wherein the power margins of the execution units satisfying the joint constraint condition satisfy the following relationship:

[0214]

[0215] In the formula, P is the power margin of the st execution unit satisfying the joint constraint condition at time T, P dis,s,T P is the discharge power allocated to the st execution unit satisfying the joint constraint condition at time T, P is the rated power of the st execution unit satisfying the joint constraint condition.

[0216] The execution units that cannot satisfy the joint constraint condition perform corresponding operations according to the rated power to respond to the scheduling target discharge power instruction and calculate the power shortage;

[0217] Wherein the power shortage of the execution units that cannot satisfy the joint constraint condition satisfies the following relationship:

[0218]

[0219] In the formula, P is the power shortage of the mth execution unit that cannot satisfy the joint constraint condition at time T, P dis,m,T P is the discharge power allocated to the mth execution unit that cannot satisfy the joint constraint condition at time T, P is the rated power of the mth execution unit that cannot satisfy the joint constraint condition.

[0220] The power shortage is allocated to the execution units with power margins to realize the secondary power allocation, which satisfies the following relationship:

[0221]

[0222] In the formula, P d ′ is,s,T P is the updated value of the discharge power of the st execution unit satisfying the joint constraint condition at time T, S is the number of execution units satisfying the joint constraint condition, and M is the number of execution units that cannot satisfy the joint constraint condition.

[0223] Consider a specific energy storage power station with a total installed capacity of 25MW / 50MWh. The power station consists of 16 energy storage units (two collector lines, each with 8 units), each rated at 1.725MW. The basic parameters of each unit are shown in Table 1:

[0224] Table 1 Basic parameters of energy storage unit

[0225]

[0226] The initial SOC values ​​of the eight energy storage units under the two collector lines are different, ranging from 0.20 to 0.80, while the initial SOH values ​​are distributed from 0.8 to 1.0.

[0227] Six key indicators are calculated based on the collected BMS monitoring data. The calculation formula for SOE range is as follows:

[0228] SOE r =SOE max -SOE min

[0229] Where, SOE r SOE is extremely poor; SOE max It is the maximum value of the SOE data sent to the server; SOE min It is the minimum value in the SOE data sent to the server. Voltage standard deviation coefficient U d and voltage difference U r Satisfies the following relationship:

[0230]

[0231] U r =U max -U min

[0232] Where U i is the voltage of the i-th energy storage unit; n is the total number of energy storage units; is the average value of the energy storage unit voltage; U max is the maximum value of the energy storage unit voltage; U min It is the minimum value of the energy storage unit voltage.

[0233] Temperature extremes T r Satisfies the following relationship:

[0234] T r =T max -T min

[0235] Where, T max is the maximum temperature of the energy storage unit, T minis the minimum value of the energy storage unit temperature.

[0236] And according to the set score rules, the six indicators are scored respectively to eliminate the influence of dimension. Since the score values of SOC and SOH are the same as their numerical values, SOC and SOH can be further calibrated in real time. Based on the second-order RC circuit model of the battery, the state equation with SOC as the state variable and the observation equation with voltage as the observation variable are constructed, and the SOC calibration system model is as follows:

[0237]

[0238] In the formula, U 1,k and U 2,k are the equivalent circuit voltages of the first resistor R1 and the second resistor R2 in the second-order RC circuit at the kth calibration; T is the transient time of the circuit; τ1 and τ2 are both time constants; η is the coulomb efficiency coefficient; Q rated is the rated capacity of the battery; I k is the current of the second-order RC circuit at the kth calibration; U k is the terminal voltage of the second-order RC circuit at the kth calibration; w k and v k are the system noise and observation noise at the kth calibration; U oc (SOC k ) is the open circuit voltage corresponding to SOC at the kth calibration; R0 is the internal resistance of the second-order RC circuit.

[0239] Similarly, based on the second-order RC circuit model of the battery, the battery capacity is taken as the state variable, and the SOC estimation error is taken as the observation variable, then the capacity calibration system model is as follows:

[0240]

[0241] In the formula, is the current actual capacity of the battery at the kth calibration, r 2,k and ε 2,k are the state noise and observation noise of the system at the kth calibration, d k is the SOC estimation error at the kth calibration,

[0242] The calibration value of SOH is:

[0243]

[0244] Based on the central error entropy criterion Kalman filter (CEEKF), the SOC calibration and capacity calibration system model are updated respectively, and the SOC and SOH are calibrated. The model voltage of the energy storage unit battery cluster calculated by the central error entropy criterion Kalman filter is compared with the voltage sent by the BMS as follows:Figure 2 The steps are as follows:

[0245] 1) Initialization: Given the initial state estimate and the initial covariance matrix PP0, set the termination iteration error e and the maximum number of iterations;

[0246] 2) According to the state equation, predict the next time state estimate and state covariance matrix, that is

[0247]

[0248]

[0249] In the formula, F is the state transition matrix, G is the control matrix, u is the control input, and QQ is the process noise covariance matrix;

[0250] 3) According to the observation equation and CEE cost function, use Newton-Raphson method to solve the optimal posterior state estimate, that is

[0251]

[0252] In the formula, y is the observation value. Repeat this step until or the maximum number of iterations is reached;

[0253] 4) Calculate the posterior covariance matrix, which is shown as follows:

[0254]

[0255] The application proposes to calibrate SOC and SOH by using central entropy Kalman filtering method. As an optimal state estimation method based on probability theory, central error entropy Kalman filtering has the advantages of accuracy, optimality, recursion, self-adaptation and strong expansibility, and is very suitable for state estimation problems of dynamic systems. Therefore, the estimation accuracy of the two core indicators is effectively improved, so that more accurate evaluation of the operating state of the energy storage unit is realized.

[0256] Then, a 9-level quantitative method is used to construct a weight evaluation matrix, and the quantitative criteria are shown in Table 2:

[0257] Table 2 Weight evaluation matrix

[0258] Importance Importance comparison 1 Same importance between two factors 3 Slightly more important of two factors 5 More important of two factors 7 Much more important of two factors 9 Extremely more important of two factors 2,4,6,8 Intermediate value between 1 and 9

[0259] Then calculate the consistency index CR to check the consistency of the weight evaluation matrix, and the formula is as follows:

[0260]

[0261] In the formula, lmax is the maximum eigenvalue of the weight evaluation matrix, and the CR of the weight evaluation matrix is calculated as 0.079, meeting the consistency requirement. Then, λ max The corresponding eigenvector is normalized to obtain six weight distribution coefficients, as shown in Table 3:

[0262] Table 3 Weight distribution coefficients

[0263] Weight coefficient a b c f h q Numerical value 0.06125 0.02572 0.00875 0.46560 0.12828 0.31040

[0264] By constructing the weight evaluation matrix and calculating the consistency index, the rationality and accuracy of the weight coefficient can be ensured, and the evaluation result is more reliable.

[0265] In the charging working condition, the relationship between the comprehensive evaluation score K and the key indicators is shown in the following formula:

[0266] K = 0.06125R(U r ) + 0.02572R(U d ) + 0.00875R(T r ) - 0.46560R(SOC)

[0267] + 0.12828R(SOE r ) + 0.31040R(SOH)

[0268] In the discharging working condition, the relationship between the comprehensive evaluation score K and the key indicators is shown in the following formula.

[0269] K = 0.06125R(U r ) + 0.02572R(U d ) + 0.00875R(T r ) + 0.46560R(SOC)

[0270] + 0.12828R(SOE r ) + 0.31040R(SOH)

[0271] The energy storage units are sorted according to the comprehensive score K from large to small, and then combined with the monitoring information of the PCS, it can be judged which energy storage units can be adjusted and which cannot be adjusted. The K of the energy storage units that cannot be adjusted is set to zero. If the K of multiple energy storage units is the same, the priority of the energy storage unit with fewer charging and discharging times is higher. In a certain iteration, the K of two energy storage units is equal, numbered 2 and 3 respectively. The adjacent energy storage unit with larger K is numbered 1, and the adjacent energy storage unit with smaller K is numbered 4. The calculation formula of the adjustment priority M is as follows:

[0272]

[0273] In the formula, C is the number of charge and discharge cycles. The adjustment priority calculation results of the four energy storage units are shown in Table 4:

[0274] Table 4 Adjustment priority calculation results

[0275]

[0276] The present application considers the PCS monitoring data and the number of charge and discharge, thereby dynamically determining the adjustment priority of each energy storage unit, and avoiding unreasonable adjustment caused by fixed priority.

[0277] At a certain time T, the power allocation is performed by applying the power control strategy proposed in the present application and the commonly used strategy respectively, and the overall cumulative output of the energy storage power station is compared as shown in the following figure: Figure 3 When the power control strategy proposed in the present application is adopted, in the power adjustment process:

[0278] When the power instruction is less than 1.735 MW, only the energy storage unit with the highest adjustment priority outputs, which reduces the charge and discharge frequency and is beneficial to delay the battery life attenuation;

[0279] When the power instruction is greater than or equal to 1.735 MW but less than 22.5 MW, part of the energy storage units are selected to act, and the power is allocated according to the dynamic proportional allocation strategy. The SOC consistency of each unit is good and can be adjusted to tend to the ideal value, the bidirectional adjustment ability is strong, and the charge and discharge depth is controlled in combination with SOH, which is beneficial to delay the battery life attenuation;

[0280] When the power instruction is greater than 22.5 MW, all the energy storage units act, and the power is allocated according to the SOC feedback control strategy, so that the energy storage power station output deviation is small, the continuous working time is long, and the overall adjustment ability is strong.

[0281] According to different target power instructions, the present application adopts different adjustment strategies, realizes dynamic division of the adjustment execution domain, ensures the completion of the target, and avoids the influence of excessive adjustment on the battery life. The present application proposes to perform dynamic power allocation according to the real-time state of each energy storage unit, avoids the imbalance of adjustment caused by fixed proportional allocation, and further improves the adjustment effect. Through accurate evaluation, dynamic adjustment priority and dynamic power allocation, the present application realizes the optimal scheduling of the power of the energy storage power station, and improves the adjustment ability and economy of the system.

[0282] The present application also proposes a power control system based on the adjustment priority evaluation of the energy storage unit, which comprises:

[0283] The evaluation index establishing module is used to obtain the characteristic data of the operating state of the energy storage unit to establish the evaluation index of the state of the energy storage unit, including the state of charge, the state of health, the energy state range, the voltage standard deviation coefficient, the voltage range and the temperature range.

[0284] The energy storage unit calibration module is configured to calibrate the state of charge, the battery capacity, and the state of health of the energy storage unit by the energy storage unit; feed back the calibrated state of charge and the state of health of the energy storage unit to the battery management system; verify the built-in battery state estimation model of the battery management system by using the calibrated state of charge and the state of health, to obtain a verified battery state estimation model; and calibrate the energy state range based on the calibrated state of charge and the battery capacity; and calibrate the voltage standard deviation coefficient, the voltage range, and the temperature range based on the measurement accuracy of the sensor.

[0285] The adjustment priority calculation module is configured to take the weighted sum of the evaluation index scores of the energy storage unit as a comprehensive evaluation score; select the energy storage units allowed to be adjusted according to the monitoring data; and determine the adjustment priority of the energy storage units allowed to be adjusted by using the comprehensive evaluation scores of the energy storage units allowed to be adjusted and the number of charge and discharge cycles of the energy storage units allowed to be adjusted.

[0286] The scheduling target power instruction response module is configured to select the energy storage unit allowed to be adjusted with the highest adjustment priority as an execution unit for responding to the scheduling target power instruction when the scheduling target power is less than the rated power of the energy storage unit allowed to be adjusted.

[0287] When the scheduling target discharge power is not less than the rated power of the energy storage unit allowed to be adjusted and is less than 90% of the rated power of the energy storage power station, the energy storage units allowed to be adjusted are selected in turn as execution units for responding to the scheduling target discharge power instruction in the order from high to low of the adjustment priority of the energy storage units allowed to be adjusted; the battery management system calculates the state of charge target value of each execution unit according to the state of charge and the state of health of each execution unit output by the verified battery state estimation model; and the scheduling target discharge power is distributed to the execution units satisfying the joint constraint condition based on the state of charge target value of each execution unit, and the execution units failing to satisfy the joint constraint condition respond to the scheduling target discharge power instruction according to the rated power.

[0288] When the scheduling target charge power is not less than 90% of the rated power of the energy storage power station, all the energy storage units allowed to be adjusted are execution units for responding to the scheduling target power instruction; the battery management system calculates the state of charge target value of each execution unit according to the state of charge and the state of health of each execution unit output by the verified battery state estimation model; and the scheduling target charge power is distributed to the execution units satisfying the joint constraint condition based on the state of charge target value of each execution unit, and the execution units failing to satisfy the joint constraint condition respond to the scheduling target discharge power instruction according to the rated power.

[0289] The application is realized in the form of a computer program, is easy to operate, easy to expand, reduces the manual operation strength, and improves the system automation level. The method and system have good universality, can be applied to different types and scales of energy storage power stations, and have high popularization and application value. The application has significant advantages in improving the operation safety of the energy storage power station, prolonging the battery life, and improving the system regulation performance.

[0290] The present disclosure can be a system, a method, and / or a computer program product. The computer program product can include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present disclosure.

[0291] The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium can be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium include the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or punched tape, a magneto-optical storage device, or any suitable combination of the foregoing. A computer readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire.

[0292] Computer readable program instructions described herein can be downloaded to respective computing / processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and / or a wireless network. The network can comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and / or edge servers. A network adapter card or network interface in each computing / processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing / processing device.

[0293] Computer readable program instructions for carrying out operations of the present disclosure can be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state setting data, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++ or the like, and conventional procedural programming languages such as the "C" programming language or similar programming languages. The computer readable program instructions can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) can execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present disclosure.

[0294] Finally, it should be noted that the above-mentioned embodiments are merely used to illustrate the technical solutions of the present application, but not to limit it. Although the present application has been described in detail with reference to the above-mentioned embodiments, those skilled in the art should understand that the specific embodiments of the present application can be modified or replaced, and any modification or replacement without departing from the spirit and scope of the present application should be covered in the protection scope of the claims of the present application.

Claims

1. A power control method based on energy storage unit adjustment priority evaluation, characterized in that: include: Acquire characteristic data of the energy storage unit's operating status to establish evaluation indicators for the energy storage unit's status, including: state of charge, health status, energy state extremes, voltage standard deviation coefficient, voltage extremes, and temperature extremes; The energy storage unit calibrates its own state of charge, battery capacity, and state of health. The calibrated state of charge and state of health of the energy storage unit are fed back to the battery management system. The battery management system uses the calibrated state of charge and state of health to verify the battery state estimation model built into the battery management system, thereby obtaining a verified battery state estimation model. Based on the calibrated state of charge and battery capacity, the energy state range is calibrated; based on the measurement accuracy of the sensor, the voltage standard deviation coefficient, voltage range and temperature range are calibrated; The weighted sum of the scores of the various evaluation indicators of the energy storage unit after calibration is used as the comprehensive evaluation score; the energy storage units that are allowed to be adjusted are screened out based on the monitoring data, and the adjustment priority of the energy storage units that are allowed to be adjusted is determined using the comprehensive evaluation scores and the number of charge and discharge cycles of the energy storage units that are allowed to be adjusted; When the dispatch target power is less than the rated power of the energy storage unit allowed to be adjusted, the energy storage unit allowed to be adjusted with the highest adjustment priority is selected as the execution unit to respond to the dispatch target power instruction; When the dispatch target discharge power is not less than the rated power of the adjustable energy storage unit and less than 90% of the rated power of the energy storage station, the adjustable energy storage unit that is used to respond to the dispatch target discharge power instruction is selected in descending order of the adjustment priority of each adjustable energy storage unit. The battery management system calculates the state of charge target value of each execution unit based on the state of charge and health status of each execution unit output by the verified battery state estimation model. Based on the state of charge target value of each execution unit, the dispatch target discharge power is allocated to the execution unit that meets the joint constraint conditions. The execution unit that cannot meet the joint constraint conditions responds to the dispatch target discharge power instruction according to the rated power. When the dispatch target charging power is no less than 90% of the rated power of the energy storage station, all energy storage units that are allowed to be adjusted are execution units that respond to the dispatch target power instruction. The battery management system calculates the state of charge target value of each execution unit based on the charge state and health state of each execution unit output by the verified battery state estimation model; based on the state of charge target value of each execution unit, the dispatch target charging power is allocated to the execution units that meet the joint constraint conditions. The execution units that cannot meet the joint constraint conditions respond to the dispatch target discharge power instruction according to the rated power.

2. The power control method based on energy storage unit adjustment priority evaluation according to claim 1, characterized in that: Obtain characteristic data of the energy storage unit's operating status and use the characteristic data to construct evaluation indicators of the energy storage unit's status, including: Collect monitoring data from the battery management system and energy storage converter, and extract characteristic data related to the operating status of the energy storage unit from the monitoring data sent by the battery management system; The evaluation indicators of the energy storage unit status are screened out from the characteristic data, including: state of charge, health state, energy state extreme difference, voltage standard deviation coefficient, voltage extreme difference and temperature extreme difference.

3. The power control method based on energy storage unit adjustment priority evaluation according to claim 1, characterized in that: Each energy storage unit uses a Kalman filter method based on the central error entropy criterion. Based on the equivalent circuit of the battery, the energy storage unit calibrates its own state of charge, battery capacity, and health status, including: Based on a second-order RC circuit of the battery, the state of charge is used as the state variable and the battery voltage is used as the observation variable. The Kalman filter method based on the central error entropy criterion is used to calibrate the state of charge. The difference between the calibrated state of charge and the state of charge estimated by the battery management system is used as the state of charge estimation error. Based on the battery's second-order RC circuit, the battery capacity is used as the state variable and the state of charge estimation error is used as the observation variable. The battery capacity is calibrated using the Kalman filter method based on the central error entropy criterion, and the health state is calibrated based on the calibrated battery capacity. The calibrated state of charge, battery capacity and health status are fed back to the battery management system of the energy storage unit.

4. The power control method based on energy storage unit adjustment priority evaluation according to claim 3 is characterized in that: The calibrated state of charge and health status of the energy storage unit are fed back to the battery management system. The battery management system uses the calibrated state of charge and health status to verify the battery state estimation model built into the battery management system. The verified battery state estimation model is obtained, including: Feedback the calibrated state of charge and health status of the energy storage unit to the battery management system, which integrates the collected energy storage unit data with the calibrated state of charge and health status to form a battery status data set; The battery management system uses the battery status data set to verify the battery status estimation model built into the battery management system. When the error between the state of charge and health status output by the battery status estimation model and the state of charge and health status after calibration of the energy storage unit is not greater than the set limit, the battery status estimation model at this time is used as the verified battery status estimation model; when the error between the state of charge and health status output by the battery status estimation model and the state of charge and health status after calibration is greater than the set limit, the battery management system sends a signal to the corresponding energy storage unit to recalibrate the state of charge and health status.

5. The power control method based on energy storage unit adjustment priority evaluation according to claim 1, characterized in that: The weighted sum of the calibrated evaluation index scores of the energy storage unit is used as the comprehensive evaluation score, including: The subjective weights of the calibrated evaluation indicators are calculated using a quantitative method, and the objective weights of the calibrated evaluation indicators are calculated using a principal component analysis method. The subjective weights and objective weights of the evaluation indicators are proportionally integrated to obtain the weights of the calibrated evaluation indicators. Based on the set scoring rules, each calibrated evaluation indicator is scored separately. Using the calibrated scores and weights of each evaluation indicator, the comprehensive evaluation score of the energy storage unit is calculated using the following relationship: : Where, 、 、 、 、 、 The voltage range after calibration is Rating , voltage standard deviation after calibration Rating , Temperature range after calibration Rating , state of charge after calibration Rating , the energy state after calibration is extremely poor Rating and calibrated health status Rating The corresponding weight coefficient.

6. The power control method based on energy storage unit adjustment priority evaluation according to claim 1, characterized in that: The energy storage units that are allowed to be adjusted are screened out based on the monitoring data. The adjustment priority of the energy storage units that are allowed to be adjusted is determined using the comprehensive evaluation scores and the number of charge and discharge cycles of the energy storage units that are allowed to be adjusted, including: Determine whether each energy storage unit is an adjustable energy storage unit based on the monitoring data, and sort the adjustable energy storage units from highest to lowest according to their comprehensive evaluation scores; place all non-adjustable energy storage units at the end of the sorted list of adjustable energy storage units, and assign an adjustment priority of zero to all non-adjustable energy storage units; Based on the ranking results of the energy storage units allowed to be adjusted, among any two energy storage units allowed to be adjusted, the energy storage unit with a larger comprehensive evaluation score has a higher adjustment priority, and the energy storage unit with a smaller comprehensive evaluation score has a lower adjustment priority; Based on the results of the allowed adjustment of the energy storage unit ranking, The first allows the adjustment of the energy storage unit and the When the allowed adjustable energy storage units have the same comprehensive evaluation score, obtain the The comprehensive evaluation score of the energy storage unit is allowed to be adjusted and the The comprehensive evaluation score of the energy storage unit is allowed to be adjusted, and the The first allows the adjustment of the energy storage unit and the The number of charge and discharge cycles of the energy storage unit is allowed to be adjusted; the following relationship is used to calculate the The first allows the adjustment of the energy storage unit and the The adjustment priority of the energy storage unit is allowed to be adjusted: Where, and Respectively The first allows the adjustment of the energy storage unit and the The adjustment priority of the energy storage unit is allowed to be adjusted. and Respectively The first allows the adjustment of the energy storage unit and the The comprehensive evaluation score of the energy storage unit is allowed to be adjusted. and Respectively The first allows the adjustment of the energy storage unit and the A device that allows the adjustment of the number of charge and discharge cycles of the energy storage unit; For multiple adjustable energy storage units with the same comprehensive evaluation score, the adjustable energy storage unit with fewer charge and discharge cycles has a higher corresponding adjustment priority.

7. The power control method based on energy storage unit adjustment priority evaluation according to claim 1, characterized in that: The battery management system calculates the target state of charge of each execution unit based on the state of charge and health status of each execution unit output by the verified battery state estimation model using the following relationship: Where, For the moment No. The target state of charge of each execution unit; The state of charge of the execution unit after calibration; and are the times when the battery management system outputs the verified battery state estimation model No. The state of charge and health of each execution unit; 、 They are the lower limit and upper limit of the state of charge of the energy storage unit respectively; 、 Separate moments The lower and upper limits of the health status of the energy storage unit; Based on the target state of charge of each execution unit, the ideal discharge power of each execution unit is calculated using the following relationship: Where, For the moment No. The ideal discharge power of each execution unit; For the Rated power of each energy storage unit; Based on the target state of charge of each execution unit, the ideal charging power of each execution unit is calculated using the following relationship: Where, For the moment No. The ideal charging power of each execution unit.

8. The power control method based on energy storage unit adjustment priority evaluation according to claim 7, characterized in that: Based on the proportion of the ideal discharge power of each execution unit in the sum of the ideal discharge powers of all execution units and the scheduling target discharge power, the discharge power allocated to each execution unit is calculated using the following relationship: Where, For the moment No. The discharge power obtained by allocating the execution units; is the number of execution units, For the moment The dispatch target discharge power; Based on the proportion of the ideal charging power of each execution unit in the sum of the ideal charging powers of all execution units and the scheduling target charging power, the charging power allocated to each execution unit is calculated using the following relationship: Where, For the moment No. The charging power allocated to each execution unit; is the number of execution units; For the moment The dispatch target charging power; For the moment No. The ideal charging power of each execution unit.

9. The power control method based on energy storage unit adjustment priority evaluation according to claim 8, characterized in that: The execution units that meet the joint constraint conditions respond to the scheduling target discharge power instruction according to the allocated discharge power; the execution units that cannot meet the joint constraint conditions respond to the scheduling target discharge power instruction according to the rated power; Among them, the joint constraints of each execution unit are as follows: SOC constraints of the execution unit: Discharge power constraints of the execution unit: Constraints on the SOC change during discharge of the execution unit: Where, For the set time period, For the The current capacity of each execution unit; The execution units that meet the joint constraint conditions respond to the scheduling target charging power instruction according to the allocated charging power; the execution units that cannot meet the joint constraint conditions respond to the scheduling target charging power instruction according to the rated power; Among them, the joint constraints of each execution unit are as follows: SOC constraints of the execution unit: The charging power constraints of the execution unit are: Constraints on the SOC change during charging of the execution unit: Where, For the set time period, For the The current capacity of the execution unit.

10. A power control system based on energy storage unit regulation priority evaluation, characterized in that: include: An evaluation index establishment module is used to obtain characteristic data of the energy storage unit's operating status to establish evaluation indicators for the energy storage unit's status, including: state of charge, health state, energy state extreme difference, voltage standard deviation coefficient, voltage extreme difference, and temperature extreme difference; The energy storage unit calibration module is used to calibrate the energy storage unit's state of charge, battery capacity, and state of health. The calibrated state of charge and state of health of the energy storage unit are fed back to the battery management system, which uses the calibrated state of charge and state of health to verify the battery state estimation model built into the battery management system to obtain a verified battery state estimation model. The module is also used to calibrate the energy state range based on the calibrated state of charge and battery capacity. Based on the measurement accuracy of the sensor, the voltage standard deviation coefficient, voltage range, and temperature range are calibrated. An adjustment priority calculation module is configured to use the weighted sum of the scores of the various evaluation indicators of the energy storage unit after calibration as a comprehensive evaluation score; screen out energy storage units that are allowed to be adjusted based on the monitoring data; and determine the adjustment priority of the energy storage units that are allowed to be adjusted using the comprehensive evaluation scores and the number of charge and discharge cycles of the energy storage units that are allowed to be adjusted; A dispatch target power instruction response module is used to select the energy storage unit with the highest adjustment priority as the execution unit to respond to the dispatch target power instruction when the dispatch target power is less than the rated power of the energy storage unit allowed to be adjusted; When the dispatch target discharge power is not less than the rated power of the adjustable energy storage unit and less than 90% of the rated power of the energy storage station, the adjustable energy storage unit that is used to respond to the dispatch target discharge power instruction is selected in descending order of the adjustment priority of each adjustable energy storage unit. The battery management system calculates the state of charge target value of each execution unit based on the state of charge and health status of each execution unit output by the verified battery state estimation model. Based on the state of charge target value of each execution unit, the dispatch target discharge power is allocated to the execution unit that meets the joint constraint conditions. The execution unit that cannot meet the joint constraint conditions responds to the dispatch target discharge power instruction according to the rated power. When the dispatch target charging power is no less than 90% of the rated power of the energy storage station, all energy storage units that are allowed to be adjusted are execution units that respond to the dispatch target power instruction. The battery management system calculates the state of charge target value of each execution unit based on the charge state and health state of each execution unit output by the verified battery state estimation model; based on the state of charge target value of each execution unit, the dispatch target charging power is allocated to the execution units that meet the joint constraint conditions. The execution units that cannot meet the joint constraint conditions respond to the dispatch target discharge power instruction according to the rated power.

Images