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

Abstract

According to the power control method and system based on energy storage unit adjustment priority evaluation, an energy storage unit calibrates the charge state, the battery capacity and the health state of the energy storage unit and feeds back the charge state, the battery capacity and the health state to a battery management system; the battery management system verifies a built-in battery state estimation model of the battery management system by using the calibrated charge state and health state; based on the calibrated charge state and the battery capacity, calibrating the energy state range; calibrating the voltage standard deviation coefficient, the voltage range and the temperature range based on the measurement precision of the sensor; taking the weighted sum of each evaluation index score after calibration of the energy storage unit as a comprehensive evaluation score; determining the adjustment priority of the energy storage unit allowed to be adjusted by using the comprehensive evaluation score and the charge-discharge cycle times of the energy storage unit allowed to be adjusted; and selecting the adjustment-allowed energy storage unit with the highest adjustment priority as an execution unit for responding to the scheduling target power instruction, and ensuring the safe and stable operation of the energy storage system at the same time.

Description

Technical Field

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

[0002] Energy storage power stations are an important technical means to maintain the safe operation of power grids. By storing energy and releasing it when needed, energy storage power stations can effectively balance the load fluctuations of the power grid and reduce the operational instability caused by the connection of new energy to the grid. In addition, energy storage power stations can also provide auxiliary services such as peak load regulation, frequency regulation, standby, and black start for the power grid, improving the overall performance and reliability of the power grid. The safe and stable operation of the energy storage system is the basic condition for its function. The unstable operation of the energy storage system may cause power system failures and even grid accidents, causing adverse effects on the economy and society. Therefore, improving the safety of energy storage power stations is an urgent problem to be solved.

[0003] In the prior art, when the energy storage power station participates in regulation, the power instructions for each energy storage unit are not allocated 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 state is affected by many factors, and a comprehensive evaluation must be completed in combination with multiple factors. In addition, SOC and SOH are core indicators for unit state evaluation, and the accuracy of the estimated values ​​must be improved to ensure accurate evaluation of the state. 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 a scheduling instruction, if a simple full output and fixed coefficient allocation strategy is adopted, the maintenance effect on battery life and performance is insufficient, affecting the safe operation of the energy storage system. Summary of the invention

[0004] In order to solve 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 realizes the optimization of power instruction allocation effect based on the energy storage unit regulation priority. Firstly, 6 key indicators are screened out to construct a comprehensive evaluation model of the energy storage unit state, and the estimation accuracy of the core indicators is improved to achieve accurate evaluation of the state; 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 solution.

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

[0007] Acquire characteristic data of the energy storage unit operation status to establish evaluation indicators of the energy storage unit status, including: state of charge, health state, energy state extreme difference, voltage standard deviation coefficient, voltage extreme difference and temperature extreme difference;

[0008] The energy storage unit calibrates its own 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 uses the calibrated state of charge and health status to verify the battery state estimation model built into the battery management system to obtain a verified battery state estimation model;

[0009] 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;

[0010] 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 according to the monitoring data, and the adjustment priority of the energy storage units that are allowed to be adjusted is determined by using the comprehensive evaluation scores and the number of charge and discharge cycles of the energy storage units that are allowed to be adjusted;

[0011] When the dispatch 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 dispatch target power instruction;

[0012] 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 turn as the execution unit according to the adjustment priority of each adjustable energy storage unit from high to low. The battery management system calculates the charge state target value of each execution unit according to the charge state and health state of each execution unit output by the verified battery state estimation model; based on the charge state target value of each execution unit, the dispatch target discharge power is allocated to the execution unit that meets the joint constraint condition, and the execution unit that cannot meet the joint constraint condition responds to the dispatch target discharge power instruction according to the rated power;

[0013] When the dispatch target charging power is not 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 to respond to the dispatch target power instructions. 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 constraints, and the execution units that cannot meet the joint constraints respond to the dispatch target discharge power instructions according to the rated power.

[0014] Preferably, acquiring characteristic data of the operating state of the energy storage unit and constructing an evaluation index of the state of the energy storage unit using the characteristic data include:

[0015] 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;

[0016] The evaluation indicators of the energy storage unit status are selected 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.

[0017] Preferably, each energy storage unit adopts a Kalman filter method based on the central error entropy criterion, and based on the equivalent circuit of the battery, the energy storage unit calibrates its own state of charge, battery capacity and health status, including:

[0018] Based on the 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.

[0019] Based on the second-order RC circuit of the battery, 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.

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

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

[0022] 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;

[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 state output by the battery status estimation model and the state of charge and health state 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 state output by the battery status estimation model and the state of charge and health state 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 state.

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

[0025] The subjective weights of the calibrated evaluation indicators are calculated by quantitative method, and the objective weights of the calibrated evaluation indicators are calculated by principal component analysis. 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, the calibrated evaluation indicators are scored respectively.

[0026] Using the scores and weights of the calibrated evaluation indicators, 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 extreme difference U after calibration. r Rating R(U r ), the voltage standard deviation after calibration U d Rating R(U d ), the temperature difference after calibration T r Rating R(T r ), the score R(SOC) of the calibrated state of charge SOC, 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 according to the monitoring data, and the adjustment priority of the energy storage units that are allowed to be adjusted is determined by 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] 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 large to small according to the comprehensive evaluation score; put all the non-adjustable energy storage units at the end of the sorting result of the adjustable energy storage units, and the adjustment priority of the non-adjustable energy storage units is zero;

[0031] 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 allowed to be adjusted with a larger comprehensive evaluation score has a higher adjustment priority, and the energy storage unit allowed to be adjusted with a smaller comprehensive evaluation score has a lower adjustment priority;

[0032] 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, 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 are obtained, and 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 are obtained; the adjustment priorities of the jth energy storage unit allowed to be adjusted and the j+1th energy storage unit allowed to be adjusted are calculated respectively according to the following relationship:

[0033]

[0034] Where M j and M j+1 are the adjustment priorities of the jth energy storage unit that is allowed to be adjusted and the j+1th energy storage unit that is allowed to be adjusted, respectively, K j-1 and K j+2 are the comprehensive evaluation scores of the j-1th allowed adjustable energy storage unit and the j+2th allowed adjustable energy storage unit, respectively. j and C j+1 are the number of charge and discharge cycles of the jth allowable adjustable energy storage unit and the j+1th allowable adjustable energy storage unit respectively;

[0035] 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.

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

[0037]

[0038] In the formula, SOC ref,i,T is the target state of charge value of the i-th execution unit at time T; SOC ideal SOC is the state of charge after the execution unit is calibrated; i,T and SOHi,T are the state of charge and health state 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 and upper limits of the state of charge of the energy storage unit; SOH min,T , SOH max,T They 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] In the formula, 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] In the formula, 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, according to the scheduling target discharge power, the discharge power allocated to each execution unit is calculated according to 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 according to 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; is the scheduling target charging power at time T; is the ideal charging power of the i-th execution unit at time T.

[0051] Preferably, the execution units that meet the joint constraint conditions respond to the dispatch target discharge power instruction according to the allocated discharge power; the execution units that cannot meet the joint constraint conditions respond to the dispatch target discharge power instruction according to the rated power;

[0052] Among them, the joint constraints of each execution unit are as follows:

[0053] SOC constraints of the execution unit:

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

[0055] Discharge power constraints of the execution unit:

[0056] 0≤P dis,i,T ≤P i rated

[0057] The SOC change constraints of the execution unit during discharge are:

[0058]

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

[0060] The execution units that meet the joint constraint conditions respond to the dispatch target charging power instruction according to the allocated charging power; the execution units that cannot meet the joint constraint conditions respond to the dispatch target charging power instruction according to the rated power;

[0061] Among them, the joint constraints of each execution unit are as follows:

[0062] SOC constraints of the execution unit:

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

[0064] The charging power constraints of the execution unit are:

[0065] 0≤P ch,i,T ≤P i rated

[0066] The SOC change constraints of the execution unit during charging are:

[0067]

[0068] In the formula, ΔT is the set time period, is the current capacity of the i-th execution unit.

[0069] The present invention also proposes a power control system based on energy storage unit regulation priority evaluation, comprising:

[0070] An evaluation index establishment module is used to obtain characteristic data of the energy storage unit operation status to establish evaluation indicators of the energy storage unit status, including: state of charge, health state, energy state extreme difference, voltage standard deviation coefficient, voltage extreme difference and temperature extreme difference;

[0071] The energy storage unit calibration module is used for the energy storage unit to calibrate its own state of charge, battery capacity and health state; the calibrated state of charge and health state of the energy storage unit are fed back to the battery management system, and the battery management system verifies the battery state estimation model built into the battery management system using the calibrated state of charge and health state to obtain a verified battery state estimation model; it 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;

[0072] The adjustment priority calculation module is used to take the weighted sum of the scores of various evaluation indicators of the energy storage unit after calibration as the comprehensive evaluation score; screen out the energy storage units that are allowed to be adjusted according to the monitoring data, and determine the adjustment priority of the energy storage units that are allowed to be adjusted by using the comprehensive evaluation scores and the number of charge and discharge cycles of the energy storage units that are allowed to be adjusted;

[0073] A dispatch target power instruction response module, used for selecting the allowed-adjustment 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 allowed-adjustment energy storage unit;

[0074] 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 turn as the execution unit according to the adjustment priority of each adjustable energy storage unit from high to low. The battery management system calculates the charge state target value of each execution unit according to the charge state and health state of each execution unit output by the verified battery state estimation model; based on the charge state target value of each execution unit, the dispatch target discharge power is allocated to the execution unit that meets the joint constraint condition, and the execution unit that cannot meet the joint constraint condition responds to the dispatch target discharge power instruction according to the rated power;

[0075] When the dispatch target charging power is not 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 to respond to the dispatch target power instructions. 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 constraints, and the execution units that cannot meet the joint constraints respond to the dispatch target discharge power instructions according to the rated power.

[0076] The beneficial effects of the present invention are that, compared with the prior art, at least the present invention includes that, 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 extreme difference, voltage standard deviation coefficient, voltage extreme difference and temperature extreme difference are introduced, forming a more comprehensive evaluation system, ensuring accurate evaluation of the state of the energy storage unit.

[0077] When the present invention performs battery compartment-level calibration, by improving the calibration accuracy of SOC and SOH, the actual state of the energy storage unit is more accurately evaluated, thereby achieving a better power control command allocation, helping to optimize the operating efficiency of the energy storage system, reduce energy loss, and improve overall energy utilization, optimize power allocation and operating efficiency. Accurate SOC and SOH evaluation can provide more accurate data for the battery management system, thereby optimizing the battery's charging and discharging strategy, reducing overcharging or over-discharging, and extending the battery's service life. Through comprehensive calibration at the battery compartment level, the excessive consumption of individual battery modules can be effectively prevented, further extending the overall life of the battery system. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0079] Figure 2 This is a comparison diagram of the model voltage of the energy storage unit battery cluster obtained by Kalman filtering calculation based on the central error entropy criterion in an embodiment of the present invention and the voltage sent to the BMS;

[0080] Figure 3 This is a comparison chart of the overall cumulative output of the energy storage power station using the power control strategy proposed by the present invention and the commonly used strategy for power allocation in an embodiment of the present invention. DETAILED DESCRIPTION

[0081] In order to make the purpose, technical scheme and advantages of the present invention clearer, the technical scheme of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. The embodiments described in this application are only embodiments of a part of the present invention, rather than all embodiments. Based on the spirit of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work belong to the protection scope of the present invention.

[0082] The present invention proposes a power control method based on energy storage unit regulation priority evaluation, such as Figure 1 As shown, including:

[0083] Step 1, obtain characteristic data of the operating status of the energy storage unit to establish evaluation indicators of the energy storage unit status, including: state of charge, health state, energy state extreme difference, voltage standard deviation coefficient, voltage extreme difference and temperature extreme difference.

[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 status of the energy storage unit from the monitoring data sent by the BMS;

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

[0087] The collected PCS monitoring data includes but is not limited to: transmittable power, actual transmit power and regulation status.

[0088] Step 1.2, selecting evaluation indicators of the energy storage unit status from the characteristic data;

[0089] Specifically, the evaluation indicators selected from the features include but are not limited to: SOC, SOH, SOE range, voltage standard deviation coefficient, voltage range and temperature range; among them, SOC and SOH are monitoring data sent by BMS; SOE range is calculated based on SOE data sent by BMS; voltage standard deviation coefficient U d And voltage difference U r Calculated based on the voltage data sent by the BMS; Temperature extreme difference T r Calculated based on the temperature data sent by the BMS.

[0090] Among them, SOC and SOH characterize the regulation ability of the energy storage unit, SOE extreme difference and voltage standard deviation coefficient characterize the consistency between each energy storage unit, and voltage extreme difference and temperature extreme difference characterize the working performance of the energy storage unit.

[0091] When evaluating the state of the energy storage unit, the present invention not only considers the two core indicators of SOC and SOH, but also introduces auxiliary indicators such as SOE extreme difference, voltage standard deviation coefficient, voltage extreme difference and temperature extreme difference, forming a more comprehensive evaluation system to ensure accurate evaluation of the state of the energy storage unit. Among them, SOC and SOH, which directly reflect the regulation ability of the energy storage unit, are used as core evaluation indicators.

[0092] Step 2, the energy storage unit calibrates its own 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 uses the calibrated state of charge and health status to verify the battery state estimation model built into the battery management system to obtain a verified battery state estimation model.

[0093] Specifically, step 2 includes:

[0094] In step 2.1, each energy storage unit uses a Kalman filter method based on the central 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 invention optimizes the parameter adjustment of the Kalman filter algorithm by introducing the central 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 energy storage units, but also effectively solves the problem of decreased accuracy that may occur in traditional filtering methods under high dynamic environments, and realizes more accurate and reliable evaluation and control of battery performance.

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

[0097] Based on the second-order RC circuit of the battery, with SOC as the state variable and the battery voltage as the observation variable, the Kalman filtering method based on the center error entropy criterion is used to calibrate the SOC, 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, with battery capacity as the state variable and the SOC estimation error as the observation variable, the Kalman filtering method based on the center error entropy criterion is used to calibrate the battery capacity, and the SOH is calibrated based on the calibrated battery capacity.

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

[0099] In the prior art, the BMS has a built-in battery state estimation model, and the SOC and SOH are calibrated at the BMS level. The BMS level can only collect parameters such as the 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 will be affected by various uncertain factors such as battery aging, ambient temperature, and battery operating status, more importantly, the measurement accuracy of the battery monitor and the estimation accuracy of the fuel gauge used at the BMS level will affect the estimation accuracy of SOC and SOH. As the operating time increases, the error of the SOC and SOH calibration based on the BMS level gradually increases, resulting in non-optimal allocation of power control instructions for the energy storage power station. Therefore, the present invention proposes to regard the entire battery compartment as a large battery, based on the equivalent circuit of the battery, and adopt the Kalman filtering method based on the central error entropy criterion to calibrate the SOC and SOH from the battery compartment level, so as to more accurately evaluate the SOC and SOH of the entire battery compartment. Moreover, this battery compartment level calibration helps to identify potential problems of individual battery modules or battery packs in the battery compartment, discover fault signs in advance, and reduce the probability of system-level faults in the energy storage station, thereby improving the reliability of the operation of the entire energy storage station and improving the fault diagnosis capability of the energy storage station system level. In addition, the battery compartment level calibration is not affected by the uncertainty of environmental conditions (such as temperature changes and load fluctuations). Since the battery compartment level calibration considers the comprehensive effect of the entire battery compartment, the uncertainty of environmental conditions will not affect the comprehensive effect, so it can improve the stability and robustness of the system and enhance the adaptability and stability of the system. The method proposed in the present invention effectively avoids the influence of the measurement accuracy of the battery monitor and the estimation accuracy of the fuel gauge on the SOC and SOH calibration results during the calibration process, and improves the accuracy and reliability of the calibration results.

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

[0101] Specifically, step 2.2 includes:

[0102] Step 2.2.1, transmitting the calibrated state of charge, battery capacity and health status of the energy storage unit 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 via a communication network; wherein the communication network includes but is not limited to: CAN bus, RS-485.

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

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

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

[0108] When the error between the SOC and SOH output by the battery state estimation model and the SOC and SOH after calibration of the energy storage unit 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 state; where the set limit is 0.05.

[0109] In the method proposed in the present invention, when the calibrated SOC and SOH data of the energy storage unit sent during model verification have a large deviation from the SOC and SOH estimated values ​​of the BMS, a signal for recalibrating the state of charge and health status will be sent to the corresponding energy storage unit, thereby forming a closed-loop control of the SOC and SOH calibration.

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

[0111] In a non-limiting preferred embodiment, based on the SOC and SOH estimated values ​​output by the verified battery state estimation model, the BMS can optimize the battery charging and discharging strategy, for example, adjusting the charging limit and discharge depth to prevent overcharging or over-discharging to protect the battery. Based on the SOC and SOH estimated values ​​output by the verified battery state estimation model, the fault detection and early warning algorithm is updated to improve the detection capability of potential battery faults. At the same time, the long-term health status of the battery is regularly evaluated, and life prediction and health analysis are performed based on the SOH data.

[0112] In the method proposed by the present invention, the Kalman filter method based on the central error entropy criterion configures the feedback link, and the calibrated SOC and SOH are fed back to the BMS level. The BMS uses the calibrated SOC and SOH to update the built-in SOC and SOH estimation models, so that the SOC and SOH estimation models are accurate. This feedback mechanism can significantly improve the estimation accuracy of the battery state by the BMS, especially under complex or dynamic load conditions, and optimize the battery management strategy. Feedback of the calibrated SOC and SOH enables the BMS to adjust its estimation model in real time, thereby improving the adaptive ability of the BMS. This dynamic adjustment mechanism enables the system to respond faster to changes in battery performance, such as aging, ambient temperature fluctuations, etc., thereby maintaining high-precision battery state monitoring. Based on the updated SOC and SOH estimation models, the BMS estimates accurate SOC and SOH to optimize the charging and discharging strategies, especially when the battery is aged or the performance is degraded, and the charging rate and discharge depth are adjusted more intelligently, thereby reducing the stress and loss on the battery, extending the battery life, and improving the energy efficiency. Moreover, the feedback mechanism can enhance the fault prediction capability of the system. By acquiring 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 alarms, thereby reducing the risk of unexpected shutdown or failure of the battery system and improving the system's failure prediction capabilities.

[0113] The present invention realizes the 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 the accurate evaluation of the operating status 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 synchronously. Therefore, the calibration process of SOC and SOH is feedback-adjusted according to 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, which includes multiple aspects of operation and functions to ensure that the system can make full use of these calibration results to optimize battery management and performance.

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

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

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

[0117] Step 4, taking the weighted sum of the scores of various evaluation indicators of the energy storage unit after calibration as the comprehensive evaluation score; screening out the energy storage units that are allowed to be adjusted according to the monitoring data, and determining the adjustment priority of the energy storage units that are allowed to be adjusted using the comprehensive evaluation scores of the energy storage units that are allowed to be adjusted and their charge and discharge cycle numbers.

[0118] The weighted sum of the scores of the calibrated evaluation indicators of the energy storage unit is used as the comprehensive evaluation score, including:

[0119] The subjective weights of the calibrated evaluation indicators are calculated by quantitative method, and the objective weights of the calibrated evaluation indicators are calculated by principal component analysis. The subjective weights and objective weights of the evaluation indicators are proportionally integrated to obtain the weights of the calibrated evaluation indicators.

[0120] Specifically, the subjective weights of the calibrated evaluation indicators calculated using the quantitative method include:

[0121] 1) Compare each evaluation index in pairs, adopt the 9-level quantitative method, and obtain the graded quantitative value of 1 to 9 according to the importance between the two indicators. Use the obtained graded quantitative value to construct the weight evaluation matrix. The weight evaluation matrix is ​​a positive reciprocal matrix with all diagonal elements being 1.

[0122] 2) Calculate the consistency index and check the consistency of the weight evaluation matrix. Due to the large number of influencing factors, in order to avoid the one-sidedness, subjectivity and major logical errors of artificial definition, the weight evaluation matrix is ​​checked for consistency 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 there are logical problems in the weight evaluation matrix, which does not meet the theoretical requirements and needs to be rebuilt.

[0123] 3) Calculate the maximum eigenvalue of the weight evaluation matrix that meets the consistency requirements and its corresponding eigenvector, and after normalizing the eigenvector, obtain the subjective weight of each evaluation index.

[0124] Specifically, the objective weights of various evaluation indicators after calibration are calculated using principal component analysis, including:

[0125] 1) Normalize each evaluation index to reduce the impact of dimension;

[0126] 2) Calculate the standardized covariance matrix to reflect the correlation between various evaluation indicators;

[0127] 3) Perform eigendecomposition on the standardized covariance matrix to obtain multiple eigenvalues;

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

[0129] The present invention adopts a combined weighting method to determine the weights of various evaluation indicators after calibration, thereby improving the accuracy of the comprehensive evaluation score.

[0130] Based on the set scoring rules, each calibrated evaluation indicator is scored separately.

[0131] Each evaluation index is scored according to the set scoring rules to eliminate the influence of dimension.

[0132] Specifically, the scoring rules include:

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

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

[0135] Table 1 Scoring rules

[0136]

[0137] Using the scores and corresponding weights of the calibrated evaluation indicators, the comprehensive evaluation score K of the energy storage unit is calculated using the following relationship:

[0138]

[0139] In the formula,

[0140] α, β, χ, φ, η, and θ are the scores of the calibrated voltage range R(U r ), the score of the voltage standard deviation after calibration R(U d), the temperature extreme score after calibration 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 large to small according to the comprehensive evaluation score;

[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 arranged at the end of the sorting result of energy storage units that are allowed to be adjusted, and the adjustment priority of 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 allowed to be adjusted with a larger comprehensive evaluation score has a higher adjustment priority, and the energy storage unit allowed to be adjusted with a smaller comprehensive evaluation score 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 that is allowed to be adjusted and the j+1th energy storage unit that is allowed to be adjusted, respectively, K j-1 and K j+2are the comprehensive evaluation scores of the j-1th allowed adjustable energy storage unit and the j+2th allowed adjustable energy storage unit, respectively. j and C j+1 are the number of charge and discharge cycles of the jth allowable adjustable energy storage unit and the j+1th allowable adjustable energy storage unit respectively;

[0150] Therefore, 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, thereby achieving balanced power distribution.

[0151] Step 5: 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 for responding to the dispatch target power instruction;

[0152] 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 turn as the execution unit according to the adjustment priority of each adjustable energy storage unit from high to low. The battery management system calculates the charge state target value of each execution unit according to the charge state and health state of each execution unit output by the verified battery state estimation model; based on the charge state target value of each execution unit, the dispatch target discharge power is allocated to the execution unit that meets the joint constraint condition, and the execution unit that cannot meet the joint constraint condition responds to the dispatch target discharge power instruction according to the rated power;

[0153] When the dispatch target charging power is not 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 to respond to the dispatch target power instructions. 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 constraints, and the execution units that cannot meet the joint constraints respond to the dispatch target discharge power instructions according to the rated power.

[0154] Specifically, step 5 includes:

[0155] Step 5.1: When the dispatch 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 to respond to the dispatch target power instruction.

[0156] In the embodiment, the rated powers of the energy storage inverters constructed at the project site are different. Based on the zoning control requirements, response time requirements, and operation management requirements, the rated powers of the energy storage inverters in the same area must be the same. Therefore, the rated powers of the energy storage units in each area of ​​the energy storage power station are the same.

[0157] Step 5.2, 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 turn as the execution unit according to the adjustment priority of each adjustable energy storage unit from high to low, and the battery management system calculates the charge state target value of each execution unit according to the charge state and health state of each execution unit output by the verified battery state estimation model; based on the charge state target value of each execution unit, the dispatch target discharge power is allocated to the execution unit that meets the joint constraint condition, and the execution unit that cannot meet the joint constraint condition responds to the dispatch target discharge power instruction according to the rated power;

[0158] 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 power station, the adjustable energy storage units that are used to respond to the dispatch target power instruction are selected in turn as execution units in the order of the adjustment priority of each adjustable energy storage unit from high to low; the present invention allocates the dispatch target discharge power to the selected energy storage unit based on the adjustment priority of the energy storage unit, so that the two-way adjustment capability of the energy storage power station is the strongest, while taking into account the health status of the energy storage unit.

[0159] Specifically, step 5.2 includes:

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

[0161]

[0162] In the formula, SOC ref,i,T is the target state of charge value of the i-th execution unit at time T; SOC ideal SOC is the state of charge after the execution unit is calibrated; i,T and SOH i,T are the state of charge and health state 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 and upper limits of the state of charge of the energy storage unit; SOH min,T , SOH max,Tare the lower and upper limits of SOH of the energy storage unit at time T respectively;

[0163] In the first and third items, when SOC i,T <SOC min or SOC i,T >SOC max When the SOC is restored, the SOC reference values ​​of all executing energy storage units are set to the ideal SOC values;

[0164] In the second term, when SOC i,T In [SOC min , SOC max ] interval, power is allocated based on the SOH of each energy storage unit. The energy storage units in good health are deeply charged and discharged, while the energy storage units in poor health are shallowly charged and discharged.

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

[0166]

[0167] In the formula, 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;

[0168] Step 5.2.3, 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:

[0169]

[0170] 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;

[0171] Step 5.2.4, the execution units that meet the joint constraint conditions respond to the dispatch target discharge power instruction according to the allocated discharge power; the execution units that cannot meet the joint constraint conditions respond to the dispatch target discharge power instruction according to the rated power.

[0172] Among them, the joint constraints of each execution unit are as follows:

[0173] SOC constraints of the execution unit:

[0174] SOC min <SOCi,T <SOC max

[0175] The charging and discharging power constraints of the execution unit are:

[0176] 0≤P dis,i,T ≤P i rated

[0177] SOC change constraints of the execution unit:

[0178]

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

[0180] The execution units that meet the joint constraint conditions at the same time execute corresponding operations according to the allocated discharge power to respond to the scheduling target discharge power instruction, and the execution units with power margin send a signal to the battery management system that the first power allocation has been completed and request a second power allocation, thereby providing conditions for the secondary allocation of the scheduling target discharge power;

[0181] Among them, the power margin of the execution unit that meets the joint constraint condition satisfies the following relationship:

[0182]

[0183] In the formula, is the power margin of the sth execution unit that satisfies the joint constraint at time T, P dis,s,T The discharge power allocated to the sth execution unit that meets the joint constraint at time T, is the rated power of the sth execution unit that satisfies the joint constraint.

[0184] The execution units that cannot meet the joint constraint conditions perform corresponding operations according to the rated power to respond to the dispatch target discharge power instruction and calculate the power shortage;

[0185] Among them, the power shortage of the execution unit that cannot meet the joint constraint condition satisfies the following relationship:

[0186]

[0187] In the formula, is the power deficit of the mth execution unit that cannot meet the joint constraint at time T, P dis,m,T is the discharge power allocated to the mth execution unit that cannot meet the joint constraint at time T, is the rated power of the mth execution unit that cannot meet the joint constraint.

[0188] The power shortage is distributed to the execution units with power margin to achieve the second power distribution, satisfying the following relationship:

[0189]

[0190] Where P d ' is,s,T is the updated value of the discharge power obtained by the allocation of the sth execution unit that meets the joint constraint at time T, S is the number of execution units that meet the joint constraint, and M is the number of execution units that cannot meet the joint constraint.

[0191] Both the power deficit and the power margin are determined based on the rated power of the energy storage unit. When the rated power of each energy storage unit is equivalent, the dispatch target power can be evenly distributed to each energy storage unit after being allocated to the energy storage unit with a higher 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 station, all energy storage units that are allowed to be adjusted are execution units to respond to the dispatch target power instruction. The battery management system calculates the charge state target value of each execution unit according to the charge state and health state of each execution unit output by the verified battery state estimation model; based on the charge state target value of each execution unit, the dispatch target charging power is allocated to the execution unit that meets the joint constraint condition, and the execution unit that cannot meet the joint constraint condition responds 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 charge state target value of each execution unit according to the charge state and health state of each execution unit output by the verified battery state estimation model using the following relationship:

[0195]

[0196] In the formula, SOC ref,i,T is the target state of charge value of the i-th execution unit at time T; SOC ideal SOC is the state of charge after the execution unit is calibrated; i,T and SOH i,T are the state of charge and health state 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 and upper limits of the state of charge of the energy storage unit; SOH min,T , SOH max,TThey are the lower limit and upper limit of the health state of the energy storage unit at time T respectively;

[0197] Step 5.3.2, based on the charge state target value of each execution unit, calculate the ideal discharge power of each execution unit using 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 powers of all execution units, and according to the scheduling target charging power, the charging power allocated to each execution unit is calculated using the following relationship:

[0201]

[0202] 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; is the scheduling target charging power at time T; is the ideal charging power of the i-th execution unit at time T.

[0203] The execution units that meet the joint constraint conditions respond to the dispatch target charging power instruction according to the allocated charging power; the execution units that cannot meet the joint constraint conditions respond to the dispatch target charging power instruction according to the rated power;

[0204] Among them, the joint constraints of each execution unit are as follows:

[0205] SOC constraints of the execution unit:

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

[0207] The charging power constraints of the execution unit are:

[0208] 0≤P ch,i,T ≤P i rated

[0209] The SOC change constraints of the execution unit during charging are:

[0210]

[0211] In the formula, ΔT is the set time period, Qi present is the current capacity of the i-th execution unit.

[0212] At the same time, the execution unit that satisfies the joint constraint conditions performs corresponding operations according to the allocated charging power to respond to the scheduling target charging power instruction, and the execution unit with power margin sends a signal to the battery management system that the first power allocation has been completed and requests the second power allocation, thereby providing conditions for the secondary allocation of the scheduling target charging power;

[0213] Among them, the power margin of the execution unit that meets the joint constraint condition satisfies the following relationship:

[0214]

[0215] In the formula, is the power margin of the sth execution unit that satisfies the joint constraint at time T, P dis,s,T The discharge power allocated to the sth execution unit that meets the joint constraint at time T, is the rated power of the sth execution unit that satisfies the joint constraint.

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

[0217] Among them, the power shortage of the execution unit that cannot meet the joint constraint condition satisfies the following relationship:

[0218]

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

[0220] The power shortage is distributed to the execution units with power margin to achieve the second power distribution, satisfying the following relationship:

[0221]

[0222] Where P d ' is,s,T is the updated value of the discharge power obtained by the allocation of the sth execution unit that meets the joint constraint at time T, S is the number of execution units that meet the joint constraint, and M is the number of execution units that cannot meet the joint constraint.

[0223] For a certain energy storage power station, the total installed capacity of energy storage is 25MW / 50MWh. The energy storage power station consists of 16 energy storage units (2 collectors, 8 energy storage units each), with a single unit rated at 1.725MW. The basic parameters of each energy storage 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 collectors are different, ranging from 0.20 to 0.80, while the initial SOH values ​​are distributed between 0.8 and 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] In the formula, 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 upper layer. 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 minIt is the minimum value of the energy storage unit temperature.

[0236] According to the set scoring rules, these six indicators are scored respectively to eliminate the impact of dimension. Since the scoring 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, a state equation with SOC as the state variable and an observation equation with voltage as the observation variable is constructed. The SOC calibration system model is as follows:

[0237]

[0238] Where U 1,k and U 2,k are the equivalent circuit voltages corresponding to the first resistor R1 and the second resistor R2 in the second-order RC circuit during 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 during the kth calibration; U k is the terminal voltage of the second-order RC circuit during the kth calibration; w k and v k are the system noise and observation noise at the kth calibration respectively; U oc (SOC k ) is the circuit open circuit voltage corresponding to the SOC during 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, with the battery capacity as the state variable and the SOC estimation error as the observation variable, the capacity calibration system model is as follows:

[0240]

[0241] In the formula, is the 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 during the kth calibration,

[0242] Then the calibration value of SOH is:

[0243]

[0244] The Kalman filter based on the center error entropy criterion (CEEKF) updates the SOC calibration and capacity calibration system models respectively, so that the SOC and SOH can be calibrated. The model voltage of the energy storage unit battery cluster calculated by the Kalman filter based on the center error entropy criterion is compared with the voltage sent to the BMS. Figure 2 The steps are as follows:

[0245] 1) Initialization: Given an 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 state estimate and state covariance matrix at the next moment, that is,

[0247]

[0248]

[0249] Where F is the state transfer 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, the Newton-Raphson method is used to solve the optimal posterior state estimate, that is,

[0251]

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

[0253] 4) Calculate the posterior covariance matrix, as shown below:

[0254]

[0255] The present invention proposes to use the central entropy Kalman filter method to calibrate SOC and SOH. As an optimal state estimation method based on probability theory, the central error entropy Kalman filter has the advantages of accuracy, optimality, recursion, adaptability and strong scalability, and is very suitable for the state estimation problem of dynamic systems. Therefore, the estimation accuracy of these two core indicators is effectively improved, thereby achieving a more accurate evaluation of the operating status of the energy storage unit.

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

[0257] Table 2 Weight evaluation matrix

[0258] Assignment Importance comparison 1 Indicates that the two factors have equal importance 3 The former is slightly more important than the other two factors. 5 The former is more important among the two factors. 7 The former is obviously more important than the other two factors. 9 The former is extremely important among the two factors. 2,4,6,8 Represents the middle difference between 1-9 quantitative

[0259] Then calculate the consistency index and check the consistency CR of the weight evaluation matrix. 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 to be 0.079, which meets the consistency requirements. Then calculate λ max The corresponding eigenvectors, after normalizing the eigenvectors, 6 weight distribution coefficients are obtained, as shown in Table 3:

[0262] Table 3 Weight distribution coefficient

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

[0264] By constructing a weight evaluation matrix and calculating the consistency index, the present invention can ensure the rationality and accuracy of the weight coefficient and make the evaluation result more reliable.

[0265] Under charging conditions, the relationship between the comprehensive evaluation score K and 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] Under discharge conditions, 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 from large to small according to the comprehensive score K, and then combined with the monitoring information of the PCS, it can be determined which energy storage units are adjustable and which are not. The K of the energy storage units that are not adjustable is set to zero. If there are multiple energy storage units with the same K, the one with fewer charge and discharge times has a higher priority. In a certain iteration, there are two energy storage units with the same K, numbered 2 and 3 respectively. The adjacent energy storage unit with a larger K is numbered 1, and the adjacent energy storage unit with a smaller K is numbered 4. The calculation formula for the adjustment priority M is as follows:

[0272]

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

[0274] Table 4 Adjustment priority calculation results

[0275]

[0276] The present invention takes into account the PCS monitoring data and the number of charge and discharge times, thereby dynamically determining the adjustment priority of each energy storage unit, thereby avoiding unreasonable adjustment that may be caused by fixed priorities.

[0277] At a certain time T, the power control strategy proposed by the present invention and the common strategy are respectively applied to distribute power. The overall cumulative output of the energy storage power station is compared as follows: Figure 3 When the strategy of the present invention is adopted, during the power regulation process:

[0278] When the power command is less than 1.735MW, only the output of the energy storage unit with the highest priority is adjusted, which reduces the frequency of charging and discharging, which is beneficial to delaying the battery life attenuation;

[0279] When the power command is greater than or equal to 1.735MW but less than 22.5MW, some energy storage units are selected to act and power is allocated according to the dynamic proportional allocation strategy. The SOC of each unit is consistent and can be adjusted to an ideal value. It has strong bidirectional adjustment capability and is combined with SOH to control the depth of charge and discharge, which is beneficial to delay the battery life attenuation.

[0280] When the power command is greater than 22.5MW, all energy storage units are activated and power is distributed according to the SOC feedback control strategy, so that the output deviation of the energy storage power station is small, the continuous working time is long, and the overall regulation capability is strong.

[0281] According to different target power instructions, the present invention adopts different adjustment strategies to achieve dynamic division of the adjustment execution domain, which not only ensures the completion of the target, but also avoids the impact of excessive adjustment on battery life. The present invention proposes dynamic power allocation according to the real-time status of each energy storage unit, avoiding the imbalance of adjustment caused by fixed ratio allocation, and further improving the adjustment effect. Through precise evaluation, dynamic adjustment priority and dynamic power allocation, the present invention realizes the optimal scheduling of energy storage power station power, and improves the adjustment ability and economy of the system.

[0282] The present invention also proposes a power control system based on energy storage unit regulation priority evaluation, comprising:

[0283] An evaluation index establishment module is used to obtain characteristic data of the energy storage unit operation status to establish evaluation indicators of the energy storage unit status, including: state of charge, health state, energy state extreme difference, voltage standard deviation coefficient, voltage extreme difference and temperature extreme difference;

[0284] The energy storage unit calibration module is used for the energy storage unit to calibrate its own state of charge, battery capacity and health state; the calibrated state of charge and health state of the energy storage unit are fed back to the battery management system, and the battery management system verifies the battery state estimation model built into the battery management system using the calibrated state of charge and health state to obtain a verified battery state estimation model; it 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;

[0285] The adjustment priority calculation module is used to take the weighted sum of the scores of various evaluation indicators of the energy storage unit after calibration as the comprehensive evaluation score; screen out the energy storage units that are allowed to be adjusted according to the monitoring data, and determine the adjustment priority of the energy storage units that are allowed to be adjusted by using the comprehensive evaluation scores of the energy storage units that are allowed to be adjusted and the number of charge and discharge cycles;

[0286] A dispatch target power instruction response module, used for selecting the allowed-adjustment 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 allowed-adjustment energy storage unit;

[0287] 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 turn as the execution unit according to the adjustment priority of each adjustable energy storage unit from high to low. The battery management system calculates the charge state target value of each execution unit according to the charge state and health state of each execution unit output by the verified battery state estimation model; based on the charge state target value of each execution unit, the dispatch target discharge power is allocated to the execution unit that meets the joint constraint condition, and the execution unit that cannot meet the joint constraint condition responds to the dispatch target discharge power instruction according to the rated power;

[0288] When the dispatch target charging power is not 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 to respond to the dispatch target power instructions. 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 constraints, and the execution units that cannot meet the joint constraints respond to the dispatch target discharge power instructions according to the rated power.

[0289] The present invention is implemented in the form of a computer program, which is simple to operate and easy to expand, reduces the intensity of manual operation, and improves the level of system automation. The method and system proposed in the present invention have good versatility and can be applied to energy storage power stations of different types and sizes, and have high promotion and application value. It has significant advantages in improving the operating safety of energy storage power stations, extending battery life, and improving system regulation performance.

[0290] The present disclosure may be a system, a method and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present disclosure.

[0291] A computer-readable storage medium may be a tangible device that can hold and store instructions used by an instruction execution device. A computer-readable storage medium may be, for example, but not limited to, an electrical 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 of computer-readable storage media (a non-exhaustive list) include: a portable computer disk, 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 disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination of the foregoing. As used herein, a computer-readable storage medium is not to be interpreted as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse through a fiber optic cable), or an electrical signal transmitted through a wire.

[0292] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0293] The computer program instructions for performing the operation of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. Computer-readable program instructions may be executed completely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or completely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be personalized by utilizing the state information of the computer-readable program instructions, and the electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present disclosure.

[0294] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents, and any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A power control method based on energy storage unit adjustment priority evaluation, characterized in that: include: Acquire characteristic data of the energy storage unit operation status to establish evaluation indicators of the energy storage unit 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 calibrates its own 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 uses the calibrated state of charge and health status to verify the battery state estimation model built into the battery management system to obtain 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 according to the monitoring data, and the adjustment priority of the energy storage units that are allowed to be adjusted is determined by 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 adjustable energy storage unit, the adjustable energy storage unit with the highest adjustment priority is selected as the execution unit for responding 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 turn as the execution unit according to the adjustment priority of each adjustable energy storage unit from high to low. The battery management system calculates the charge state target value of each execution unit according to the charge state and health state of each execution unit output by the verified battery state estimation model; based on the charge state target value of each execution unit, the dispatch target discharge power is allocated to the execution unit that meets the joint constraint condition, and the execution unit that cannot meet the joint constraint condition responds to the dispatch target discharge power instruction according to the rated power; When the dispatch target charging power is not 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 to respond to the dispatch target power instructions. 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 constraints, and the execution units that cannot meet the joint constraints respond to the dispatch target discharge power instructions according to the rated power.

2. The power control method based on energy storage unit adjustment priority evaluation according to claim 1 is 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 selected 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 is 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 the 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 second-order RC circuit of the battery, 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, and obtains a verified battery state estimation model, 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 state output by the battery status estimation model and the state of charge and health state 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 state output by the battery status estimation model and the state of charge and health state 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 state.

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 scores of the calibrated evaluation indicators of the energy storage unit is used as the comprehensive evaluation score, including: The subjective weights of the calibrated evaluation indicators are calculated by quantitative method, and the objective weights of the calibrated evaluation indicators are calculated by principal component analysis. 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, the calibrated evaluation indicators are scored respectively. Using the scores and weights of the calibrated evaluation indicators, the comprehensive evaluation score K of the energy storage unit is calculated using the following relationship: In the formula, α, β, χ, φ, η, and θ are the voltage range difference U after calibration. r Rating R(U r ), the voltage standard deviation after calibration U d Rating R(U d ), the temperature difference after calibration T r Rating R(T r ), the score R(SOC) of the calibrated state of charge SOC, 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).

6. The power control method based on energy storage unit adjustment priority evaluation according to claim 1 is characterized in that: The energy storage units that are allowed to be adjusted are screened out according to the monitoring data, and the adjustment priority of the energy storage units that are allowed to be adjusted is determined by 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 large to small according to the comprehensive evaluation score; put all the non-adjustable energy storage units at the end of the sorting result of the adjustable energy storage units, and the adjustment priority of the non-adjustable energy storage units is zero; 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 allowed to be adjusted with a larger comprehensive evaluation score has a higher adjustment priority, and the energy storage unit allowed to be adjusted with a smaller comprehensive evaluation score has a lower adjustment priority; 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, 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 are obtained, and 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 are obtained; the adjustment priorities of the jth energy storage unit allowed to be adjusted and the j+1th energy storage unit allowed to be adjusted are calculated respectively according to the following relationship: Where M j and M j+1 are the adjustment priorities of the jth energy storage unit that is allowed to be adjusted and the j+1th energy storage unit that is allowed to be adjusted, respectively, K j-1 and K j+2 are the comprehensive evaluation scores of the j-1th allowed adjustable energy storage unit and the j+2th allowed adjustable energy storage unit, respectively. j and C j+1 are the number of charge and discharge cycles of the jth allowable adjustable energy storage unit and the j+1th allowable adjustable energy storage unit respectively; 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 is characterized in that: The battery management system calculates the target state of charge of each execution unit according to the state of charge and health state of each execution unit output by the verified battery state estimation model using the following relationship: In the formula, SOC ref,i,T is the target state of charge value of the i-th execution unit at time T; SOC ideal SOC is the state of charge after the execution unit is calibrated; i,T and SOH i,T are the state of charge and health state 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 respectively; SOH min,T , SOH max,T They are the lower limit and upper limit of the health state of the energy storage unit at time T respectively; 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: In the formula, 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; 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: In the formula, is the ideal charging power of the i-th execution unit at time T.

8. The power control method based on energy storage unit adjustment priority evaluation according to claim 7 is 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 according to the scheduling target discharge power, the discharge power allocated to each execution unit is calculated using the following relationship: Where P dis,i,T 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; 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 according to the scheduling target charging power, the charging power allocated to each execution unit is calculated using the following relationship: 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; is the scheduling target charging power at time T; is the ideal charging power of the i-th execution unit at time T.

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 dispatch target discharge power instruction according to the allocated discharge power; the execution units that cannot meet the joint constraint conditions respond to the dispatch 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: SOCIETY min <SOC i,T <SOC max Discharge power constraints of the execution unit: 0≤P dis,i,T ≤P i rated The SOC change constraints of the execution unit during discharge are: In the formula, ΔT is the set time period, is the current capacity of the i-th execution unit; The execution units that meet the joint constraint conditions respond to the dispatch target charging power instruction according to the allocated charging power; the execution units that cannot meet the joint constraint conditions respond to the dispatch 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: SOCIETY min <SOC i,T <SOC max The charging power constraints of the execution unit are: 0≤P ch,i,T ≤P i rated The SOC change constraints of the execution unit during charging are: In the formula, ΔT is the set time period, is the current capacity of the i-th 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 operation status to establish evaluation indicators of the energy storage unit 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 for the energy storage unit to calibrate its own state of charge, battery capacity and health state; the calibrated state of charge and health state of the energy storage unit are fed back to the battery management system, and the battery management system verifies the battery state estimation model built into the battery management system using the calibrated state of charge and health state to obtain a verified battery state estimation model; it 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; The adjustment priority calculation module is used to take the weighted sum of the scores of various evaluation indicators of the energy storage unit after calibration as the comprehensive evaluation score; screen out the energy storage units that are allowed to be adjusted according to the monitoring data, and determine the adjustment priority of the energy storage units that are allowed to be adjusted by 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, used for selecting the allowed-adjustment 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 allowed-adjustment energy storage unit; 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 turn as the execution unit according to the adjustment priority of each adjustable energy storage unit from high to low. The battery management system calculates the charge state target value of each execution unit according to the charge state and health state of each execution unit output by the verified battery state estimation model; based on the charge state target value of each execution unit, the dispatch target discharge power is allocated to the execution unit that meets the joint constraint condition, and the execution unit that cannot meet the joint constraint condition responds to the dispatch target discharge power instruction according to the rated power; When the dispatch target charging power is not 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 to respond to the dispatch target power instructions. 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 constraints, and the execution units that cannot meet the joint constraints respond to the dispatch target discharge power instructions according to the rated power.

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