A virtual power plant multi-energy storage coordinated control method based on adaptive droop control

Abstract

The embodiment of the application relates to the technical field of automatic control of power systems, and particularly relates to a virtual power plant multi-energy storage coordinated control method based on adaptive droop control, which comprises the following steps: obtaining active power instructions, actual active power and operation data of each energy storage unit of a virtual power plant grid-connected point, constructing a multi-energy storage real-time control state vector and judging power regulation working conditions; constructing an SOC safety potential function and an economic wear factor according to an SOC safety margin, a health state, a cycle loss cost and available power, and forming a comprehensive participation factor matrix; correcting active droop coefficients based on the matrix, distributing power deviations and outputting charging and discharging instructions. Compared with a traditional fixed proportion or fixed droop control method, the application improves the dynamic response accuracy and working condition adaptability of the virtual power plant to the power deviation of the grid-connected point while guaranteeing energy storage safety and prolonging the service life through the technical means of multi-dimensional state sensing and adaptive droop coefficient dynamic correction.

Description

Technical Field

[0001] This application relates to the field of power system automatic control technology, and in particular to a virtual power plant multi-energy storage coordinated control method based on adaptive droop control. Background Technology

[0002] With the widespread integration of distributed renewable energy sources, energy storage devices, and various types of loads in industrial parks, integrated energy stations, and distributed resource aggregation scenarios, virtual power plants are gradually acquiring the ability to provide power regulation and ancillary services. Among these, energy storage devices, due to their fast response speed and high control precision, have become a crucial regulation resource for virtual power plants to smooth grid-connected power fluctuations and improve power point tracking capabilities. In actual operation, the active power at the grid connection point of a virtual power plant is affected by factors such as fluctuations in renewable energy output, changes in user load, and differences in the operating status of energy storage. When the actual active power at the grid connection point deviates from the active power command, multiple energy storage units need to work together to undertake charging and discharging regulation tasks. However, existing multi-energy storage coordinated control methods mostly adopt fixed ratio allocation, fixed droop coefficient, or power allocation based solely on the rated capacity of energy storage. These methods fail to fully consider the safety margin of the state of charge, health status, cycle loss cost, and current available regulation capability of different energy storage units. If power deviation is allocated directly according to a fixed ratio or fixed droop coefficient, it can easily lead to problems such as overcharging and discharging of some energy storage units, SOC approaching the boundary, uneven cycle loss, and insufficient utilization of the response capabilities of different types of energy storage. This, in turn, affects the grid-connected power tracking effect of virtual power plants and the long-term operational reliability of energy storage systems.

[0003] Therefore, it is necessary to propose a virtual power plant multi-energy storage coordinated control method based on adaptive droop control. The droop coefficient is dynamically modified according to the SOC safety status, economic wear level and available adjustment capability of each energy storage unit to achieve safe, economical and coordinated power support for multiple energy storage units. Summary of the Invention

[0004] To address this, the present invention provides a virtual power plant multi-energy storage coordinated control method based on adaptive droop control, which overcomes the problems in the prior art where each energy storage unit cannot undertake adjustment tasks according to its own real-time state differences under fixed droop or fixed ratio allocation methods, which easily leads to overcharging and over-discharging of some energy storage, uneven life loss, low power tracking accuracy at grid connection point, and poor adaptability to operating conditions.

[0005] To achieve the above objectives, this invention provides a coordinated control method for multiple energy storage systems in a virtual power plant based on adaptive droop control. It includes:

[0006] Step S1: Obtain the first target power, actual power, and operating status of each energy storage unit at the virtual power plant grid connection point; determine the power deviation based on the first target power and actual power; and determine the current power regulation condition based on the power deviation and the operating status.

[0007] Step S2: Based on the current power regulation conditions, determine the safety margin, economic wear level, and available regulation power of each energy storage unit, and form a multi-energy storage comprehensive participation factor matrix based on the safety margin, economic wear level, and available regulation power.

[0008] Step S3: Correct the droop coefficient of each energy storage unit according to the multi-energy storage integrated participation factor matrix, and allocate the power deviation as the second target power of each energy storage unit based on the droop coefficient.

[0009] Step S4: Perform operational constraint verification on the second target power, and output the second target power that has passed the operational constraint verification as the charging and discharging command for each energy storage unit.

[0010] Further, in step S1, determining the current power regulation condition based on the power deviation and the operating state includes:

[0011] Step S11: Determine the power deviation characteristics of the current control cycle based on the direction and magnitude of the deviation between the first target power and the actual power at the virtual power plant grid connection point.

[0012] Step S12: Collect the state of charge, health status, rated parameters, power limits, operating status and loss cost information of each energy storage unit to form a real-time control status information set for each energy storage unit.

[0013] Step S13: Based on the deviation direction, extract the power limit and charge boundary corresponding to the deviation direction from the control state information set of each energy storage unit, and determine the available adjustable power of each energy storage unit under the current control direction.

[0014] Step S14: Determine the current power regulation condition based on the deviation direction, deviation magnitude, and the cumulative sum of the available adjustable power of each energy storage unit.

[0015] Further, in step S2, a multi-energy storage integrated participation factor matrix is ​​formed, including:

[0016] Step S21: Determine the safety margin of the current state of charge of each energy storage unit from the charge boundary along the deviation direction according to the deviation direction corresponding to the current power regulation condition.

[0017] Step S22: Based on the safety margin of each energy storage unit, construct the charge safety potential function of each energy storage unit;

[0018] Step S23: Based on the health status and unit cycle loss cost of each energy storage unit, construct the economic wear factor of each energy storage unit.

[0019] Step S24: Perform a comprehensive weighted calculation on the available adjustable power, charge safety potential function and economic wear factor of each energy storage unit to obtain the comprehensive participation factor of each energy storage unit;

[0020] Step S25: Arrange the comprehensive participation factors of each energy storage unit to form a multi-energy storage comprehensive participation factor matrix.

[0021] Further, in step S3, allocating the power deviation to the second target power of each energy storage unit based on the droop coefficient includes:

[0022] Step S31: Based on the comprehensive participation factor of each energy storage unit, the droop coefficient of each energy storage unit is corrected to obtain the adaptive droop coefficient of each energy storage unit.

[0023] Step S32: Based on the adaptive droop coefficient of each energy storage unit, the power deviation is allocated to each energy storage unit to obtain the preliminary target power of each energy storage unit.

[0024] Step S33: Based on the charge safety potential function and economic wear factor of each energy storage unit, the preliminary target power is corrected to obtain the corrected second target power of each energy storage unit.

[0025] Further, in step S31, the adaptive droop coefficient of each energy storage unit is obtained, including:

[0026] Obtain the droop coefficient of each energy storage unit;

[0027] Using the comprehensive participation factor of each energy storage unit as a weight, the benchmark droop coefficient is weighted and corrected to obtain the adaptive droop coefficient of each energy storage unit.

[0028] Further, in step S33, the preliminary target power is corrected, including:

[0029] In response to the energy storage unit's charge safety potential function being greater than a preset safety threshold or its economic wear factor being greater than a preset wear threshold, the initial target power of the energy storage unit is reduced, and the amount of the reduction in the initial target power is transferred to other energy storage units that meet the safety constraints and online operating conditions.

[0030] Further, in step S4, the second target power is subjected to operational constraint verification, and the verified second target power is output as the charging and discharging command for each energy storage unit, including:

[0031] Step S41: Perform power limit verification on the second target power of each energy storage unit and limit the second target power within the range of the available adjustable power of each energy storage unit.

[0032] Step S42: Perform a state of charge boundary check on the second target power of each energy storage unit to ensure that after each energy storage unit executes the second target power, the state of charge of its next control cycle does not exceed the allowable upper and lower limits of the state of charge.

[0033] Step S43: Perform a charge / discharge state consistency check on the second target power of each energy storage unit, and prohibit the same energy storage unit from being in both charging and discharging states simultaneously within the same control cycle.

[0034] Step S44: The second target power that simultaneously passes the power limit verification, state of charge boundary verification, and charge / discharge state consistency verification is used as the charge / discharge command output for each energy storage unit.

[0035] Furthermore, after step S44, the following steps are also included:

[0036] Calculate the remaining power deviation after allocation based on the actual power executed by each energy storage unit;

[0037] In response to the absolute value of the remaining power deviation being less than or equal to a preset deviation threshold, the charging and discharging power command of each energy storage unit and the remaining power deviation are output.

[0038] In response to the absolute value of the remaining power deviation being greater than a preset deviation threshold, the multi-energy storage integrated participation factor matrix is ​​corrected and the power is reallocated based on the deviation direction corresponding to the remaining power deviation and the available adjustable power of each energy storage unit that has not yet been called after this power allocation.

[0039] Furthermore, it also includes:

[0040] When the state of charge of any energy storage unit is close to the safety boundary, the health status is lower than the preset threshold, or the unit cycle loss cost is higher than the preset threshold, the comprehensive participation factor of that energy storage unit is reduced, and the power that the energy storage unit could not allocate due to the reduced weight is transferred to other energy storage units that meet the operating constraints.

[0041] Furthermore, it also includes:

[0042] After each control cycle, the charge safety potential function, economic wear factor, comprehensive participation factor and adaptive droop coefficient of each energy storage unit are updated; when the absolute value of the remaining power deviation exceeds the preset threshold, the output regulation capability is insufficient.

[0043] Compared with the prior art, the beneficial effects of the present invention are as follows: The embodiments of the present invention collect the first target power and actual power at the grid connection point in real time and calculate the direction and magnitude of the power deviation. Simultaneously, they collect the state of charge, health status, rated parameters, power limits, operating status, and loss cost information of each energy storage unit to construct a real-time control state information set. Then, based on the deviation direction, the power limit and charge boundary of the corresponding direction are extracted from the state information set to determine the available adjustable power of each energy storage unit under the current control direction. Finally, based on the deviation direction, deviation magnitude, and the cumulative sum of the available adjustable power of each energy storage unit, the current power regulation condition is accurately determined. The system determines whether the operating conditions are discharge compensation, charging absorption, or insufficient regulation capacity. Simultaneously, it sets the available adjustable power of energy storage units that are offline, faulty, locked, or have abnormal communication to zero and removes them. This enables multi-energy storage coordinated control to accurately identify the direction and degree of deviation between the actual power at the grid connection point and the first target power, the real-time adjustable capability of each energy storage unit, and whether the overall regulation capability meets the requirements. It also adaptively switches control strategies according to different operating conditions, effectively avoiding incorrect power allocation direction or distorted regulation capability assessment caused by misjudgment of operating conditions. This provides an accurate and reliable data foundation for the precise coordinated allocation of power from multiple energy storage units in the future.

[0044] Furthermore, in this embodiment of the invention, the safety margin of the current state of charge of each energy storage unit along the direction of the deviation corresponding to the current power regulation condition is determined, and a safety potential function of charge is constructed based on the safety margin. This allows energy storage units whose state of charge is close to the safety boundary to automatically increase the value of the potential function to suppress their continued participation in high-power charging and discharging in the same direction. At the same time, an economic wear factor is constructed based on the health status and unit cycle loss cost of each energy storage unit. This allows energy storage units with poor health status or high unit cycle loss cost to automatically increase the wear factor value to reduce their power allocation priority. Then, the available regulation power, the safety potential function of charge, and the economic wear factor of each energy storage unit are comprehensively weighted to obtain a comprehensive participation factor, which is then arranged to form a multi-energy storage comprehensive participation factor matrix. When the sum of the available regulation power of all energy storage units is zero, an insufficient regulation capability flag is output. Thus, the comprehensive participation factor can comprehensively reflect the safety margin, economic wear degree, and available regulation capability of each energy storage unit under the current operating condition.

[0045] Furthermore, this embodiment of the invention uses the comprehensive participation factor of each energy storage unit as a weight to weight the benchmark droop coefficient, so that the energy storage unit with a larger comprehensive participation factor obtains a smaller adaptive droop coefficient and thus bears a larger proportion of power deviation allocation. At the same time, the initial target power is corrected according to the charge safety potential function and economic wear factor of each energy storage unit. When the charge safety potential function is greater than a preset safety threshold or the economic wear factor is greater than a preset wear threshold, the initial target power of the energy storage unit is reduced and the reduction is transferred to other energy storage units that meet the safety constraints and online operation conditions. This allows energy storage units with lower safety margins or heavier economic wear to automatically reduce their power load, thereby achieving accurate power deviation allocation while taking into account the safety and economy of energy storage operation. In addition, when multiple energy storage units contain different types of energy storage, a response correction coefficient is set according to the energy storage type. When the power deviation change rate is large, the response priority of power-type energy storage is increased to give full play to its rapid response advantage.

[0046] Furthermore, this embodiment of the invention performs power limit verification, state of charge boundary verification, and charge / discharge state consistency verification on the second target power of each energy storage unit in sequence. This limits the second target power within the available adjustable power range of each energy storage unit, ensures that the state of charge does not exceed the allowable upper and lower limits in the next control cycle after the second target power is executed, and prohibits the same energy storage unit from charging and discharging simultaneously in the same control cycle. This effectively avoids actual execution deviations caused by the second target power exceeding the physical capacity boundary of energy storage or equipment malfunctions caused by charging / discharging state conflicts. Based on this, the remaining power deviation after allocation is calculated according to the actual executed power of each energy storage unit. When the absolute value of the remaining power deviation is not greater than a preset deviation threshold, the command and the remaining deviation are output. When the absolute value is greater than the preset deviation threshold, the command and the remaining deviation are output. The system corrects the comprehensive participation factor matrix and redistributes power based on the remaining deviation direction and the available adjustable power of each energy storage unit that has not yet been called up, thus realizing closed-loop iterative correction of the power deviation that still exists after the first allocation. At the same time, it executes cyclically according to the preset control cycle, and after each cycle, it updates the relevant parameters for the next cycle based on the actual executed power, the change in state of charge, the change in health status, and the cumulative amount of cycle loss. This allows each control parameter to be dynamically adjusted with the change in energy storage status, thereby realizing continuous adaptive optimization of multi-energy storage coordinated control. In addition, when the total available adjustable power of all energy storage units is insufficient, the system outputs the maximum executable power according to the principle of prioritizing energy storage safety and calculates the uncompensated deviation. Based on the deviation direction, it outputs a new energy generation restriction command or a grid-connected power deviation alarm.

[0047] Furthermore, this embodiment of the invention monitors the state of charge, health status, and unit cycle loss cost of each energy storage unit during the control cycle execution process. When the state of charge of any energy storage unit approaches the safety boundary, the health status is below a preset threshold, or the unit cycle loss cost is above a preset threshold, its comprehensive participation factor is actively reduced. The power allocation that the energy storage unit cannot undertake due to the reduced weight is automatically transferred to other energy storage units that meet the operating constraints. This achieves proactive protection of high-risk energy storage units and dynamic reallocation of power tasks, effectively preventing high-risk energy storage units from being over-utilized and ensuring the overall operational safety of the energy storage system. It balances with service life; at the same time, after each control cycle, the charge safety potential function, economic wear factor, comprehensive participation factor and adaptive droop coefficient of each energy storage unit are updated according to the actual execution power, state of charge change, health status change and cumulative cycle loss of each energy storage unit. This enables the above parameters to be adaptively adjusted with the dynamic changes of the energy storage unit status. When the remaining power deviation exceeds the preset threshold, an insufficient regulation capability indicator is output. This realizes the adaptive linkage update between energy storage status changes and droop control parameters, and provides a clear status feedback signal to the upper-level system when the overall regulation capability of multiple energy storage units is insufficient. Attached Figure Description

[0048] Figure 1 This is a flowchart of the virtual power plant multi-energy storage coordinated control method based on adaptive droop control according to an embodiment of this application;

[0049] Figure 2 This is a graph showing the grid-connected power deviation input and power regulation condition discrimination in the virtual power plant multi-energy storage coordinated control method based on adaptive droop control in an embodiment of this application.

[0050] Figure 3 This is a dynamic response diagram of adaptive droop control for multiple energy storage in the virtual power plant multi-energy storage coordinated control method based on adaptive droop control in the embodiments of this application;

[0051] Figure 4 This is a diagram showing the residual power deviation verification and SOC evolution in the virtual power plant multi-energy storage coordinated control method based on adaptive droop control, as described in this application embodiment. Detailed Implementation

[0052] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0053] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0054] like Figures 1-4 As shown, Figure 1 This is a flowchart of the virtual power plant multi-energy storage coordinated control method based on adaptive droop control according to an embodiment of this application; Figure 2 This is a graph showing the grid-connected power deviation input and power regulation condition discrimination in the virtual power plant multi-energy storage coordinated control method based on adaptive droop control in an embodiment of this application. Figure 3 This is a dynamic response diagram of adaptive droop control for multiple energy storage in the virtual power plant multi-energy storage coordinated control method based on adaptive droop control in the embodiments of this application; Figure 4 This is a diagram showing the residual power deviation verification and SOC evolution in the virtual power plant multi-energy storage coordinated control method based on adaptive droop control, as described in this application embodiment.

[0055] The technical solution provided in this application includes the following steps:

[0056] Step S1: Obtain the first target power, actual power, and operating status of each energy storage unit at the virtual power plant grid connection point; determine the power deviation based on the first target power and actual power; and determine the current power regulation condition based on the power deviation and the operating status.

[0057] Step S2: Based on the current power regulation conditions, determine the safety margin, economic wear level, and available regulation power of each energy storage unit, and form a multi-energy storage comprehensive participation factor matrix based on the safety margin, economic wear level, and available regulation power.

[0058] Step S3: Correct the droop coefficient of each energy storage unit according to the multi-energy storage integrated participation factor matrix, and allocate the power deviation as the second target power of each energy storage unit based on the droop coefficient.

[0059] Step S4: Perform operational constraint verification on the second target power, and output the second target power that has passed the operational constraint verification as the charging and discharging command for each energy storage unit.

[0060] In this embodiment of the invention, the virtual power plant grid connection point is equipped with a power acquisition device and a communication terminal. The power acquisition device acquires the actual active power of the grid connection point in real time, and the communication terminal receives the active power target command for the grid connection point issued by the upper-level dispatch system of the virtual power plant. Each energy storage unit obtains operating status data through its local battery management system and uploads the data to the virtual power plant coordination controller through the communication network. At the beginning of each control cycle, the coordination controller synchronously collects the first target power, actual power, and real-time operating status information of all online energy storage units at the grid connection point, serving as the data basis for subsequent power deviation calculation and operating condition judgment.

[0061] The first target power of the grid connection point includes, but is not limited to, the power planned by the virtual power plant dispatch, the automatic generation control command, or the power setting value of the grid connection point issued by the grid dispatching agency; the actual power of the grid connection point includes, but is not limited to, the real-time measured power of the grid connection point, the average power after filtering, or the reconstructed power value after communication delay compensation; the operating status data of the energy storage unit includes, but is not limited to, state of charge, health status, rated power, rated capacity, maximum charging power, maximum discharging power, state of charge limit, state of charge limit, unit cycle loss cost, and operating status flags, the operating status flags including online status, fault status, locked status, and communication abnormal status.

[0062] Specifically, in step S1, determining the current power regulation condition based on the power deviation and the operating state includes:

[0063] Step S11: Determine the power deviation characteristics of the current control cycle based on the direction and magnitude of the deviation between the first target power and the actual power at the virtual power plant grid connection point.

[0064] Step S12: Collect the state of charge, health status, rated parameters, power limits, operating status and loss cost information of each energy storage unit to form a real-time control status information set for each energy storage unit.

[0065] Step S13: Based on the deviation direction, extract the power limit and charge boundary corresponding to the deviation direction from the control state information set of each energy storage unit, and determine the available adjustable power of each energy storage unit under the current control direction.

[0066] Step S14: Determine the current power regulation condition based on the deviation direction, deviation magnitude, and the cumulative sum of the adjustable power available in each energy storage unit. The current power regulation condition includes discharge compensation condition, charge absorption condition, and insufficient regulation capacity condition.

[0067] In this embodiment of the invention, the active power command (i.e., the first target power) at the grid connection point of the virtual power plant is used. And the actual active power at the grid connection point (i.e., actual power). Calculate the real-time active power deviation of the virtual power plant :

[0068] ;

[0069] in, for The real-time active power deviation needs to be compensated by multiple energy storage units in a coordinated manner at all times; when When the actual active power at the grid connection point is lower than the active power command at the grid connection point, the energy storage unit needs to discharge to compensate; when When the actual active power at the grid connection point exceeds the active power command at the grid connection point, the energy storage unit needs to charge and absorb the power.

[0070] Get the State of charge of each energy storage unit Health status Rated power Rated capacity Maximum charging power Maximum discharge power State of charge limit Upper limit of state of charge Unit cycle loss cost and running status flags Construct a real-time control state vector for multiple energy storage systems; among which, , The number of energy storage units within the virtual power plant; For the first Rated power of each energy storage unit For the first Rated capacity of each energy storage unit For the first Unit cycle loss cost of energy storage unit Used to characterize the Whether each energy storage unit is online, faulty, locked, or in a communication abnormal state.

[0071] Based on real-time active power deviation The direction, determine the first The available adjustable power of each energy storage unit during the current control cycle :

[0072]

[0073] in, For the first The available adjustable power of each energy storage unit under the current control direction. To control the cycle duration.

[0074] Based on the real-time active power deviation direction, deviation magnitude, and total available adjustable power of multiple energy storage units, the current power regulation condition is determined; when Furthermore, the total usable discharge power of multiple energy storage units is not less than When, it is determined to be a discharge compensation condition; when Furthermore, the total usable charging power of multiple energy storage units is not less than When the total available adjustable power of multiple energy storage units is less than the charging absorption condition, it is determined to be in charging absorption mode. When the condition is determined to be insufficient adjustment capacity, the operating condition is considered to be in this state. When an energy storage unit is offline, faulty, locked, or in a communication abnormal state, the available regulated power of the energy storage unit will be reduced. Set it to zero and remove it from the power deviation allocation object of the current control cycle.

[0075] This invention embodiment collects the first target power and actual power at the grid connection point in real time and calculates the direction and magnitude of the power deviation. Simultaneously, it collects the state of charge, health status, rated parameters, power limits, operating status, and loss cost information of each energy storage unit to construct a real-time control status information set. Then, based on the deviation direction, it extracts the corresponding power limit and charge boundary from the status information set to determine the available adjustable power of each energy storage unit under the current control direction. Finally, based on the deviation direction, deviation magnitude, and the cumulative sum of the available adjustable power of each energy storage unit, it accurately determines the current power regulation condition as a discharge compensation condition. In charging absorption or insufficient regulation conditions, the available adjustable power of energy storage units that are offline, faulty, locked, or have abnormal communication is set to zero and removed. This enables multi-energy storage coordinated control to accurately identify the direction and degree of deviation between the actual power at the grid connection point and the first target power, the real-time adjustable capability of each energy storage unit, and whether the overall regulation capability meets the requirements. It also adaptively switches control strategies according to different operating conditions, effectively avoiding incorrect power allocation direction or distorted regulation capability assessment caused by misjudgment of operating conditions. This provides an accurate and reliable data foundation for the precise coordinated allocation of power from multiple energy storage units in the future.

[0076] Specifically, in step S2, a multi-energy storage integrated participation factor matrix is ​​formed, including:

[0077] Step S21: Determine the safety margin of the current state of charge of each energy storage unit from the charge boundary along the deviation direction according to the deviation direction corresponding to the current power regulation condition.

[0078] Step S22: Based on the safety margin of each energy storage unit, construct the charge safety potential function of each energy storage unit;

[0079] Step S23: Based on the health status and unit cycle loss cost of each energy storage unit, construct the economic wear factor of each energy storage unit.

[0080] Step S24: Perform a comprehensive weighted calculation on the available adjustable power, charge safety potential function and economic wear factor of each energy storage unit to obtain the comprehensive participation factor of each energy storage unit;

[0081] Step S25: Arrange the comprehensive participation factors of each energy storage unit to form a multi-energy storage comprehensive participation factor matrix.

[0082] In this embodiment of the invention, the first power regulation condition is calculated based on the current power regulation condition. SOC safety distance of each energy storage unit :

[0083]

[0084] in, The larger the value, the higher the value. The further an energy storage unit is from the SOC safety boundary in the current charge / discharge direction, the greater its safety margin.

[0085] According to the SOC safety distance , construct the first SOC safety potential function of each energy storage unit :

[0086]

[0087] in, For the first The SOC safety potential function of each energy storage unit To prevent a preset positive number with a denominator of zero; when the SOC of the energy storage unit approaches the safety boundary under the current control direction, The increase is used to suppress the energy storage unit from continuing to participate in high-power charging and discharging in the same direction.

[0088] According to the Health status of each energy storage unit and unit cycle loss cost Constructing economic wear and tear factors :

[0089]

[0090] in, For the first The economic wear factor of an energy storage unit; when the energy storage unit is in poor health or the unit cycle loss cost is high. Increase, used to reduce the power allocation priority of the energy storage unit.

[0091] According to the Available adjustable power of each energy storage unit SOC security potential function and economic wear factor Calculate the first The overall participation factor of each energy storage unit :

[0092]

[0093] in, For the first The overall participation factor of each energy storage unit For SOC security weights, The economic wear and tear weight is used to characterize the priority of energy storage units in participating in real-time power deviation compensation. The greater the SOC safety margin, the better the health status, the lower the unit cycle loss cost, and the greater the available adjustable power, the greater the comprehensive participation factor of the energy storage unit.

[0094] Construct a multi-energy storage comprehensive participation factor matrix based on the comprehensive participation factors of each energy storage unit. :

[0095]

[0096] in, It is used to characterize the priority of each energy storage unit in participating in real-time active power deviation compensation within the current control cycle, and to perform weighted correction on the benchmark active power droop coefficient matrix.

[0097] When the sum of the available adjustable power of all energy storage units is zero, it is determined that the multiple energy storage units do not have the active power adjustment capability in the current direction, and an insufficient energy storage adjustment capability flag is output.

[0098] This invention determines the safety margin of each energy storage unit's current state of charge (SOC) along the direction of the deviation corresponding to the current power regulation condition. Based on this safety margin, a SOC safety potential function is constructed. Energy storage units with SOCs close to the safety boundary automatically increase their potential function values ​​to suppress their continued participation in high-power charging and discharging in the same direction. Simultaneously, an economic wear factor is constructed based on the health status and unit cycle loss cost of each energy storage unit. Energy storage units with poor health or high unit cycle loss costs automatically increase their wear factor values ​​to reduce their power allocation priority. The available regulation power, SOC safety potential function, and economic wear factor of each energy storage unit are then comprehensively weighted to obtain a comprehensive participation factor. This comprehensive participation factor matrix is ​​then arranged to form a multi-energy storage comprehensive participation factor matrix. When the sum of the available regulation power of all energy storage units is zero, an insufficient regulation capability flag is output. Thus, the comprehensive participation factor comprehensively reflects the safety margin, economic wear degree, and available regulation capability of each energy storage unit under the current operating condition.

[0099] Specifically, in step S3, the power deviation is allocated to the second target power of each energy storage unit based on the droop coefficient, including:

[0100] Step S31: Based on the comprehensive participation factor of each energy storage unit, the droop coefficient of each energy storage unit is corrected to obtain the adaptive droop coefficient of each energy storage unit.

[0101] Step S32: Based on the adaptive droop coefficient of each energy storage unit, the power deviation is allocated to each energy storage unit to obtain the preliminary target power of each energy storage unit.

[0102] Step S33: Based on the charge safety potential function and economic wear factor of each energy storage unit, the preliminary target power is corrected to obtain the corrected second target power of each energy storage unit.

[0103] Specifically, in step S31, the adaptive droop coefficient of each energy storage unit is obtained, including:

[0104] Obtain the droop coefficient of each energy storage unit;

[0105] Using the comprehensive participation factor of each energy storage unit as a weight, the benchmark droop coefficient is weighted and corrected to obtain the adaptive droop coefficient of each energy storage unit.

[0106] Specifically, in step S33, the preliminary target power is corrected, including:

[0107] In response to the energy storage unit's charge safety potential function being greater than a preset safety threshold or its economic wear factor being greater than a preset wear threshold, the initial target power of the energy storage unit is reduced, and the amount of the reduction in the initial target power is transferred to other energy storage units that meet the safety constraints and online operating conditions.

[0108] In this embodiment of the invention, a reference active power droop coefficient is set for multiple energy storage units. and according to the first The overall participation factor of each energy storage unit Dynamically correct its active power droop coefficient:

[0109]

[0110] in, For the first The adaptive active power droop coefficient of the first energy storage unit in the current control cycle; the adaptive active power droop coefficient is used to characterize the first... The response strength of each energy storage unit to real-time active power deviation.

[0111] Based on the adaptive active power droop coefficient of each energy storage unit, the real-time active power deviation of the virtual power plant is allocated as follows: The second target power contribution of each energy storage unit :

[0112]

[0113] in, For the first The second target power contribution of each energy storage unit is obtained according to the adaptive droop control model; Indicates the first One energy storage unit discharges. Indicates the first Each energy storage unit is charged.

[0114] When the SOC safety potential function of each energy storage unit Greater than the preset safety potential threshold This reduces the adaptive active power droop coefficient of the energy storage unit; when the first Economic wear factor of an energy storage unit Greater than the preset wear threshold At that time, the adaptive active power droop coefficient of the energy storage unit is reduced; among which, Set according to the safe operation requirements of energy storage SOC It is set according to the requirements of economic operation of energy storage.

[0115] The power allocation amount reduced due to exceeding the SOC safety potential function limit or the economic wear factor limit will be transferred to the remaining energy storage units that meet the SOC safety constraints, power constraints and online operation conditions; if the remaining energy storage units cannot fully accept the power allocation amount, the unallocated power deviation will be retained as the remaining active power deviation.

[0116] When multiple energy storage units include different types of energy storage, the response correction coefficient is set according to the energy storage type. The comprehensive participation factor is then corrected based on the response correction coefficient to obtain the corrected comprehensive participation factor. :

[0117]

[0118] in, For the first The response correction coefficient for each energy storage unit For the first The revised comprehensive participation factor for each energy storage unit; when the rate of change of real-time active power deviation exceeds a preset rate of change threshold, the response correction coefficient of power-type energy storage units is increased; when the duration of real-time active power deviation exceeds a preset duration threshold, the response correction coefficient of energy-type energy storage units is increased; when the revised comprehensive participation factor is used... When using Alternative The active power droop coefficient is dynamically corrected.

[0119] This invention employs a weighted correction of the baseline droop coefficient based on the comprehensive participation factor of each energy storage unit. This allows energy storage units with larger comprehensive participation factors to receive smaller adaptive droop coefficients, thus assuming a larger proportion of power deviation allocation. Simultaneously, the initial target power is corrected based on the charge safety potential function and economic wear factor of each energy storage unit. When the charge safety potential function exceeds a preset safety threshold or the economic wear factor exceeds a preset wear threshold, the initial target power of that energy storage unit is reduced, and the reduction is transferred to other energy storage units that meet safety constraints and online operating conditions. This allows energy storage units with lower safety margins or heavier economic wear to automatically reduce their power load, thereby achieving precise power deviation allocation while ensuring both energy storage operation safety and economy. Furthermore, when multiple energy storage units contain different types of energy storage, a response correction coefficient is set according to the energy storage type. When the power deviation change rate is large, the response priority of power-type energy storage is increased to fully leverage its rapid response advantage.

[0120] Specifically, in step S4, the second target power is subjected to operational constraint verification, and the verified second target power is output as the charging and discharging command for each energy storage unit, including:

[0121] Step S41: Perform power limit verification on the second target power of each energy storage unit and limit the second target power within the range of the available adjustable power of each energy storage unit.

[0122] Step S42: Perform a state of charge boundary check on the second target power of each energy storage unit to ensure that after each energy storage unit executes the second target power, the state of charge of its next control cycle does not exceed the allowable upper and lower limits of the state of charge.

[0123] Step S43: Perform a charge / discharge state consistency check on the second target power of each energy storage unit, and prohibit the same energy storage unit from being in both charging and discharging states simultaneously within the same control cycle.

[0124] Step S44: The second target power that simultaneously passes the power limit verification, state of charge boundary verification, and charge / discharge state consistency verification is used as the charge / discharge command output for each energy storage unit.

[0125] Specifically, after step S44, the following steps are also included:

[0126] Calculate the remaining power deviation after allocation based on the actual power executed by each energy storage unit;

[0127] In response to the absolute value of the remaining power deviation being less than or equal to a preset deviation threshold, the charging and discharging power command of each energy storage unit and the remaining power deviation are output.

[0128] In response to the absolute value of the remaining power deviation being greater than a preset deviation threshold, the multi-energy storage integrated participation factor matrix is ​​corrected and the power is reallocated based on the deviation direction corresponding to the remaining power deviation and the available adjustable power of each energy storage unit that has not yet been called after this power allocation.

[0129] In this embodiment of the invention, for the first The second target power contribution of each energy storage unit Perform power limit verification to obtain the first Charge and discharge power commands for each energy storage unit :

[0130]

[0131] in, For the first The charging and discharging power commands for each energy storage unit. This is a saturation limiting function used to limit the amplitude of the first... The second target power contribution of each energy storage unit is limited to its available adjustable power range.

[0132] For the Each energy storage unit undergoes a State of Charge (SOC) boundary check to determine its state of charge (SOC) for the next control cycle. satisfy:

[0133]

[0134] in, For the first The state of charge of each energy storage unit in the next control cycle; when hour, Updated according to discharge efficiency; when hour, Updated according to charging efficiency.

[0135] For the Each energy storage unit undergoes a charge / discharge status check, prohibiting the same energy storage unit from being in both charging and discharging states simultaneously within the same control cycle, and ensuring that it meets the following requirements:

[0136]

[0137] in, For the first The charging state variables of each energy storage unit For the first Discharge state variables of each energy storage unit.

[0138] Step 4.4, based on the actual power output of each energy storage unit Calculate the remaining active power deviation after compensation. :

[0139]

[0140] in, For the first The actual operating power of each energy storage unit during the current control cycle. The remaining active power deviation after multi-energy storage coordination and compensation.

[0141] when When the deviation is not greater than the preset deviation threshold, it is determined that the grid-connected power deviation compensation requirement is met, and the charging and discharging power commands and remaining active power deviations of each energy storage unit are output; when When the deviation exceeds the preset threshold, the multi-energy storage integrated participation factor matrix is ​​corrected based on the direction of the remaining active power deviation and the remaining available adjustable power of each energy storage unit.

[0142] The method is executed cyclically according to a preset control cycle. Within each control cycle, the real-time active power deviation, the real-time control state vector of multiple energy storage units, the SOC safety potential function, the economic wear factor, the multi-energy storage comprehensive participation factor matrix, the adaptive active power droop coefficient, and the charge / discharge power command are updated sequentially. At the end of the current control cycle, based on the actual executed power of each energy storage unit, the SOC change, the health status change, and the cumulative cycle loss, the SOC safety potential function, economic wear factor, comprehensive participation factor, and active power droop coefficient for the next control cycle are updated. When the total available adjustable power of the multiple energy storage units is less than the absolute value of the real-time active power deviation, the maximum executable charge / discharge power of the multiple energy storage units is output according to the principle of prioritizing energy storage safety, and the uncompensated power deviation is calculated. When the grid-connected power corresponding to the uncompensated power deviation is higher than the active power command at the grid connection point, it is determined to be a power surplus direction and a new energy generation restriction command is output. When the grid-connected power corresponding to the uncompensated power deviation is lower than the active power command at the grid connection point, it is determined to be a power deficit direction and a grid-connected power deviation alarm or external power support demand is output.

[0143] This invention, through sequential power limit verification, state of charge boundary verification, and charge / discharge state consistency verification of the second target power of each energy storage unit, limits the second target power within the usable adjustable power range of each energy storage unit, ensures that the state of charge does not exceed the allowable upper and lower limits in the next control cycle after executing the second target power, and prohibits the simultaneous charging and discharging of the same energy storage unit in the same control cycle. This effectively avoids actual execution deviations caused by the second target power exceeding the physical capacity boundaries of energy storage or equipment malfunctions caused by charging / discharging state conflicts. Based on this, the remaining power deviation after allocation is calculated according to the actual executed power of each energy storage unit. When the absolute value of the remaining power deviation is not greater than a preset deviation threshold, an instruction and the remaining deviation are output; when it is greater than the preset deviation threshold, according to... The remaining deviation direction and the available adjustable power of each energy storage unit that has not yet been called are comprehensively included in the factor matrix and the power is redistributed, realizing closed-loop iterative correction of the power deviation that still exists after the first allocation. At the same time, it is executed cyclically according to the preset control cycle, and after the end of each cycle, the relevant parameters for the next cycle are updated according to the actual executed power, the change in state of charge, the change in health status, and the cumulative amount of cycle loss. This allows each control parameter to be dynamically adjusted with the change in energy storage status, thereby realizing continuous adaptive optimization of multi-energy storage coordinated control. In addition, when the total available adjustable power of all energy storage units is insufficient, the maximum executable power is output according to the principle of prioritizing energy storage safety and the uncompensated deviation is calculated. According to the deviation direction, the corresponding new energy generation restriction command or grid-connected power deviation alarm is output.

[0144] Specifically, it also includes:

[0145] When the state of charge of any energy storage unit is close to the safety boundary, the health status is lower than the preset threshold, or the unit cycle loss cost is higher than the preset threshold, the comprehensive participation factor of that energy storage unit is reduced, and the power that the energy storage unit could not allocate due to the reduced weight is transferred to other energy storage units that meet the operating constraints.

[0146] Specifically, it also includes:

[0147] After each control cycle, the charge safety potential function, economic wear factor, comprehensive participation factor and adaptive droop coefficient of each energy storage unit are updated; when the absolute value of the remaining power deviation exceeds the preset threshold, the output regulation capability is insufficient.

[0148] In this embodiment of the invention, during the execution of the control cycle, when the coordinating controller detects that the state of charge of any energy storage unit is close to its safe operating boundary, its health status has deteriorated to below a preset threshold, or its unit cycle loss cost is higher than a preset threshold, the coordinating controller reduces the comprehensive participation factor of that energy storage unit to actively reduce its power allocation weight in the current cycle and subsequent cycles. The power allocation that the energy storage unit cannot undertake due to the reduced weight is automatically transferred to other energy storage units that meet the state of charge safety boundary, power limit, and online operating conditions. This avoids the over-utilization of high-risk energy storage units and ensures the overall operational safety and balanced service life of the energy storage system.

[0149] Meanwhile, at the end of each control cycle, the coordination controller updates the charge safety potential function, economic wear factor, comprehensive participation factor, and adaptive droop coefficient of each energy storage unit based on the actual executed power, state of charge change, health status change, and cumulative cycle loss of each energy storage unit in the current cycle. This allows the above parameters to adaptively adjust with the dynamic changes in the state of the energy storage units, so as to accurately reflect the actual regulation capacity and participation priority of each energy storage unit in the next control cycle. When the calculated residual power deviation is greater than the preset deviation threshold, the coordination controller determines that the overall regulation capacity of the current multi-energy storage units is insufficient to meet the power deviation compensation requirements of the grid connection point, and outputs a regulation capacity insufficiency flag to indicate to the upper-level dispatch system of the virtual power plant that there is still a power deviation that has not been fully compensated in the current control cycle, providing a basis for the upper-level system to call up reserve capacity or adjust power commands.

[0150] This invention monitors the state of charge, health status, and unit cycle loss cost of each energy storage unit during the control cycle execution process. When the state of charge of any energy storage unit approaches a safety boundary, its health status falls below a preset threshold, or its unit cycle loss cost exceeds a preset threshold, its comprehensive participation factor is proactively reduced. The power allocation that the energy storage unit cannot undertake due to the reduced weight is automatically transferred to other energy storage units that meet the operational constraints. This achieves proactive protection of high-risk energy storage units and dynamic reallocation of power tasks, effectively preventing excessive utilization of high-risk energy storage units and ensuring the overall operational safety and usability of the energy storage system. The system uses lifetime balancing; simultaneously, at the end of each control cycle, it updates the charge safety potential function, economic wear factor, comprehensive participation factor, and adaptive droop coefficient of each energy storage unit based on the actual operating power, state of charge change, health status change, and cumulative cycle loss of each energy storage unit. This allows the above parameters to adaptively adjust with the dynamic changes in the state of the energy storage unit, and outputs an insufficient regulation capability flag when the remaining power deviation exceeds a preset threshold. This achieves adaptive linkage update between energy storage state changes and droop control parameters, and provides a clear state feedback signal to the upper-level system when the overall regulation capability of multiple energy storage units is insufficient.

[0151] This invention employs a virtual power plant model comprising distributed renewable energy sources, user loads, a grid connection interface, and four energy storage units to verify the effectiveness of the proposed virtual power plant multi-energy storage coordinated control method based on adaptive droop control in scenarios with dynamic changes in grid-connected power deviation. The virtual power plant tracks the active power command at the grid connection point and utilizes multiple energy storage units to undertake power deviation compensation tasks. Energy storage-side inputs include SOC, SOH, rated capacity, maximum charge / discharge power, upper and lower limits of SOC, unit cycle loss cost, and online operating status.

[0152] like Figure 1 As shown, the system first acquires the active power command at the grid connection point, the actual active power at the grid connection point, and the operating data of each energy storage unit. It then calculates the real-time active power deviation and determines the power regulation condition. Next, it forms a multi-energy storage integrated participation factor matrix based on the SOC safety distance, SOC safety potential function, economic wear factor, and available regulating power. Further, it corrects the active power droop coefficient of each energy storage unit based on this matrix and allocates the real-time power deviation as the second target power contribution of each energy storage unit. Finally, it verifies the power limit, SOC boundary, charging / discharging state, and remaining power deviation. If the constraints are met, it outputs the charging / discharging power command; otherwise, it corrects the integrated participation factor matrix and enters the next control cycle.

[0153] To evaluate the multi-energy storage coordinated control effect of the method of the present invention, this embodiment sets up four energy storage units ES1, ES2, ES3 and ES4, where ES1 is a lithium battery energy storage unit, ES2 is a flow battery energy storage unit, ES3 is a power-type energy storage unit, and ES4 is a cascaded battery energy storage unit. The rated capacities of the four energy storage units are set to 520kWh, 760kWh, 180kWh and 430kWh, respectively; the maximum charge and discharge powers are set to 180kW, 165kW, 230kW and 135kW, respectively; and the initial SOCs are set to 0.72, 0.56, 0.64 and 0.47, respectively.

[0154] Table 1

[0155]

[0156] As shown in Table 1, compared with the fixed ratio allocation method and the fixed droop control method, the method of the present invention has better performance in terms of maximum residual power deviation, average residual power deviation, SOC safety constraint, power limit constraint, loss sharing balance, dynamic response speed and utilization rate of available adjustment capacity. This indicates that the present invention can improve the grid-connected power tracking capability of virtual power plants and the coordinated control effect of multiple energy storage while ensuring the safe operation of energy storage.

[0157] Figure 2The diagram illustrates the input power deviation and power regulation condition discrimination. As shown, the active power command at the grid connection point remains at 1000kW. When the actual active power at the grid connection point is lower than the command value, the real-time active power deviation is positive, and the system enters a mild compensation, discharge compensation, or high deviation compensation mode. When the actual active power at the grid connection point is higher than the command value, the real-time active power deviation is negative, and the system enters a charging absorption mode. When the power deviation recovers to a small positive value, the system enters a correction tracking mode. This result demonstrates that the method of this invention can determine the charging and discharging control direction of multiple energy storage units based on the direction and amplitude of the grid connection power deviation, providing a basis for subsequent adaptive droop allocation.

[0158] Figure 3 The figure shows the dynamic response of the multi-energy storage adaptive droop control. As can be seen from the figure, during the discharge compensation phase, each energy storage unit outputs positive power to compensate for the grid-connected power deficit; during the charge absorption phase, each energy storage unit outputs negative power to absorb the grid-connected power surplus; during the correction tracking phase, each energy storage unit readjusts its power output and tends to stabilize. Because ES3 has a faster response speed, it has a faster dynamic response to power deviation changes; ES4, due to its relatively low health status and high economic wear level, bears less power but still participates in regulation. This result demonstrates that the method of this invention can achieve differentiated power sharing among multiple energy storage units based on their state differences.

[0159] Figure 4 The graph shows the remaining power deviation verification and SOC evolution. As can be seen from the graph, the total power of multiple energy storage systems can track the power deviation before compensation quite well. After compensation, the remaining power deviation remains near the allowable deviation range for most of the time, with only a short-term over-limit point appearing at the moment of power deviation step switching, and then gradually converging. Figure 4 The lower part shows that within a 60-minute operating window, the State of Charge (SOC) of each energy storage unit changes during discharge compensation, charge absorption, and corrective tracking processes, but overall remains within a typical safe SOC range. This result demonstrates that the method of this invention can compensate for grid-connected power deviations while also considering energy storage SOC safety constraints.

[0160] In summary, this embodiment demonstrates that the virtual power plant multi-energy storage coordinated control method based on adaptive droop control provided by this invention can adaptively adjust the active power droop coefficient of each energy storage unit according to the direction of grid-connected power deviation, energy storage SOC safety margin, health status, cycle loss cost, and available adjustment capability, thereby achieving coordinated power allocation among multiple energy storage units. Compared with fixed ratio allocation or fixed droop coefficient control methods, this invention is beneficial for improving the grid-connected power tracking capability of the virtual power plant, the energy storage SOC safety protection capability, the rationality of cycle loss sharing, and the collaborative response capability of heterogeneous energy storage.

[0161] The above embodiments are merely illustrative examples and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations. However, obvious variations or modifications derived therefrom are still within the scope of protection of this application.

Claims

1. A coordinated control method for multiple energy storage systems in a virtual power plant based on adaptive droop control, characterized in that, include: Step S1: Obtain the first target power, actual power, and operating status of each energy storage unit at the virtual power plant grid connection point; determine the power deviation based on the first target power and actual power; and determine the current power regulation condition based on the power deviation and the operating status. Step S2: Based on the current power regulation conditions, determine the safety margin, economic wear level, and available regulation power of each energy storage unit, and form a multi-energy storage comprehensive participation factor matrix based on the safety margin, economic wear level, and available regulation power. Step S3: Correct the droop coefficient of each energy storage unit according to the multi-energy storage integrated participation factor matrix, and allocate the power deviation as the second target power of each energy storage unit based on the droop coefficient. Step S4: Perform operational constraint verification on the second target power, and output the second target power that has passed the operational constraint verification as the charging and discharging command for each energy storage unit.

2. The method according to claim 1, characterized in that, In step S1, the current power regulation condition is determined based on the power deviation and the operating state, including: Step S11: Determine the power deviation characteristics of the current control cycle based on the direction and magnitude of the deviation between the first target power and the actual power at the virtual power plant grid connection point. Step S12: Collect the state of charge, health status, rated parameters, power limits, operating status and loss cost information of each energy storage unit to form a real-time control status information set for each energy storage unit. Step S13: Based on the deviation direction, extract the power limit and charge boundary corresponding to the deviation direction from the control state information set of each energy storage unit, and determine the available adjustable power of each energy storage unit under the current control direction. Step S14: Determine the current power regulation condition based on the deviation direction, deviation magnitude, and the cumulative sum of the available adjustable power of each energy storage unit.

3. The method according to claim 1, characterized in that, In step S2, a multi-energy storage integrated participation factor matrix is ​​formed, including: Step S21: Determine the safety margin of the current state of charge of each energy storage unit from the charge boundary along the deviation direction according to the deviation direction corresponding to the current power regulation condition. Step S22: Based on the safety margin of each energy storage unit, construct the charge safety potential function of each energy storage unit; Step S23: Based on the health status and unit cycle loss cost of each energy storage unit, construct the economic wear factor of each energy storage unit. Step S24: Perform a comprehensive weighted calculation on the available adjustable power, charge safety potential function and economic wear factor of each energy storage unit to obtain the comprehensive participation factor of each energy storage unit; Step S25: Arrange the comprehensive participation factors of each energy storage unit to form a multi-energy storage comprehensive participation factor matrix.

4. The method according to claim 1, characterized in that, In step S3, the power deviation is allocated to the second target power of each energy storage unit based on the droop coefficient, including: Step S31: Based on the comprehensive participation factor of each energy storage unit, the droop coefficient of each energy storage unit is corrected to obtain the adaptive droop coefficient of each energy storage unit. Step S32: Based on the adaptive droop coefficient of each energy storage unit, the power deviation is allocated to each energy storage unit to obtain the preliminary target power of each energy storage unit. Step S33: Based on the charge safety potential function and economic wear factor of each energy storage unit, the preliminary target power is corrected to obtain the corrected second target power of each energy storage unit.

5. The method according to claim 4, characterized in that, In step S31, the adaptive droop coefficient of each energy storage unit is obtained, including: Obtain the droop coefficient of each energy storage unit; Using the comprehensive participation factor of each energy storage unit as a weight, the benchmark droop coefficient is weighted and corrected to obtain the adaptive droop coefficient of each energy storage unit.

6. The method according to claim 4, characterized in that, In step S33, the preliminary target power is corrected, including: In response to the energy storage unit's charge safety potential function being greater than a preset safety threshold or its economic wear factor being greater than a preset wear threshold, the initial target power of the energy storage unit is reduced, and the amount of the reduction in the initial target power is transferred to other energy storage units that meet the safety constraints and online operating conditions.

7. The method according to claim 1, characterized in that, In step S4, the second target power is subjected to operational constraint verification, and the verified second target power is output as the charging and discharging command for each energy storage unit, including: Step S41: Perform power limit verification on the second target power of each energy storage unit and limit the second target power within the range of the available adjustable power of each energy storage unit. Step S42: Perform a state of charge boundary check on the second target power of each energy storage unit to ensure that after each energy storage unit executes the second target power, the state of charge of its next control cycle does not exceed the allowable upper and lower limits of the state of charge. Step S43: Perform a charge / discharge state consistency check on the second target power of each energy storage unit, and prohibit the same energy storage unit from being in both charging and discharging states simultaneously within the same control cycle. Step S44: The second target power that simultaneously passes the power limit verification, state of charge boundary verification, and charge / discharge state consistency verification is used as the charge / discharge command output for each energy storage unit.

8. The method according to claim 7, characterized in that, Following step S44, the following is also included: Calculate the remaining power deviation after allocation based on the actual power executed by each energy storage unit; In response to the absolute value of the remaining power deviation being less than or equal to a preset deviation threshold, the charging and discharging power command of each energy storage unit and the remaining power deviation are output. In response to the absolute value of the remaining power deviation being greater than a preset deviation threshold, the multi-energy storage integrated participation factor matrix is ​​corrected and the power is reallocated based on the deviation direction corresponding to the remaining power deviation and the available adjustable power of each energy storage unit that has not yet been called after this power allocation.

9. The method according to claim 1, characterized in that, Also includes: When the state of charge of any energy storage unit is close to the safety boundary, the health status is lower than the preset threshold, or the unit cycle loss cost is higher than the preset threshold, the comprehensive participation factor of that energy storage unit is reduced, and the power that the energy storage unit could not allocate due to the reduced weight is transferred to other energy storage units that meet the operating constraints.

10. The method according to claim 1, characterized in that, Also includes: After each control cycle, the charge safety potential function, economic wear factor, comprehensive participation factor and adaptive droop coefficient of each energy storage unit are updated; when the absolute value of the remaining power deviation exceeds the preset threshold, the output regulation capability is insufficient.

Images