An independent energy storage full life cycle collaborative scheduling method and system

Abstract

The application discloses an independent energy storage full life cycle collaborative scheduling method and system, relates to the technical field of energy storage optimal scheduling of power systems, and comprises the following steps: obtaining a current health state of energy storage, determining available power, available capacity and a remaining degradation budget of a current scheduling period; dividing the available power and the available capacity into guaranteed callable resources and conditionally callable resources, and constructing a hierarchical schedulable resource set; under the constraints of the hierarchical schedulable resource set and the remaining degradation budget, performing power service allocation and intraday calling; according to the deviation between an actual incremental degradation amount of the current period and a predicted value, feeding back and correcting the degradation budget of the next period, and rolling and reconstructing the scheduling resource boundary according to the updated health state; and the application solves the problems that in the prior independent energy storage scheduling, the available capacity does not match the actual realized capacity, the intraday calling does not sufficiently consider the remaining life cycle degradation constraints, and the degradation prediction deviation is difficult to feed back to the subsequent scheduling period.

Description

Technical Field

[0001] This invention relates to the field of power system energy storage optimization scheduling technology, and more specifically, to a method and system for collaborative scheduling of independent energy storage throughout its entire life cycle. Background Technology

[0002] With the continuous expansion of new energy power generation, independent energy storage, with its rapid bidirectional regulation capabilities, can participate in various power services such as electricity trading, frequency regulation, and new energy capacity leasing. Existing independent energy storage dispatching methods typically determine the dispatchability of energy storage based on rated power, rated capacity, state of charge, and health status, and formulate charging and discharging plans in conjunction with power service demands; some methods further consider battery cycle degradation or calendar degradation to reduce lifespan loss during energy storage operation.

[0003] However, as the energy storage lifecycle progresses, battery performance degradation and differences in battery cluster status can cause discrepancies between theoretically available capacity and actual deliverable capacity. Existing methods typically allocate resources across multiple services directly based on calculated available power and capacity, making it difficult to account for the varying reliability of resource allocation across different services. Furthermore, during intraday additional calls caused by random renewable energy output, if the call boundaries are primarily determined based on power, capacity, and state of charge, the impact of incremental degradation resulting from these additional calls on remaining lifecycle resources can easily be overlooked.

[0004] Furthermore, actual energy storage degradation is affected by actual operating conditions such as charge / discharge depth, rate, state of charge, and temperature. There may be discrepancies between the predicted degradation amount during the dispatch phase and the actual degradation amount. If subsequent dispatching still relies on the original degradation prediction results to determine the degradation budget and available capacity, it may easily lead to excessive consumption of degraded resources or overly conservative dispatching capabilities. Summary of the Invention

[0005] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide a method and system for coordinated scheduling of independent energy storage throughout its entire life cycle. By constructing a hierarchical resource coordinated scheduling and degradation deviation feedback reconstruction method oriented towards life cycle degradation, the present invention solves the problems of mismatch between available capacity and actual delivery capacity, insufficient consideration of remaining life cycle degradation constraints in intraday dispatch, and difficulty in feeding back degradation prediction deviations to subsequent scheduling cycles in existing independent energy storage scheduling.

[0006] To achieve the above objectives, the present invention provides the following technical solution: Firstly, this application provides a method for coordinated scheduling of independent energy storage throughout its entire lifecycle. This method includes: obtaining the current health status of the energy storage, determining the available power, available capacity, and remaining degradation budget for the current scheduling period; dividing the available power and available capacity into guaranteed callable resources and conditionally callable resources, constructing a hierarchical set of callable resources; under the constraints of the hierarchical set of callable resources and the remaining degradation budget, performing power service allocation and intraday dispatch, wherein the upper limit of intraday dispatch power is determined by the change in state of charge and incremental degradation caused by the dispatch; based on the deviation between the actual incremental degradation and the predicted value for the current period, correcting the degradation budget for the next period, and collaboratively reconstructing the scheduling resource boundaries based on the updated health status.

[0007] In one embodiment, obtaining the current health status of energy storage includes: synchronizing and preprocessing battery monitoring data and environmental monitoring data during historical operation to obtain an effective operating dataset; based on the effective operating dataset, calculating the cumulative cycle degradation caused by charge-discharge cycles and the cumulative calendar degradation caused by time aging, respectively, superimposing them to correct the initial health status, and obtaining the current health status value; and determining the battery temperature, ambient temperature, and state of charge range at the current moment as the current environmental operating parameters.

[0008] In one embodiment, determining the available power, available capacity, and remaining degradation budget for the current scheduling period includes: adjusting the initial rated capacity based on the current health status and determining the effective capacity and charge / discharge capacity by combining the state of charge boundary; determining the allowable charge / discharge power on the battery side based on the effective capacity, the current state of charge, and the battery temperature, and comparing it with the allowable power on the converter side, taking the smaller value as the available charge / discharge power; comparing the maximum charge / discharge energy corresponding to the available charge / discharge power with the charge / discharge capacity respectively, taking the smaller value as the available charge / discharge capacity; obtaining the historical cumulative degradation amount and the end-of-life degradation limit, using the difference between the two as the remaining degradation amount, and allocating it according to the proportion of the current scheduling period to the expected remaining running time to obtain the remaining degradation budget for the current scheduling period.

[0009] In one embodiment, the available power and available capacity are divided into guaranteed callable resources and conditionally callable resources, including: acquiring the state parameters of each battery cluster and determining the capacity dispersion of the battery cluster; determining the prediction deviation boundary based on the deviation between the theoretical available capacity and the actual realized capacity in the historical scheduling cycle; deducting the corresponding margin from the available power and available capacity based on the capacity dispersion and the prediction deviation boundary to obtain the guaranteed callable resources; determining the difference between the available power and available capacity and the guaranteed callable resources as conditionally callable resources, and releasing the conditionally callable resources only when the real-time state meets preset conditions.

[0010] In one embodiment, power service allocation includes: converting power trading demand, frequency regulation demand, and renewable energy capacity leasing demand into corresponding power demand and capacity demand, respectively; determining the frequency regulation demand and renewable energy capacity leasing demand as guaranteed resource demand, and determining the power trading demand as adjustable resource demand; prioritizing the allocation of guaranteed callable resources to the guaranteed resource demand, and allocating the remaining guaranteed callable resources after deducting the allocated resources, as well as conditionally callable resources, to the adjustable resource demand; calculating the expected degradation consumption corresponding to each service allocation, and if the total expected degradation consumption exceeds the remaining degradation budget, then sequentially reducing the resource allocation of the corresponding service in ascending order of unit degradation benefit, until the remaining degradation budget constraint is met.

[0011] In one embodiment, intraday dispatch includes: for each scheduling period of each random scenario of renewable energy output, firstly, using the renewable energy capacity leasing resources reserved in the previous day to compensate for the renewable energy output deviation of that period, and constructing multiple candidate additional dispatch power for the remaining deviation demand; calculating the incremental degradation amount corresponding to each candidate dispatch power, and based on the free degradation margin after deducting the minimum degradation amount required for subsequent committed services from the current remaining degradation budget, screening candidate dispatch power whose incremental degradation amount does not exceed the free degradation margin, and determining the safe dispatch power upper limit in combination with state of charge constraints and temperature constraints; and taking the smaller value between the remaining deviation demand and the safe dispatch power upper limit as the actual scenario dispatch power for that period.

[0012] In one embodiment, intraday calling further includes: updating the remaining degradation budget based on the actual incremental degradation amount generated by the actual scenario calling power, and updating the health status and effective capacity; based on the updated health status and effective capacity, recalculating the available power and available capacity for the next scheduling period, and re-dividing guaranteed callable resources and conditionally callable resources to form a hierarchical set of schedulable resources for the next scheduling period.

[0013] In one embodiment, intraday calling further includes: calculating the remaining margin in the discharge direction relative to the upper limit of the allowable state of charge and the remaining margin in the charging direction relative to the upper limit of the allowable state of charge, respectively, to independently determine the risk of exceeding the state of charge limit from both the charging and discharging directions; determining the life cycle safety margin based on the expected cumulative degradation amount after the calling and the maximum allowable cumulative degradation amount determined based on the lifespan termination condition; when the actual state of charge in each scheduling period is within the allowable range and the life cycle safety margin is not less than zero, it is determined to be a safe calling scenario; otherwise, it is determined to be a calling over-limit scenario.

[0014] In one embodiment, based on the deviation between the actual incremental degradation amount and the predicted value in the current period, the degradation budget for the next period is corrected, and the scheduling resource boundary is reconstructed in a rolling manner with the updated health status. This includes: determining the degradation budget compensation coefficient for the next scheduling period based on the deviation between the actual incremental degradation amount and the predicted baseline value in the current scheduling period, and correcting the basic degradation budget using the compensation coefficient; updating the health status based on the actual incremental degradation amount in the current scheduling period, and using the corrected remaining degradation budget and the updated health status together to reconstruct the available capacity for the next scheduling period, so that the actual degradation result of the current scheduling period is fed back to the resource boundary of the subsequent scheduling period, realizing cross-period closed-loop update.

[0015] Secondly, this application provides an independent energy storage full lifecycle collaborative scheduling system, which includes: a lifecycle availability capacity determination module, used to obtain the current health status of energy storage and determine the available power, available capacity, and remaining degradation budget for the current scheduling cycle; a schedulable resource trust layering module, used to divide the available power and available capacity into guaranteed callable resources and conditionally callable resources, and construct a layered schedulable resource set; a multi-service collaborative scheduling and degradation constraint calling module, used to perform power service allocation and intraday calling under the constraints of the layered schedulable resource set and the remaining degradation budget, wherein the upper limit of intraday calling power is determined by the change in state of charge and incremental degradation caused by the calling; and a degradation deviation feedback and resource boundary reconstruction module, used to correct the degradation budget for the next cycle based on the deviation between the actual incremental degradation and the predicted value of the current cycle, and collaboratively reconstruct the scheduling resource boundary with the updated health status.

[0016] As can be seen from the above technical solutions, the embodiments of this application have the following advantages: By linking energy storage health status, available power, available capacity, and remaining degradation budget, and classifying dispatchable resources into guaranteed callable resources and conditionally callable resources based on actual resource availability, differentiated utilization of energy storage resources with varying reliability levels can be achieved. Simultaneously, during the coordinated allocation of multiple power services and intraday dispatch, changes in state of charge and incremental degradation are used together as the basis for determining the dispatch power boundary, preventing short-term over-dispatch from adversely affecting the remaining lifespan. Furthermore, the deviation between actual incremental degradation and predicted values ​​is used to correct the degradation budget for the next dispatch cycle, and the dispatch resource boundary is reconstructed on a rolling basis in conjunction with the updated health status. This allows energy storage dispatch capability to continuously adjust with actual degradation status, reducing the deviation between theoretical available capacity and actual availability. While ensuring the safety of the energy storage lifespan, this approach improves energy storage resource utilization and the reliability and adaptability of coordinated dispatch of multiple power services. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of a collaborative scheduling method for the entire life cycle of independent energy storage, provided as an embodiment of this application.

[0019] Figure 2 This is a schematic diagram of an independent energy storage full life cycle collaborative scheduling system provided in an embodiment of this application.

[0020] Figure 3 This is a schematic diagram of the capacity degradation fitting curves under different battery operating temperatures provided in the embodiments of this application.

[0021] Figure 4 A schematic diagram illustrating the changes in the health status of independent energy storage during its entire life cycle, as provided in this application embodiment.

[0022] Figure 5 This is a schematic diagram illustrating the change in marginal degradation intensity corresponding to the candidate additional call power provided in the embodiments of this application. Detailed Implementation

[0023] To enable those skilled in the art to better understand the technical solutions in this application, the technical solutions in the embodiments of this application will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0024] Reference Figure 1 As shown in the diagram, the present invention provides a flowchart of a collaborative scheduling method for the entire lifecycle of independent energy storage, which includes the following steps: S1: Obtain the current lifecycle health status and environmental operating parameters of the independent energy storage.

[0025] In this embodiment, the current lifecycle health status and environmental operating parameters of the independent energy storage are obtained, including: S11. According to the preset sampling period, acquire the battery operation monitoring data and environmental monitoring data of independent energy storage during the historical operation period before the current scheduling time, and record the acquisition time corresponding to each monitoring data. The battery operation monitoring data includes state of charge, terminal voltage, charging and discharging current, charging and discharging power, battery temperature, cumulative charging and discharging amount and cumulative running time. The environmental monitoring data includes ambient temperature and ambient humidity. The preset sampling period is pre-set based on the data acquisition frequency of the independent energy storage battery management system and the environmental monitoring equipment, specifically taking the common sampling time interval at which each monitoring parameter can be stably obtained.

[0026] S12, based on the collection time corresponding to the battery operation monitoring data and environmental monitoring data, using the time node corresponding to the preset sampling period as the reference time node, the battery operation monitoring data and environmental monitoring data whose time deviation between the collection time and the reference time node is not greater than the preset synchronization threshold are associated with the same reference time node to obtain synchronized operation data arranged in chronological order; The preset synchronization threshold is determined based on a preset sampling period and is used to limit the maximum allowable time deviation of data collected by different monitoring devices belonging to the same reference time node. For example, the preset synchronization threshold is set to no more than half of the preset sampling period.

[0027] S13, based on the synchronous operation data, data that exceeds the allowed operating range of the corresponding device is identified as abnormal data, and data that does not have a corresponding sample value is identified as missing data; for missing data with a consecutive number of missing values ​​not greater than a preset missing threshold, interpolation is performed to complete the missing data based on adjacent valid sample values; for data with a consecutive number of missing values ​​greater than the preset missing threshold and the abnormal data, the missing data is removed, and the remaining data is rearranged according to the reference time node to obtain a valid operating dataset. The preset missing threshold is determined based on the maximum consecutive missing duration allowed to be filled by interpolation using adjacent valid sample values, specifically the number of consecutive missing sample points obtained by rounding down the ratio of the maximum consecutive missing duration to the preset sampling period.

[0028] S14, Based on the effective operating dataset, identify the charging and discharging processes before the start of the current scheduling cycle according to the continuous change of the state of charge over time, and combine adjacent charging and discharging processes into a single charging and discharging process. The depth of charge and discharge is determined by the difference between the maximum and minimum values ​​of the state of charge during each charge and discharge process. The charge and discharge rate is determined by the average charge and discharge current and the corresponding effective battery capacity during the charge and discharge process. The number of historical equivalent cycles is determined by the depth of charge and discharge corresponding to each charge and discharge process. The specific formula for calculating the historical equivalent loop count is as follows:

[0029] In the formula, For the historical equivalent number of iterations, Depth of charge / discharge, This represents the number of charging and discharging processes identified up to the start of the current scheduling cycle.

[0030] S15, based on the depth of charge and discharge and the charge and discharge rate corresponding to each charge and discharge process, and combined with the average battery temperature corresponding to each charge and discharge process, calculate the cycle degradation amount generated by each charge and discharge process. The cycle degradation amount is characterized by the capacity loss ratio relative to the initial rated capacity of the independent energy storage. The cycle degradation amounts corresponding to each charge and discharge process before the start time of the current scheduling cycle are accumulated to obtain the historical cumulative cycle degradation amount. The specific formula for calculating the cyclic degradation amount is as follows:

[0031] In the formula, Let $\frac{j}{j}$ be the amount of cyclic degradation generated during the $j$-th charge-discharge process. The cycle degradation factor under baseline operating conditions refers to the proportion of baseline capacity loss relative to the initial rated capacity of independent energy storage under a unit equivalent cycle. This is a depth of charge / discharge correction function. This is the charge / discharge rate correction function. This is a battery temperature correction function. This refers to the charge / discharge rate. This represents the average battery temperature.

[0032] The cycle degradation coefficient is determined based on the capacity detection results and equivalent cycle statistics during the historical operation of independent energy storage. Specifically, it is the ratio of the capacity decay ratio between two adjacent capacity detections to the cumulative number of equivalent cycles during that period.

[0033] In one specific implementation, the depth of charge / discharge correction function can be expressed as:

[0034] In the formula, The charge / discharge depth degradation sensitivity coefficient is obtained by keeping the charge / discharge rate and operating temperature as reference values, changing the charge / discharge depth to obtain the cyclic degradation amount at different charge / discharge depths, and then determining the relationship between the cyclic degradation amount and the charge / discharge depth by curve fitting according to the charge / discharge depth correction function.

[0035] The charge / discharge rate correction function can be expressed as:

[0036] In the formula, This is the scaling factor degradation sensitivity coefficient. Using the charge / discharge rate as a reference, the rate degradation sensitivity coefficient is obtained by keeping the charge / discharge depth and operating temperature as reference values, changing the charge / discharge rate to obtain the cyclic degradation amount under different charge / discharge rates, and then determining the relationship between the cyclic degradation amount and the charge / discharge rate by linear fitting according to the charge / discharge rate correction function.

[0037] The temperature correction function can be in exponential form:

[0038] In the formula, This is the temperature degradation sensitivity coefficient. The temperature degradation sensitivity coefficient is determined by keeping the depth of charge and discharge and the charge / discharge rate as reference values, changing the battery operating temperature to obtain the amount of cycle degradation at different operating temperatures, and performing an exponential fit on the relationship between the amount of cycle degradation and the operating temperature according to the temperature correction function. The reference temperature is the average value of the battery temperature in the historical valid operating data.

[0039] like Figure 3 The figure shows a schematic diagram of the capacity degradation fitting curves under different battery operating temperatures in this embodiment. With the increase of charge / discharge depth, the capacity loss per unit cycle exhibits a non-linear growth trend. Under the same charge / discharge depth conditions, the higher the operating temperature, the faster the capacity degradation rate, indicating that battery temperature has a significant impact on cycle degradation. This fitting result reflects the coupling effect of charge / discharge depth and temperature on cycle degradation, and can serve as the basis for subsequent lifecycle health state calculations, degradation budget allocation, and incremental degradation calculations during collaborative scheduling.

[0040] S16. Based on the cumulative runtime, state of charge, and battery temperature in the effective operating dataset, calculate the calendar degradation amount corresponding to each historical operating segment. The calendar degradation amount is characterized by the capacity loss ratio relative to the initial rated capacity of the independent energy storage. The calendar degradation amounts corresponding to each historical operating segment are accumulated to obtain the historical cumulative calendar degradation amount up to the start time of the current scheduling cycle. The specific formula for calculating the calendar degradation amount is as follows:

[0041] In the formula, This represents the calendar degradation amount corresponding to the i-th historical runtime segment. This represents the percentage of baseline capacity loss relative to the initial rated capacity per unit time. For SOC correction function, This is a calendar degradation temperature correction function. The duration of the i-th runtime segment.

[0042] The calendar degradation rate is determined based on the capacity detection results during the historical operation of the independent energy storage, specifically the ratio of the capacity decay rate after deducting the cyclic degradation amount between two adjacent capacity detections to the corresponding operating time.

[0043] In one specific implementation, the SOC correction function is expressed as:

[0044] In the formula, The coefficient representing the impact of SOC on calendar degradation. The reference state of charge is the average value of the state of charge in historical valid operating data, and the reference temperature is the average value of the battery temperature in historical valid operating data.

[0045] The influence coefficient of SOC on calendar degradation is determined by using linear regression to fit the relationship between the calendar degradation rate and the deviation of the state of charge from the baseline state of charge in the historical operation data of independent energy storage, based on the calendar degradation rate corresponding to different state of charge intervals.

[0046] The calendar degradation temperature correction function is expressed as:

[0047] In the formula, The calendar degradation temperature sensitivity coefficient is determined by using exponential regression to fit the relationship between the calendar degradation rate and the change of battery temperature deviating from the reference temperature, based on the calendar degradation rate corresponding to different battery temperature ranges in the historical operation data of independent energy storage.

[0048] S17. Based on the cumulative cyclic degradation amount and the cumulative calendar degradation amount, determine the historical cumulative degradation amount of the independent energy storage up to the start time of the current scheduling cycle, and correct the initial health state of the independent energy storage according to the cumulative degradation amount to obtain the current health state value. The current health state value, the cumulative cyclic degradation amount and the cumulative calendar degradation amount are used together as the current life cycle health state. The specific formula for calculating the historical cumulative degradation amount is as follows:

[0049] In the formula, Historical cumulative degradation refers to the cumulative degree of battery performance degradation caused by charge-discharge cycles and aging over time from the time an independent energy storage system was put into operation until the start of the current dispatch cycle. For cumulative cyclic degradation, This represents the cumulative calendar degradation.

[0050] Further determine the current life cycle health status (SOH) based on historical cumulative degradation:

[0051] In the formula, This represents the current lifecycle health status value. The initial health status value for independent energy storage to be put into operation.

[0052] like Figure 4 The diagram illustrates the changes in the state of health (SOH) of independent energy storage throughout its entire lifecycle in this embodiment. As the cumulative number of cycles increases, the SOH shows a continuous downward trend. In the initial stage of operation, capacity decay is relatively slow; after entering the stable operation phase, the SOH decreases approximately linearly. However, in the later stages of the lifecycle, due to the combined cumulative effect of cycle degradation and calendar degradation, the rate of SOH decline accelerates further, gradually approaching the end-of-life threshold. This trend demonstrates that the present invention, by using both cycle degradation and calendar degradation to calculate the SOH, can accurately reflect the capacity decay process throughout the entire lifecycle of energy storage, providing a basis for the dynamic determination of subsequent available power, available capacity, and degradation budget.

[0053] S18. Based on the effective operating dataset, determine the battery temperature, ambient temperature, and ambient humidity corresponding to the current scheduling time, and determine the charge / discharge rate range and state of charge range of the independent energy storage based on the charge / discharge rate and the current state of charge. Use the battery temperature, ambient temperature, ambient humidity, charge / discharge rate range, and state of charge range together as the current environmental operating parameters. S19, associate the current life cycle health status with the current environmental operating parameters according to the current scheduling time to form an independent energy storage current life cycle status parameter set, and use the current life cycle status parameter set as the input for determining the available power, available capacity and remaining degradation budget corresponding to the current life cycle stage in S2.

[0054] S2, based on the health status and environmental operating parameters, determine the available power, available capacity and remaining degradation budget corresponding to the current life cycle stage.

[0055] In this embodiment, determining the available power, available capacity, and remaining degradation budget corresponding to the current lifecycle stage based on the health status and environmental operating parameters includes: S21, the effective capacity at the start of the current scheduling cycle is determined based on the product of the current health status value obtained in S1 and the initial rated capacity of the independent energy storage. Based on the current state of charge, the upper limit of the allowable state of charge, the lower limit of the allowable state of charge, and the effective capacity, the rechargeable capacity and the dischargeable capacity corresponding to the start of the current scheduling cycle are determined respectively. The upper limit of the allowable state of charge and the lower limit of the allowable state of charge are determined according to the charge and discharge protection boundaries configured by the independent energy storage battery management system. The effective capacity is calculated using the following formula:

[0056] In the formula, Effective capacity refers to the maximum electrical energy that an independent energy storage system can actually store under current healthy conditions, after capacity decay correction relative to its initial rated capacity. This is the initial rated capacity.

[0057] The specific formula for calculating the rechargeable capacity is as follows:

[0058] The specific formula for calculating the discharge capacity is as follows:

[0059] In the formula, For rechargeable capacity, Discharge capacity, The upper limit of allowed states of charge configured for the BMS. The limit of the allowed charge state configured for the BMS.

[0060] S22, based on the effective capacity obtained in S21, and according to the current health status value, current state of charge and battery temperature obtained in S1, determine the maximum allowable charging rate and maximum allowable discharging rate corresponding to the current health status value, current state of charge and battery temperature from the charging and discharging capacity parameters stored in the independent energy storage battery management system, and multiply the effective capacity by the maximum allowable charging rate and maximum allowable discharging rate respectively to obtain the battery-side allowable charging power and battery-side allowable discharging power in the current state; The allowable charging power on the battery side is calculated using the following formula:

[0061] The allowable discharge power on the battery side is calculated using the following formula:

[0062] In the formula, The allowed charging power on the battery side, This refers to the allowable discharge power on the battery side. The maximum allowable charging rate, This represents the maximum permissible discharge rate.

[0063] S23, Based on the battery-side allowable charging power and battery-side allowable discharging power obtained in S22, compare them with the maximum allowable charging power and maximum allowable discharging power of the independent energy storage converter, respectively, and determine the smaller value between the battery-side allowable charging power and the converter's maximum allowable charging power as the available charging power for the current scheduling cycle, and determine the smaller value between the battery-side allowable discharging power and the converter's maximum allowable discharging power as the available discharging power for the current scheduling cycle; S24, based on the rechargeable capacity and dischargeable capacity obtained in S21 and the available charging power and available discharging power obtained in S23, calculate the maximum charging energy corresponding to the available charging power and the maximum discharging energy corresponding to the available discharging power according to the duration of the current scheduling cycle, determine the smaller value between the rechargeable capacity and the maximum charging energy as the available charging capacity of the current scheduling cycle, and determine the smaller value between the dischargeable capacity and the maximum discharging energy as the available discharging capacity of the current scheduling cycle; The maximum charging energy corresponding to the available charging power is calculated using the following formula:

[0064] The maximum discharge energy corresponding to the available discharge power is calculated using the following formula:

[0065] In the formula, This represents the maximum charging energy corresponding to the available charging power. This represents the maximum discharge energy corresponding to the available discharge power. Available charging power, The available discharge power, For charging efficiency, For discharge efficiency, The duration of the scheduling cycle.

[0066] S25, obtain the historical cumulative degradation amount, and obtain the life-end degradation limit corresponding to the independent energy storage reaching the end of its lifespan. Determine the non-negative difference between the life-end degradation limit and the historical cumulative degradation amount as the remaining degradation amount in the current remaining lifespan of the independent energy storage. The life-end degradation limit is determined based on the difference between the life-end health state and the initial health state stored in the independent energy storage battery management system. S26. Based on the ratio between the historical cumulative degradation amount obtained in S25 and the cumulative runtime obtained in S1, determine the historical unit time degradation rate of independent energy storage up to the start of the current scheduling cycle, and determine the expected remaining runtime according to the ratio of the remaining degradation amount to the historical unit time degradation rate. Then, allocate the remaining degradation amount according to the proportion of the current scheduling cycle duration to the expected remaining runtime to obtain the remaining degradation budget that can be consumed in the current scheduling cycle. The remaining degradation budget is calculated using the following formula:

[0067] In the formula, The remaining degradation budget allowed to be consumed in the current scheduling cycle. This represents the amount of degradation over the remaining lifespan. This represents the estimated remaining runtime.

[0068] S27. Based on the available charging power and available discharging power obtained in S23, the available charging capacity and available discharging capacity obtained in S24, and the remaining degradation budget obtained in S26, a set of schedulable resources corresponding to the current scheduling cycle is formed, and the set of schedulable resources is used as a constraint boundary for joint resource allocation among the demand for electricity trading, frequency regulation and new energy capacity leasing.

[0069] It should be noted that when the historical cumulative degradation amount is greater than zero, the historical degradation rate per unit time is determined based on the ratio of the historical cumulative degradation amount to the cumulative running time; when the historical cumulative degradation amount is zero or the historical valid running data is insufficient to calculate the degradation rate, the degradation rate per unit time corresponding to the historical running data of the same battery type as the independent energy storage is used as the current degradation rate per unit time.

[0070] In this embodiment, the set of schedulable resources obtained after processing in S27 is the theoretical available capacity for the current scheduling cycle, determined based on the overall health status, state of charge, environmental operating parameters, and equipment operating boundaries of the independent energy storage system. However, independent energy storage typically consists of multiple battery clusters connected in parallel. Different battery clusters, during long-term operation, are affected by variations in charge / discharge cycles, operating temperature, and aging levels, resulting in varying degrees of dispersion in their state of charge, health status, internal resistance, and terminal voltage. This limits the actual redeemable capacity of the energy storage system to battery clusters with significantly deviated states. Furthermore, due to deviations in health status estimation, operating parameter measurement, and capacity calculation, the theoretical available power and capacity determined in S27 may differ from the power and capacity that can be stably redeemed during historical actual deployments. Therefore, directly allocating all schedulable resources obtained in S27 as deterministic resources to services such as electricity trading, frequency regulation, and new energy capacity leasing may result in a situation where the committed resource amount exceeds the actual redeemable capacity. Based on this, after obtaining the set of schedulable resources in S27, this embodiment further combines the degree of dispersion of battery cluster status and historical capability fulfillment deviation to classify the schedulable resources by reliability, so as to distinguish between guaranteed callable resources and conditionally callable resources.

[0071] S28, based on the current state parameters of each independent energy storage battery cluster and the deviation between available capacity and actual fulfillment capacity during historical scheduling, the set of schedulable resources is hierarchically divided into layers, forming a hierarchical set of schedulable resources that includes guaranteed callable resources and conditionally callable resources, specifically including: S281, obtain the state parameters corresponding to each independent energy storage battery cluster at the start of the current scheduling cycle, including state of charge, health status, battery temperature, DC internal resistance and terminal voltage, and associate each state parameter according to the battery cluster number to form a battery cluster state parameter set characterizing the current operating state of each battery cluster. S282, based on the battery cluster state parameter set, calculate the deviation of each battery cluster's state of charge, state of health, battery temperature, DC internal resistance, and terminal voltage from the statistical center value of the corresponding parameters of all battery clusters, i.e., the difference. Then, normalize the deviation of each state parameter according to the ratio of the relative deviation of each state parameter to the maximum relative deviation of the corresponding state parameter in all battery clusters to obtain the normalized state deviation of each battery cluster. The average value of the normalized state deviations corresponding to the same battery cluster is determined as the capacity deviation index of the battery cluster, and the maximum value of the capacity deviation index of all battery clusters is determined as the capacity dispersion of the battery cluster in the current scheduling cycle. S283: Based on the dispersion of battery cluster capacity, obtain the historical dispersion of battery cluster capacity obtained in the same way as S281 and S282 for each historical scheduling period before the current scheduling period, and sort them in ascending order according to the difference between the historical battery cluster capacity dispersion and the current battery cluster capacity dispersion. Select the top-ranked historical scheduling periods as similar historical scheduling periods. Calculate the non-negative differences between the theoretical available charging power, theoretical available discharging power, theoretical available charging capacity, and theoretical available discharging capacity and the corresponding actual realized charging power, discharging power, charging capacity, and discharging capacity in each similar historical scheduling period. Obtain a historical capacity realization deviation set including the charging power realization deviation set, the discharging power realization deviation set, the charging capacity realization deviation set, and the discharging capacity realization deviation set. S284, based on each set of capability fulfillment deviations, arrange the fulfillment deviations in each set in ascending order, and determine the quantile position according to the target fulfillment probability corresponding to the subsequent energy storage service. The fulfillment deviations located at the quantile position in each set of capability fulfillment deviations are respectively determined as the charging power prediction deviation boundary, the discharging power prediction deviation boundary, the charging capacity prediction deviation boundary, and the discharging capacity prediction deviation boundary. S285, based on the capability prediction deviation boundaries and combined with the current battery cluster capability dispersion obtained in S282, determine the charging power uncertainty margin, discharging power uncertainty margin, charging capacity uncertainty margin and discharging capacity uncertainty margin for the current scheduling cycle, respectively. Each uncertainty margin is determined by the sum of the corresponding capability prediction deviation boundary and the capability additional deduction caused by the current battery cluster capability dispersion. The capability additional deduction is determined by the product of the current battery cluster capability dispersion and the available power or available capacity corresponding to S27. S286, based on the various uncertainty margins obtained in S285, subtract the corresponding uncertainty margins from the available charging power, available discharging power, available charging capacity and available discharging capacity obtained in S27 respectively, and determine the larger value between the subtraction result and zero as the guaranteed callable charging power, guaranteed callable discharging power, guaranteed callable charging capacity and guaranteed callable discharging capacity respectively, forming the guaranteed callable resource set for the current scheduling period; S287, based on the guaranteed callable resource set obtained in S286, calculate the non-negative difference between the available charging power, available discharging power, available charging capacity, and available discharging capacity obtained in S27 and the corresponding guaranteed callable resources, respectively, and determine the obtained difference as conditional callable charging power, conditional callable discharging power, conditional callable charging capacity, and conditional callable discharging capacity, respectively, and associate the conditional callable resources with the corresponding real-time release conditions to form a conditional callable resource set; S288: Based on the set of conditionally callable resources, during the actual call process, the real-time state of charge (SOC), real-time battery temperature, and actual charging / discharging power of each battery cluster are obtained. The real-time SOC is compared with the upper and lower limits of the allowable SOC set by the battery management system, and the real-time battery temperature is compared with the upper limit of the allowable operating temperature set by the battery management system. The deviation between the actual charging / discharging power and the current call power is calculated. When the real-time SOC of each battery cluster is within the allowable SOC range, the real-time battery temperature does not exceed the upper limit of the allowable operating temperature, and the deviation between the actual charging / discharging power and the current call power does not exceed the corresponding power prediction deviation boundary obtained in S284, the corresponding conditionally callable resources are released; otherwise, the release of the conditionally callable resources is stopped. S289: Based on the guaranteed callable resource set obtained in S286, the conditional callable resource set obtained in S287, and the real-time release status of the conditional callable resources obtained in S288, and combined with the remaining degradation budget, a hierarchical schedulable resource set is formed, including guaranteed callable power, guaranteed callable capacity, conditional callable power, conditional callable capacity, conditional resource release status, and remaining degradation budget. The hierarchical schedulable resource set is then used as the input for joint resource allocation of subsequent electricity trading demand, frequency regulation demand, and new energy capacity leasing demand.

[0072] It should be noted that by simultaneously considering the dispersion of the current state parameters of each battery cluster in independent energy storage and the deviation between the historical theoretical available capacity and the actual realized capacity, the reliability of the theoretically schedulable resources obtained in S27 can be further assessed. This avoids determining the available capacity solely based on the overall health status and operational boundaries of energy storage while ignoring the actual capacity limitations caused by the inconsistency of battery clusters. Furthermore, by selecting historical scheduling cycles with a similar dispersion in the current battery cluster capacity to determine the capacity prediction deviation boundary and forming a dynamic uncertainty margin, the resource reliability evaluation can be adapted to the current actual operating state. The schedulable resources are further divided into guaranteed callable resources and conditionally callable resources. The release of conditionally callable resources is dynamically controlled based on real-time state of charge, battery temperature, and power realization deviation. This transforms the original single theoretical available resource boundary into resource boundaries with different callability reliability levels. This reduces the risk of over-commitment and under-fulfillment of resources in energy trading, frequency regulation, and new energy capacity leasing, while avoiding waste of available energy storage resources due to uniform conservative deductions. This improves the reliability and resource utilization of multi-scenario collaborative scheduling of independent energy storage.

[0073] S3, based on the electricity trading demand, frequency regulation demand, and new energy capacity leasing demand, jointly allocate the available power, available capacity, and remaining degradation budget among different regulation demands to obtain a day-ahead reservation scheme, including: S31, obtain the electricity trading plan, frequency regulation demand, and new energy capacity leasing demand within the day-ahead scheduling cycle, divide the day-ahead scheduling cycle into multiple scheduling periods according to the same time interval, and assign the electricity trading plan, frequency regulation demand, and new energy capacity leasing demand to each scheduling period; extract the planned charging and discharging power, planned trading volume, and trading price corresponding to electricity trading in each scheduling period, the frequency regulation power demand, frequency regulation duration, and frequency regulation compensation price corresponding to frequency regulation, and the leasing power, leasing capacity, leasing duration, and capacity leasing price corresponding to new energy capacity leasing, to form a multi-service demand set corresponding to each scheduling period; S32, based on the obtained multi-service demand set, the planned charging and discharging power and planned trading volume corresponding to the electricity energy trading are determined as the electricity energy trading power demand and capacity demand, respectively. The frequency regulation power demand corresponding to frequency regulation is determined as the bidirectional frequency regulation power reserve demand. The frequency regulation capacity reserve demand is calculated based on the frequency regulation power demand, the frequency regulation duration, and the frequency regulation energy demand coefficient determined by the historical frequency regulation command. The leased power and leased capacity corresponding to the new energy capacity leasing are determined as the leased power demand and leased capacity demand, respectively. Thus, the three types of service demand are uniformly converted into power demand and capacity demand. The frequency modulation capacity reservation requirement for the t-th scheduling period is as follows:

[0074] In the formula, Reserved for frequency modulation capacity For frequency modulation power requirements, For frequency modulation duration, This is the frequency modulation energy demand factor.

[0075] The frequency modulation energy demand coefficient is determined based on the ratio of the cumulative energy offset generated by historical frequency modulation commands within the corresponding historical scheduling period to the product of frequency modulation power and frequency modulation duration.

[0076] S33, based on the obtained power and capacity requirements of various services, and depending on whether each service requires the corresponding power or capacity to remain available during the service period determined in the day-ahead, the frequency regulation requirements and new energy capacity leasing requirements that need to remain available according to the day-ahead agreement are determined as guaranteed resource requirements, and the electricity trading requirements that allow adjustment of charging and discharging power or trading volume according to the intraday operating status are determined as adjustable resource requirements; a correspondence is established between the guaranteed resource requirements and the guaranteed callable resources, and a correspondence is established between the adjustable resource requirements and the remaining guaranteed callable resources and conditional callable resources after the allocation of guaranteed resource requirements is completed; S34, based on the established correspondence, within each scheduling period, the corresponding charging power, discharging power, charging capacity, and discharging capacity are allocated from the guaranteed available resources for frequency regulation needs and new energy capacity leasing needs, respectively. The allocated power and capacity are deducted from the guaranteed available resources for the corresponding scheduling period to obtain the remaining guaranteed available resources. Based on the remaining guaranteed available resources, charging and discharging power and charging and discharging capacity are allocated for the energy trading needs. When the remaining guaranteed available resources cannot meet the energy trading needs, the conditional available resources for the corresponding scheduling period are used as candidate supplementary resources for energy trading to obtain the initial service resource allocation results for each scheduling period. Within the same scheduling period, the sum of the guaranteed callable power in the same direction occupied by various services shall not exceed the guaranteed callable power in the corresponding direction, and the sum of the guaranteed callable capacity in the same direction occupied by various services shall not exceed the guaranteed callable capacity in the corresponding direction, so as to avoid the repeated allocation of the same guaranteed callable resource among different services.

[0077] S35, based on the obtained initial service resource allocation results, the charging power allocated to power trading, frequency regulation and new energy capacity leasing in each scheduling period is accumulated to obtain the total charging power of the corresponding scheduling period, the discharge power of each type of service is accumulated to obtain the total discharge power, and the expected state of charge of independent energy storage is updated period by period according to the total charging power, total discharge power, charging and discharging efficiency, scheduling period duration and current effective capacity to obtain the expected state of charge change sequence corresponding to the day-ahead scheduling cycle; The expected state of charge for the (t+1)th scheduling period is:

[0078] In the formula, and These are the expected states of charge at the start times of the t-th and t+1-th scheduling periods, respectively. and Let be the total charging power and the total discharging power during the t-th scheduling period, respectively. and These are charging efficiency and discharging efficiency, respectively. The duration of the scheduling period. This represents the current available capacity.

[0079] S36, based on the obtained expected state of charge change sequence, calculate the charging power excess between the total charging power and the corresponding available charging power, the discharge power excess between the total discharging power and the corresponding available discharge power, the charging capacity excess between the cumulative charging energy and the corresponding available charging capacity, the discharge capacity excess between the cumulative discharging energy and the corresponding available discharge capacity, and the state of charge excess energy corresponding to the expected state of charge exceeding the upper limit of the allowable state of charge or falling below the upper limit of the allowable state of charge for each scheduling period; when all excesses are zero, retain the service resource allocation result for the current scheduling period; when at least one excess is greater than zero, convert the corresponding excess into the charging power or discharging power that needs to be reduced, and first reduce it from the conditionally callable resources allocated to the energy trading in the corresponding scheduling period, with the reduction amount being the smaller value between the power to be reduced and the power allocated to the corresponding conditionally callable resources; when there is still a remaining excess after reducing all corresponding conditionally callable resources, reduce it from the guaranteed callable resources allocated to the energy trading according to the remaining excess, to obtain the service resource allocation result that satisfies the power, capacity, and state of charge constraints; Wherein, the expected state of charge satisfies:

[0080] In the formula, and These are the lower limit of the allowable state of charge and the upper limit of the allowable state of charge for independent energy storage, respectively.

[0081] S37, based on the obtained service resource allocation results, determine the corresponding charge / discharge depth and charge / discharge rate according to the expected charge / discharge power and expected charge / discharge energy of each type of service in each scheduling period, and combine with the expected battery temperature to determine the expected cycle degradation amount for each type of service according to the calculation method of cycle degradation amount in S1; at the same time, based on the expected state of charge, battery temperature and duration corresponding to each scheduling period, determine the expected calendar degradation amount according to the calculation method of calendar degradation amount in S1; express the expected cycle degradation amount and the expected calendar degradation amount as the capacity loss ratio relative to the initial rated capacity of independent energy storage, and add the two to obtain the expected degradation consumption amount corresponding to the day-ahead service resource allocation; S38: Based on the obtained estimated degradation consumption and the remaining degradation budget obtained in S2, calculate the degradation budget excess when the estimated degradation consumption exceeds the remaining degradation budget; when the degradation budget excess is zero, retain the service resource allocation result obtained in S36; when the degradation budget excess is greater than zero, calculate the unit degradation revenue for electricity trading, frequency regulation, and new energy capacity leasing respectively, and determine the service resource reduction order in ascending order of unit degradation revenue; for the service to be reduced, determine the unit resource reduction based on the ratio of the estimated degradation consumption of the service to the corresponding estimated service electricity. The degradation intensity is determined by the ratio of the current remaining excess degradation budget to the degradation intensity per unit of resource, which is then used as the theoretical resource reduction amount. The smaller of the theoretical resource reduction amount and the currently allocated resources for the service to be reduced is used as the actual resource reduction amount. Based on the actual resource reduction amount, the corresponding expected degradation amount is calculated and the remaining excess degradation budget is updated. When the updated remaining excess degradation budget is greater than zero, the resource reduction is repeated for the next service according to the service resource reduction order until the remaining excess degradation budget is zero, thus obtaining a day-ahead joint resource allocation result that satisfies the remaining degradation budget constraint. The unit degradation benefit for the s-th type of service is:

[0082] In the formula, The unit degradation benefit for serving class s, for, This represents the estimated degradation cost corresponding to the s-th type of service. This is used to avoid positive numbers with a denominator of zero.

[0083] The specific calculation formula for the corresponding reduction in the expected degradation is as follows:

[0084] In the formula, In order to reduce the expected amount of degradation, The intensity of degradation per unit resource This represents the actual amount of resource reduction.

[0085] The specific formula for calculating the excess amount of the remaining degradation budget for updating is as follows:

[0086] In the formula, For the remaining budget surplus of degradation that still needs to be eliminated, This is to mitigate the budget overrun.

[0087] S39, based on the obtained day-ahead joint resource allocation results, record the reserved charging and discharging power and reserved trading power corresponding to power energy trading, the reserved frequency regulation power and frequency regulation capacity corresponding to frequency regulation, and the reserved leased power and reserved leased capacity corresponding to new energy capacity leasing for each scheduling period. Also record the guaranteed callable resources, conditional callable resources, and corresponding expected degradation consumption occupied by each type of service to form a day-ahead reservation scheme. The day-ahead reservation scheme is used as the basic scheme for intraday call for random scenarios of new energy output in S4.

[0088] Among them, guaranteed callable resources refer to the power and capacity that can be allocated as deterministic resources during the day-ahead resource reservation phase after deducting the capacity uncertainty margin from the theoretically available resources; conditional callable resources refer to the power and capacity of theoretically available resources that, apart from guaranteed callable resources, can only be actually called upon after meeting the real-time release conditions specified in S28 during the actual operation within the day.

[0089] It should be noted that by unifying the demands for electricity trading, frequency regulation, and renewable energy capacity leasing into power and capacity demands, and combining this with a tiered, joint allocation based on guaranteed available resources, conditionally available resources, and remaining degradation budget, resource duplication among different services can be avoided. Simultaneously, by periodically verifying the over-limit of power, capacity, and state of charge, and determining resource reduction amounts based on the degree of over-limit, the day-ahead reserve scheme can be guaranteed to meet the actual operational boundaries of energy storage. Furthermore, by combining the expected degradation consumption and unit degradation revenue of various services, resources exceeding the degradation budget can be quantitatively reduced. While controlling lifecycle degradation consumption, priority is given to retaining service resources with higher degradation utilization benefits, thereby improving the reliability, economy, and full lifecycle utilization efficiency of independent energy storage multi-scenario service resource allocation.

[0090] S4 is used to call up the day-ahead reserved scheme for random scenarios of new energy power output within the day, calculate the scenario incremental degradation amount corresponding to each random scenario and verify the state of charge and life cycle safety margin after the call.

[0091] In this embodiment, for random scenarios of new energy output, the day-ahead reserved plan is called up intraday, and the scenario incremental degradation amount corresponding to each random scenario is calculated, including: S41: Obtain the daily forecast output of new energy sources and the updated forecast information of new energy sources within the day. Generate multiple random scenarios of new energy output based on historical new energy forecast errors, and determine the output of new energy scenarios corresponding to each random scenario in sequence according to the scheduling period within the day, forming a set of random scenarios of new energy output. S42, based on the random scenario of new energy output, calculate the output deviation between the new energy scenario output and the day-ahead predicted new energy output for each scheduling period, and determine the first compensation amount that can be borne by the reserved leasing resources in the new energy output deviation according to the rental power and rental capacity reserved for the new energy capacity rental demand in the corresponding scheduling period in the day-ahead reservation plan, and determine the remaining part of the new energy output deviation after deducting the first compensation amount as the scenario remaining deviation demand. Among them, the The new energy output deviation for a random scenario in the t-th scheduling period is:

[0092] In the formula, For the first The output of new energy sources in a random scenario during the t-th scheduling period. To provide power output for the day-ahead renewable energy forecast during the t-th scheduling period, For the first The deviation of renewable energy output from the day-ahead forecast renewable energy output in a random scenario during the t-th scheduling period.

[0093] The first compensation amount is:

[0094] In the formula, For the first The first compensation amount undertaken by a random scenario in the t-th scheduling period using reserved resources from new energy capacity leasing. This refers to the leased power reserved for new energy capacity leasing demand during the t-th scheduling period. For the first In a random scenario, during the t-th scheduling period, the remaining leased capacity reserved for new energy capacity leasing that has not yet been used in the previous scheduling period. The duration of a single scheduling period.

[0095] The remaining deviation requirement for the scenario is:

[0096] In the formula, When the initial compensation amount cannot fully cover the output deviation of new energy sources, the remaining deviation demand in the scenario still needs to be covered by other available energy storage resources.

[0097] The corresponding compensation direction is determined as either the charging direction or the discharging direction based on the sign of the new energy output deviation.

[0098] S43, based on the scenario remaining deviation requirement, obtain the power and capacity reserved for power trading, frequency regulation and new energy capacity leasing respectively in the current scheduling period of the day-ahead reservation scheme, and based on the guaranteed callable resources and conditional callable resources formed in S28, deduct the service resources that still need to be maintained in the current scheduling period, and obtain the remaining guaranteed callable resources and remaining conditional callable resources that can be further used to compensate for the scenario remaining deviation requirement in the current scheduling period. The service resources that still need to be maintained include frequency regulation reserved resources that have not yet been completed during the current scheduling period, remaining reserved resources for new energy capacity leasing, and electricity trading resources that still need to be executed according to the day-ahead reserved plan.

[0099] The conditionally callable resources are checked according to the real-time release conditions specified in S28, and the remaining conditionally callable power that meets the real-time release conditions is determined as the releaseable conditional power.

[0100] Further determine the basic callable power limit for the current scheduling period:

[0101] In the formula, The remaining guaranteed callable power after deducting the service resources that still need to be maintained. For conditional power release, This is the upper limit of the basic callable power that can be used to compensate for the remaining deviation demand in new energy scenarios during the current scheduling period without occupying service resources that still need to be maintained.

[0102] S44, Based on the basic callable power limit, between the smaller value of zero to the scenario remaining deviation requirement and the basic callable power limit, multiple candidate additional callable powers are constructed in power increment order to form a candidate callable power set;

[0103] And satisfy:

[0104] as well as:

[0105] This yields multiple candidate additional call schemes for the remaining deviation requirements of the scenario during the current scheduling period; In the formula, For the first A set of candidate call power constructed for a random scenario in the t-th scheduling period. Add the maximum candidate call power from the candidate call power set, ensuring that it does not exceed the smaller of the scenario's remaining deviation requirement and the basic callable power limit. Zero additional call power means that no additional callable resources are used to compensate for the new energy deviation beyond the first compensation amount.

[0106] S45, perform directional netting on the additional call power, first compensation amount and reserved charging and discharging power of each candidate scheme in the current scheduling period, obtain the candidate net charging and discharging power corresponding to each candidate scheme, and predict the candidate state of charge after the execution of each candidate scheme based on the candidate net charging and discharging power, current effective capacity, charging and discharging efficiency and scheduling period duration. In this scheme, the charging direction is defined as the positive direction and the discharging direction as the negative direction. The power of the three types of services in the day-ahead reservation scheme is combined to form the day-ahead net planned power. Then the net operating power corresponding to the Mth candidate scheme is:

[0107] Further confirmation:

[0108]

[0109] Make:

[0110] The corresponding candidate charge states are:

[0111] In the formula, For the first In a random scenario, during the t-th scheduling period, under the M-th candidate scheme, the candidate compensation power is synthesized from the first compensation amount and the candidate additional call power according to the compensation direction corresponding to the new energy output deviation. The candidate net operating power is obtained by adding the Mth candidate compensation power to the current net planned power. Let M be the candidate net charging power corresponding to the Mth candidate scheme. Let M be the candidate net discharge power corresponding to the Mth candidate scheme. The state of charge at the start of the (t+1)th scheduling period is predicted after executing the Mth candidate calling scheme. For the first The state of charge of a random scenario at the start of the t-th scheduling period. Charging efficiency for independent energy storage. For independent energy storage, the discharge efficiency For the first The independent effective energy storage capacity is determined based on the current health status at the start of the t-th scheduling period for each random scenario.

[0112] S46. Based on the candidate net charge / discharge power and candidate state of charge, determine the depth of charge / discharge according to the state of charge change corresponding to each candidate scheme, determine the charge / discharge rate according to the candidate net charge / discharge power and the current effective capacity, and combine the current battery temperature, determine the candidate incremental degradation amount corresponding to each candidate call power in the current scheduling period according to the calculation method of cycle degradation amount and calendar degradation amount in S1. The candidate incremental degradation amount corresponding to the Mth candidate call power is:

[0113] In the formula, and These are the cyclic incremental degradation and calendar incremental degradation generated by the corresponding candidate calls, respectively, and both are characterized as a capacity loss ratio relative to the initial rated capacity of the independent energy storage. This represents the candidate incremental degradation amount.

[0114] S47. Based on the obtained adjacent candidate call power and corresponding candidate incremental degradation amount, calculate the marginal degradation intensity corresponding to each adjacent candidate call power interval to characterize the proportion of capacity loss increased by increasing unit call power in the current battery state, and form the marginal degradation sequence corresponding to the current scheduling period. The specific formula for calculating the marginal degradation intensity is as follows:

[0115] In the formula, Let be the marginal degradation intensity corresponding to the Mth candidate call interval.

[0116] like Figure 5 The diagram illustrates the change in marginal degradation intensity corresponding to the candidate additional call power in this embodiment. As the candidate additional call power gradually increases, the marginal degradation intensity exhibits a non-linear growth trend. Within the recommended operating range, the capacity loss per unit of additional call power increases relatively slowly. When the call power approaches the safe call boundary, the marginal degradation intensity increases rapidly, indicating that further increasing the call power will lead to a significant increase in the lifetime consumption per unit of regulation capacity. Therefore, this embodiment determines the safe call boundary under degradation constraints through marginal degradation intensity, ensuring that the intraday call process meets regulation requirements while also considering lifecycle resource utilization efficiency and operational safety.

[0117] S48. Based on the remaining degradation budget at the start of the current scheduling period and the frequency regulation service, renewable energy capacity leasing service and deterministic power trading service already committed for each scheduling period after the current scheduling period in the day-ahead reservation scheme, calculate the minimum degradation amount required to be retained for the subsequent committed services according to the degradation calculation method in S1, and determine the non-negative remaining amount after deducting the minimum degradation amount from the current remaining degradation budget as the free degradation margin for the current scheduling period. The specific formula for calculating the free degradation margin is as follows:

[0118] In the formula, This represents the free degradation margin for the current scheduling period. For the current remaining degradation budget, The minimum amount of degradation that must be retained for the committed service after the current scheduling period is completed.

[0119] The minimum degradation amount is calculated and accumulated for each scheduling period based on the minimum charging and discharging power and minimum service capacity that must be fulfilled in the pre-scheduled plan for each subsequent scheduling period, using the same cyclic degradation amount and calendar degradation amount calculation method as S1.

[0120] S49, based on each candidate incremental degradation amount and the free degradation margin, select candidate call power from the candidate call power set whose candidate incremental degradation amount does not exceed the free degradation margin, and determine the largest candidate call power as the maximum allowable call power under degradation constraints for the current scheduling period; This converts the remaining lifetime degradation capability into the power call boundary corresponding to the current scheduling period.

[0121] S410, based on each candidate state of charge, determine the maximum candidate call power that still meets the upper and lower limits of the allowable state of charge after executing the candidate call, and use it as the maximum allowable call power under the state of charge constraint; and determine the maximum allowable call power under the temperature constraint according to the current battery temperature and the allowable charge and discharge power under the current temperature conditions given by the energy storage battery management system. Take the smaller value of the maximum allowable call power under the state of charge constraint, the maximum allowable call power under the temperature constraint, the maximum allowable call power under the degradation constraint, and the physical callable power corresponding to the current hierarchical schedulable resource to obtain the upper limit of the safe call power for the current scheduling period; S411, based on the scenario remaining deviation requirement and the safety call power limit, the smaller of the two is determined as the actual scenario call power for the current scheduling period, and the actual net charging power or actual net discharging power is determined according to the direction netting process, so as to obtain the actual scenario operating power for the current scheduling period. The charging or discharging direction corresponding to the actual scenario's power output deviation is determined based on the direction of the new energy output deviation.

[0122] S412: Based on the actual scenario call power, obtain the scenario charge state of the next scheduling period according to the charge state update method of S45, and calculate the actual time period incremental degradation amount generated by the actual scenario call in the current scheduling period according to the degradation calculation method in S1; update the remaining degradation budget according to the actual time period incremental degradation amount, and update the health status and effective capacity according to the updated cumulative degradation amount. in:

[0123] In the formula, For the updated remaining degradation budget, For the first The incremental degradation amount generated by the actual call in a random scenario during the t-th scheduling period.

[0124] The corresponding cumulative degradation amount is updated as follows:

[0125] In the formula, This represents the updated cumulative degradation amount. For the first The cumulative degradation of a random scenario during the t-th scheduling period.

[0126] The corresponding health status is:

[0127] In the formula, This is the updated health status.

[0128] The corresponding effective capacity is:

[0129] In the formula, This is the updated effective capacity.

[0130] S413: Based on the updated state of charge, health status, effective capacity, and remaining degradation budget, recalculate the available power and available capacity corresponding to the next scheduling period according to the determination method of available charging and discharging power and available charging and discharging capacity in S2. Combined with the division method of guaranteed callable resources and conditional callable resources in S28, re-form the hierarchical schedulable resource set corresponding to the next scheduling period. Use the re-formed hierarchical schedulable resource set as the resource boundary for executing S43 in the next scheduling period, so as to realize the rolling feedback reconstruction of the resource boundary of the next scheduling period based on the calling result of the current scheduling period.

[0131] S414, according to the order of scheduling time periods, the hierarchical schedulable resource set reconstructed based on S413 is sequentially processed... In the subsequent scheduling periods of a random new energy output scenario, S43 to S413 are repeatedly executed until the rolling call of all intraday scheduling periods under the random scenario is completed. The actual incremental degradation amount generated in each scheduling period is accumulated to obtain the first... The incremental degradation amount corresponding to a random scenario of new energy power output; Perform the above steps for all random scenarios of new energy power output to obtain the set of scenario incremental degradation corresponding to each random scenario of new energy power output.

[0132] The incremental degradation amount in the above scenario refers to the amount of degradation in the first scenario. In a scenario where new energy output is random, the proportion of new capacity loss in the current scheduling cycle is obtained by summing the actual incremental degradation of each scheduling period when the independent energy storage is running according to the intraday rolling call results.

[0133] It should be noted that by linking the randomness of renewable energy output, the day-ahead resource reservation status, and the energy storage lifecycle degradation constraints, the renewable energy capacity leasing and reserved resources are first used to compensate for renewable energy output deviations during intraday scheduling. Then, candidate scheduling schemes are constructed based on the remaining deviation demand, combined with guaranteed callable resources and conditionally callable resources that meet release conditions. The marginal degradation intensity and free degradation margin are determined by the change in state of charge and incremental degradation corresponding to the candidate schemes, thereby transforming the remaining degradation capacity into the safe callable power boundary for the current period. At the same time, the remaining degradation budget, health status, and effective capacity are updated in real time based on the incremental degradation generated by actual calls, and the callable resource boundary for the next scheduling period is reconstructed accordingly. This allows the actual operation and degradation results of the previous period to be fed back to subsequent resource call decisions, thereby avoiding excessive resource calls or conservative reservations caused by fixed power and fixed capacity boundaries. While ensuring the fulfillment of various day-ahead services and the safety of energy storage operation, this improves the utilization efficiency of energy storage resources under the random fluctuations of renewable energy and the rationality of lifecycle scheduling.

[0134] Furthermore, the state of charge and lifecycle safety margin after the call are verified, including: S415, based on the intraday rolling call results corresponding to each random scenario of new energy power output, obtain the actual net charging power and actual net discharging power of each random scenario in each scheduling period, and calculate the actual state of charge after the actual call according to the state of charge, effective capacity, charging efficiency, discharging efficiency and scheduling period duration at the start of the current scheduling period, forming the actual state of charge change sequence corresponding to each random scenario of new energy power output. S416, based on the actual state of charge change sequence, compare the actual state of charge of each scheduling period with the lower limit and upper limit of the allowable state of charge of independent energy storage respectively; when the actual state of charge is between the upper and lower limits of the allowable state of charge, the corresponding scheduling period is determined as the safe state of charge period, and the remaining margin of the actual state of charge relative to the lower limit and upper limit of the allowable state of charge is calculated respectively; when the actual state of charge is lower than the lower limit of the allowable state of charge or higher than the upper limit of the allowable state of charge, the corresponding scheduling period is determined as the state of charge exceeding the limit period; The corresponding discharge direction state-of-charge margin is:

[0135] The corresponding state-of-charge margin in the charging direction is:

[0136] In the formula, The current state of charge is far from the limit of the allowable state of charge. The remaining margin, The current state of charge is far from the upper limit of the allowable state of charge. When both the remaining margin and the remaining margin are not less than zero, it indicates that the current state of charge meets the requirements for safe operation. This represents the actual state of charge.

[0137] The reason for calculating the SOC margin separately in the up and down directions instead of simply taking a single margin is that energy storage may face charging or discharging calls in the future, and the actual SOC constraints in the two directions are different.

[0138] S417. Based on the incremental degradation amount of the scenario and the cumulative degradation amount already formed by independent energy storage at the start of the current scheduling cycle, the two are added together to obtain the expected cumulative degradation amount after each new energy output random scenario completes the current scheduling cycle call, and the expected health status after the call is determined according to the expected cumulative degradation amount. S418, Based on the expected cumulative degradation after the call, the maximum allowable cumulative degradation is determined according to the minimum allowable health status corresponding to the independent energy storage life termination condition, and the difference between the maximum allowable cumulative degradation and the expected cumulative degradation after the call is determined as the life cycle safety margin under the corresponding random scenario of new energy output. When the lifecycle safety margin is greater than or equal to 0, it means that the expected cumulative degradation amount after the current random scenario call has not yet exceeded the lifecycle allowable degradation boundary; When the lifecycle safety margin is less than 0, it means that the expected cumulative degradation after the current random scenario call exceeds the lifecycle allowable degradation boundary.

[0139] S419, based on the state-of-charge verification results of each scheduling period in S416 and the lifecycle safety margin obtained in S418, comprehensively verify the intraday call results corresponding to each new energy output random scenario; when the actual state of charge of all scheduling periods of the corresponding random scenario is within the allowable upper and lower limits of the state of charge, and the corresponding lifecycle safety margin is not less than zero, the random scenario is determined as a call safe scenario; when the actual state of charge of at least one scheduling period exceeds the allowable upper and lower limits of the state of charge, or the lifecycle safety margin is less than zero, the random scenario is determined as a call over-limit scenario, and the corresponding state of charge over-limit period, over-limit direction, state of charge over-limit amount, and lifecycle degradation over-limit amount are recorded to form the call safety verification results corresponding to each new energy output random scenario.

[0140] It should be noted that by jointly verifying the state of charge (SOC) and lifecycle safety margin after intraday rolling dispatch, the feasibility of energy storage dispatch schemes under random renewable energy output scenarios can be verified from both short-term operational safety and long-term lifecycle safety dimensions. The remaining SOC margin in the charging and discharging directions is used to identify the risk of SOC exceeding the limit during different dispatch periods. Combined with the incremental degradation amount in the scenario, it is determined whether the cumulative degradation after dispatch exceeds the lifecycle allowable boundary. This allows for timely identification of operational limit exceeding and lifecycle overdraft risks caused by random fluctuations in renewable energy and continuous charging and discharging dispatch. This provides a reliable basis for subsequent health status updates and adjustments to dispatchable resource boundaries, thereby improving the safety and stability of independent energy storage's full lifecycle collaborative dispatch.

[0141] S5, update the lifecycle health status based on the actual incremental degradation amount of the current scheduling cycle, and correct the remaining degradation budget for the next scheduling cycle based on the deviation between the actual incremental degradation amount and the corresponding scenario incremental degradation amount. Reconstruct the available capacity for the next scheduling cycle based on the updated lifecycle health status and the corrected remaining degradation budget to obtain a continuously updated independent energy storage collaborative scheduling scheme across lifecycles, including: S51, obtain the actual new energy output sequence after the end of the current scheduling cycle and the actual charging and discharging power, actual state of charge and actual battery temperature change sequence of independent energy storage during the current scheduling cycle, and perform time correspondence on the actual operating data according to the scheduling period adopted in S4 to form the actual operating trajectory of the current scheduling cycle. S52, compare the actual new energy output sequence with the new energy output sequence corresponding to each new energy output random scenario, calculate the trajectory deviation between the actual new energy output sequence and each random scenario, and determine the random scenario with the smallest trajectory deviation as the degradation prediction reference scenario for the current scheduling cycle, and determine the scenario incremental degradation amount corresponding to the degradation prediction reference scenario in S4 as the degradation prediction benchmark value for the current scheduling cycle. Among them, the The trajectory deviation between a random scenario and the actual new energy output sequence is:

[0142] The reference scenario for degradation prediction is:

[0143] In the formula, The deviation between the actual renewable energy output trajectory in the k-th scheduling cycle and the trajectory in the ω-th random scenario is... For the ω-th random scenario in the t-th scheduling period, the new energy output is... This refers to the installed capacity of new energy sources or the benchmark power used to normalize the deviation of new energy output. The reference scenario number is used for degradation prediction.

[0144] It should be noted that the incremental degradation amount in this scenario is only used as a "prediction baseline" and is not used to update the SOH as the actual degradation amount.

[0145] S53, based on the obtained independent energy storage actual operation trajectory, identifies the actual charging and discharging process formed in the current scheduling cycle according to the actual state of charge change, determines the actual cycle incremental degradation amount according to the actual charging and discharging depth, actual charging and discharging rate and actual battery temperature; and determines the actual calendar incremental degradation amount according to the actual state of charge, actual battery temperature and duration of each scheduling period, and adds the two to obtain the actual incremental degradation amount of the current scheduling cycle. The actual cyclic incremental degradation, actual calendar incremental degradation, and actual incremental degradation are all characterized as capacity loss ratios relative to the initial rated capacity of the independent energy storage.

[0146] S54, based on the obtained degradation prediction benchmark value and the actual incremental degradation amount, the difference between the actual incremental degradation amount and the degradation prediction benchmark value is determined as the degradation fulfillment deviation of the current scheduling cycle, and the degradation fulfillment deviation of the current scheduling cycle is added to the degradation fulfillment deviation record corresponding to each previous scheduling cycle to form an updated degradation fulfillment deviation sequence. S55, based on the formed degradation fulfillment deviation sequence, obtain the actual incremental degradation amount and degradation prediction benchmark value corresponding to the current scheduling cycle and the previous multiple consecutive scheduling cycles, and assign each historical scheduling cycle with a decreasing weight from near to far according to the time interval between the current scheduling cycle and the historical scheduling cycle, and determine the degradation fulfillment deviation compensation coefficient of the next scheduling cycle according to the ratio of the weighted actual incremental degradation amount to the weighted predicted incremental degradation amount. The weight for the i-th historical scheduling period is determined as follows:

[0147] In the formula, This represents the weight assigned to the i-th historical scheduling cycle when determining the degradation compensation coefficient for the (k+1)-th scheduling cycle. is the relative time distance between the i-th historical scheduling cycle and the current scheduling cycle, j is the summation index, and L is the number of historical scheduling cycles involved in the deviation compensation calculation.

[0148] The degradation realization deviation compensation coefficient is:

[0149] In the formula, This is the degradation fulfillment deviation compensation coefficient used to correct the degradation budget for the (k+1)th scheduling cycle. Let be the actual incremental degradation amount generated in the i-th historical scheduling cycle. This is the degradation prediction baseline value corresponding to the i-th historical scheduling cycle.

[0150] when When this occurs, it indicates that the actual degradation in the near term is higher than the predicted degradation, and the degradation budget for the next scheduling cycle needs to be tightened. when When the actual degradation is lower than the predicted degradation in the near term, the degradation budget for the next scheduling cycle can be appropriately released within the allowable range of the remaining lifespan.

[0151] By using multiple consecutive cycles to form compensation coefficients, we can avoid directly and significantly adjusting the resource boundary of the next cycle based solely on the occasional operational fluctuations of a single scheduling cycle.

[0152] S56, based on the actual incremental degradation amount obtained and the historical cumulative degradation amount at the start of the current scheduling cycle, the historical cumulative degradation amount at the start of the next scheduling cycle is obtained, and the health status and effective capacity of the next scheduling cycle are determined based on the updated historical cumulative degradation amount; At the same time, the actual charge state at the end of the current scheduling cycle is used as the initial charge state of the next scheduling cycle, thereby obtaining the initial life cycle state of the next scheduling cycle.

[0153] S57, based on the historical cumulative degradation amount obtained for the next scheduling cycle, determine the remaining lifetime degradation amount corresponding to the start time of the next scheduling cycle according to the end-of-life health status, and determine the basic degradation budget for the next scheduling cycle without considering degradation fulfillment deviation according to the degradation budget calculation method in S2. S58, based on the degradation fulfillment deviation compensation coefficient, compensates and corrects the basic degradation budget obtained in S57, and limits the correction result to between zero and the remaining lifetime degradation amount, to obtain the remaining degradation budget actually used for collaborative scheduling in the next scheduling cycle; The compensation correction is specifically as follows:

[0154] In the formula, After actual degradation fulfillment deviation feedback compensation, the degradation budget ultimately allowed for the (k+1)th scheduling cycle to be used for coordinated scheduling of electricity trading, frequency regulation, and renewable energy capacity leasing is determined. To determine the basic degradation budget without considering degradation prediction and fulfillment deviation compensation, based on factors such as the remaining lifetime degradation amount in the (k+1)th scheduling cycle and the expected remaining operating period, according to the established degradation budget allocation method in S2, It represents the remaining lifetime degradation amount that can still be consumed at the start of the (k+1)th scheduling cycle, i.e., the proportion of capacity loss remaining before the end of the lifetime degradation boundary.

[0155] S59: Based on the health status, effective capacity, and initial state of charge of the next scheduling cycle obtained in S56, and the remaining degradation budget after compensation obtained in S58, and combined with the battery temperature and environmental operating parameters at the start of the next scheduling cycle, the available charging power, available discharging power, available charging capacity, and available discharging capacity of the next scheduling cycle are recalculated according to the available capacity determination method in S2, forming an updated available capacity set for the next scheduling cycle; the updated available capacity set is used as the input for S28 to divide the guaranteed callable resources and conditionally callable resources for the next scheduling cycle, and S28, S3, and S4 are executed sequentially, so that the actual degradation realization result of the current scheduling cycle is fed back to the resource boundary, resource layering, and collaborative scheduling process of the next scheduling cycle, thereby obtaining an independent energy storage collaborative scheduling scheme that is continuously updated across the life cycle.

[0156] It should be noted that, compared with conventional technical solutions that directly determine the available capacity for the next scheduling cycle based solely on the current SOH, SOC, and fixed degradation model, the above solution establishes a cross-cycle closed loop of "predicted degradation—actual degradation—realization deviation—budget compensation—capacity reconstruction." This compares the degradation results generated by the actual operation of the current scheduling cycle with the pre-predicted degradation results under random scenarios. It also uses the degradation realization deviations from multiple consecutive scheduling cycles to form a compensation coefficient, adaptively correcting the degradation budget for the next scheduling cycle. This proactively tightens lifetime resources when the actual degradation is higher than the predicted level, and moderately releases lifetime resources within the allowable range of the remaining lifetime when the actual degradation is lower than the predicted level. Simultaneously, the corrected degradation budget, along with the updated health status, effective capacity, and initial state of charge, are used to reconstruct the available power and capacity for the next cycle. This reduces the excessive consumption of lifetime resources or overly conservative scheduling capabilities caused by the long-term accumulation of degradation model prediction errors. It allows the available energy storage capacity to be continuously adjusted across scheduling cycles according to the actual degradation status, improving the resource utilization rate of energy storage throughout its entire lifecycle and the adaptability of multi-scenario collaborative scheduling while ensuring lifecycle safety.

[0157] Reference Figure 2 As shown in the diagram, this invention provides a schematic of an independent energy storage full lifecycle collaborative scheduling system, including a lifecycle availability capability determination module, a schedulable resource trusted layering module, a multi-service collaborative scheduling and degradation constraint invocation module, and a degradation deviation feedback and resource boundary reconstruction module. The modules are interconnected. The lifecycle availability determination module is used to obtain the current health status of energy storage and determine the available power, available capacity and remaining degradation budget for the current scheduling cycle; The schedulable resource trusted layering module is used to divide available power and available capacity into guaranteed callable resources and conditionally callable resources, and construct a layered set of schedulable resources. The multi-service collaborative scheduling and degradation constraint invocation module is used to allocate power services and invocation within the day under the constraints of the hierarchical schedulable resource set and the remaining degradation budget. The power limit of the intraday invocation is determined by the change in state of charge and incremental degradation caused by the invocation. The degradation deviation feedback and resource boundary reconstruction module is used to correct the degradation budget for the next period based on the deviation between the actual incremental degradation amount and the predicted value in the current period, and to coordinate with the updated health status to reconstruct the scheduling resource boundary.

[0158] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product.

[0159] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0160] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0161] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for coordinated scheduling of independent energy storage throughout its entire lifecycle, characterized in that, include: Obtain the current health status of energy storage and determine the available power, available capacity, and remaining degradation budget for the current scheduling cycle; The available power and available capacity are divided into guaranteed callable resources and conditionally callable resources, and a hierarchical set of schedulable resources is constructed. Under the constraints of a hierarchical set of schedulable resources and a remaining degradation budget, power service allocation and intraday dispatch are carried out, wherein the power limit of intraday dispatch is determined by the change in state of charge and incremental degradation caused by the dispatch. Based on the deviation between the actual incremental degradation amount and the predicted value in the current cycle, the degradation budget for the next cycle is corrected, and the scheduling resource boundaries are reconstructed in a rolling manner in conjunction with the updated health status.

2. The method according to claim 1, characterized in that, Obtain the current health status of energy storage, including: Synchronize and preprocess battery monitoring data and environmental monitoring data from historical operation periods to obtain an effective operational dataset; Based on the effective running dataset, the cumulative cycle degradation caused by charge-discharge cycles and the cumulative calendar degradation caused by time aging are calculated respectively. After being superimposed, the initial health status is corrected to obtain the current health status value. The current battery temperature, ambient temperature, and state of charge range are determined as the current environmental operating parameters.

3. The method according to claim 2, characterized in that, The determination of available power, available capacity, and remaining degradation budget for the current scheduling period includes: The initial rated capacity is adjusted based on the current health status, and the effective capacity and chargeable / dischargeable capacity are determined in conjunction with the state of charge boundary. Based on the effective capacity, current state of charge and battery temperature, determine the allowable charge / discharge power on the battery side and compare it with the allowable power on the converter side, taking the smaller value as the available charge / discharge power; The maximum charge / discharge energy corresponding to the available charge / discharge power is compared with the charge / discharge capacity, and the smaller value is taken as the available charge / discharge capacity. Obtain the historical cumulative degradation amount and the end-of-life degradation limit, use the difference between the two as the remaining degradation amount, and allocate it according to the proportion of the current scheduling cycle to the expected remaining runtime to obtain the remaining degradation budget for the current scheduling cycle.

4. The method according to claim 1, characterized in that, The division of available power and available capacity into guaranteed callable resources and conditionally callable resources includes: Obtain the state parameters of each battery cluster and determine the degree of dispersion in the battery cluster's capability; The prediction deviation boundary is determined based on the deviation between the theoretical available capacity and the actual fulfillment capacity in the historical scheduling cycle; Based on the aforementioned capacity dispersion and prediction deviation boundary, the corresponding margin is subtracted from the available power and available capacity to obtain the guaranteed callable resources; The difference between available power and available capacity and guaranteed callable resources is determined as conditional callable resources, and these conditional callable resources are released only when preset conditions are met in the real-time state.

5. The method according to claim 1, characterized in that, The power service distribution includes: The electricity trading demand, frequency regulation demand, and new energy capacity leasing demand are respectively converted into corresponding power demand and capacity demand. The frequency regulation demand and the new energy capacity leasing demand are defined as guaranteed resource demand, and the electricity trading demand is defined as adjustable resource demand. The guaranteed callable resources will be allocated preferentially to the guaranteed resource requirements, and the remaining guaranteed callable resources after deducting the allocated resources, as well as the conditional callable resources, will be allocated to the adjustable resource requirements. Calculate the expected degradation consumption for each service after allocation. If the total expected degradation consumption exceeds the remaining degradation budget, reduce the resource allocation of the corresponding services in order of increasing unit degradation benefit until the remaining degradation budget constraint is met.

6. The method according to claim 1, characterized in that, The intraday call includes: For each scheduling period of each random scenario of new energy output, the new energy capacity rental resources reserved in the previous day are first used to compensate for the new energy output deviation in that period, and multiple candidate additional call power are constructed for the remaining deviation requirements. Calculate the incremental degradation amount corresponding to each candidate call power. Based on the free degradation margin after deducting the minimum degradation amount required for subsequent committed services from the current remaining degradation budget, select candidate call powers whose incremental degradation amount does not exceed the free degradation margin. Combine the state of charge constraint and temperature constraint to determine the upper limit of safe call power. The smaller of the remaining deviation requirement and the upper limit of the safe call power is taken as the actual scenario call power for that period.

7. The method according to claim 6, characterized in that, The intraday call also includes: The remaining degradation budget is updated based on the actual incremental degradation amount generated by the power call in the actual scenario, and the health status and effective capacity are also updated. Based on the updated health status and effective capacity, the available power and available capacity for the next scheduling period are recalculated, and the guaranteed callable resources and conditionally callable resources are re-divided to form a hierarchical set of schedulable resources for the next scheduling period.

8. The method according to claim 7, characterized in that, The intraday call also includes: Calculate the discharge directional margin relative to the upper limit of the allowable state of charge and the charging directional margin relative to the upper limit of the allowable state of charge, respectively, so as to independently determine the risk of exceeding the state of charge limit from both the charging and discharging directions. The lifecycle safety margin is determined based on the expected cumulative degradation after the call and the maximum permissible cumulative degradation determined based on the end-of-life conditions. When the actual charge state of each scheduling period is within the allowable range and the life cycle safety margin is not less than zero, it is determined to be a safe calling scenario; otherwise, it is determined to be a calling over-limit scenario.

9. The method according to claim 1, characterized in that, The step of feeding back and correcting the degradation budget for the next period based on the deviation between the actual incremental degradation amount and the predicted value in the current period, and collaboratively reconstructing the scheduling resource boundary in a rolling manner based on the updated health status, includes: Based on the deviation between the actual incremental degradation amount and the predicted baseline value in the current scheduling cycle, the degradation budget compensation coefficient for the next scheduling cycle is determined, and the basic degradation budget is corrected using the compensation coefficient. The health status is updated based on the actual incremental degradation amount of the current scheduling cycle. The corrected remaining degradation budget and the updated health status are used together to reconstruct the available capacity for the next scheduling cycle, so that the actual degradation result of the current scheduling cycle is fed back to the resource boundary of the subsequent scheduling cycle, realizing cross-cycle closed-loop update.

10. A system using the independent energy storage full life cycle collaborative scheduling method as described in any one of claims 1-9, characterized in that, include: The lifecycle availability determination module is used to obtain the current health status of energy storage and determine the available power, available capacity and remaining degradation budget for the current scheduling cycle; The schedulable resource trusted layering module is used to divide available power and available capacity into guaranteed callable resources and conditionally callable resources, and construct a layered set of schedulable resources. The multi-service collaborative scheduling and degradation constraint invocation module is used to allocate power services and invocation within the day under the constraints of the hierarchical schedulable resource set and the remaining degradation budget. The power limit of the intraday invocation is determined by the change in state of charge and incremental degradation caused by the invocation. The degradation deviation feedback and resource boundary reconstruction module is used to correct the degradation budget for the next period based on the deviation between the actual incremental degradation amount and the predicted value in the current period, and to coordinate with the updated health status to reconstruct the scheduling resource boundary.

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