Medium and long term and multi-day fusion transaction method and system for independent energy storage power station

Abstract

The application provides a medium and long term and multi-day fusion transaction method and system for independent energy storage power station, and relates to the technical field of data processing. The method comprises the following steps: firstly, collecting physical parameters of the power station and medium and long term capacity contract information, and generating a daily medium and long term capacity locking block table according to the contract content; synchronously acquiring day-ahead electricity price time series data, and generating an initial charging and discharging strategy in combination with the physical parameters of the energy storage; taking the medium and long term capacity contract constraint condition as a benchmark, and performing conflict correction and optimization adjustment on the preliminary charging and discharging strategy to output a final adjustable strategy plan table in compliance; and finally, generating day-ahead electricity quantity declaration data that can be used for market declaration based on the plan table, realizing medium and long term contract and multi-day operation time series fusion, avoiding capacity performance conflict, and guaranteeing energy storage operation compliance.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and in particular to a method and system for medium- and long-term and multi-day integrated trading of independent energy storage power stations. Background Technology

[0002] In the current electricity market environment, independent energy storage power stations, as assets with flexible dispatch capabilities, are widely involved in multi-level trading structures, including medium- and long-term capacity markets, day-ahead power markets, and real-time power balance markets. In particular, medium- and long-term capacity contracts (such as monthly or quarterly capacity output contracts) usually require energy storage to maintain the discharge capacity required by the grid during specific periods, which puts forward strict requirements on the dispatch capability guarantee of energy storage systems.

[0003] Currently, when generating day-ahead charge / discharge trading strategies, the relevant scheduling systems primarily rely on single day-ahead electricity price time series forecasts, with the sole optimization objective of maximizing daily peak-valley arbitrage profits. During computation, the system directly outputs the daily charge / discharge plan based solely on the conventional physical boundary conditions of the energy storage power station (such as upper and lower limits of State of Charge (SOC), maximum charge / discharge power, etc.), while treating the complex performance conditions in medium- and long-term capacity contracts as static, offline contract texts.

[0004] However, in practice, traditional technologies do not fully consider the power maintenance and energy retention requirements during medium- and long-term capacity lock-in periods when formulating day-ahead discharge strategies. This may lead to discharge plans covering prohibited discharge periods or prematurely lowering the State of Charge (SOC) level, resulting in insufficient dispatchability of the energy storage system during the capacity fulfillment period, or even contract default. Currently, most dispatching systems lack automated strategy conflict identification and coordination mechanisms, posing certain operational risks. Summary of the Invention

[0005] This application provides a method and system for medium- and long-term and multi-day integrated trading of independent energy storage power plants, which is used to automatically generate executable day-ahead charge and discharge strategies under the constraints of medium- and long-term capacity contracts.

[0006] In a first aspect, this application provides a method for medium- and long-term and multi-day integrated trading of independent energy storage power stations. The method includes: obtaining physical parameters and medium- and long-term capacity contract information of the independent energy storage power station; generating a daily medium- and long-term locked block table based on the medium- and long-term capacity contract information; obtaining the day-ahead electricity price time series and generating a preliminary charging and discharging strategy based on the physical parameters and the day-ahead electricity price time series; adjusting the preliminary charging and discharging strategy with the medium- and long-term capacity contract information as a constraint to obtain a final adjustable strategy plan table; and generating day-ahead electricity declaration data based on the final adjustable strategy plan table.

[0007] By adopting the above technical solution, the medium- and long-term capacity contract information is structured into a locked block table before generating the day-ahead charge and release strategy, giving the subsequent strategy generation stage a natural contract awareness capability. This locked block table is then used as a hard constraint to perform conflict detection and adjustment on the initial charge and release strategy, unifying the previously separate medium- and long-term performance logic and day-ahead scheduling logic into a single decision-making process. Therefore, the system can simultaneously satisfy contract performance security and day-ahead scheduling objectives within a single strategy generation cycle, avoiding default risks and manual intervention costs caused by the separation of strategy levels.

[0008] In conjunction with some embodiments of the first aspect, in some embodiments, the step of generating a daily medium-to-long-term lock-in block table based on the medium-to-long-term capacity contract information specifically includes: obtaining the capacity availability obligation parameters undertaken by the independent energy storage power station in the current period from the medium-to-long-term capacity contract information, wherein the capacity availability obligation parameters include at least available capacity, capacity lock-in period, power maintenance, and alarm conditions; encapsulating the capacity availability obligation parameters into the contract strategy management module, and generating a temporary scheduling template based on the capacity lock-in requirements for each capacity lock-in period; subdividing the daily time axis into hourly granularities based on the temporary scheduling template and the date of the next day; constructing a schedulable state dictionary at each hourly granularity, and generating a time period lock-in control table as the daily medium-to-long-term lock-in block table, wherein the schedulable state dictionary includes whether discharge is possible, discharge intensity limits, and whether the SOC safety boundary must be maintained.

[0009] By adopting the above technical solution, the capacity availability obligation parameters are mapped to a schedulable state dictionary with hourly granularity, so that each time unit carries explicit discharge permission, power limit, and SOC boundary markers. This dictionary-like structure transforms contract terms from textual semantics into Boolean and numerical constraints that can be queried by the program on a time-by-time basis. Subsequent conflict detection can be completed by comparing time-by-time, without repeatedly parsing the original contract text, thereby reducing the computational complexity of policy verification.

[0010] In some embodiments of the first aspect, the step of obtaining the day-ahead electricity price time series and generating a preliminary charge-discharge strategy based on the physical parameters and the day-ahead electricity price time series specifically includes: obtaining hourly forecast electricity prices or clearing electricity price data of the day-ahead market to form the day-ahead electricity price time series; calculating the current day's average electricity price and standard deviation of the electricity price, extracting price point segments that are higher than a set deviation rate, and recording the time position corresponding to the price point segment as the preliminary discharge position; and generating the preliminary charge-discharge strategy by combining the preliminary discharge position and the physical parameters.

[0011] By adopting the above technical solution, the discharge decision is based on statistical significance rather than absolute thresholds, enabling it to adapt to the fluctuations in electricity prices on different days. Furthermore, by combining physical parameters with power and energy feasibility constraints on the initial discharge location, the output initial charge-discharge strategy is ensured to be electrically executable. This provides a physically compliant benchmark strategy for subsequent contract conflict detection, reducing the number of conflicts and iterations in the subsequent adjustment phase.

[0012] In conjunction with some embodiments of the first aspect, in some embodiments, the physical parameter includes at least the current SOC, minimum SOC limit, maximum discharge power, minimum charging price, and technology cycle limit.

[0013] By adopting the above technical solutions, the generated preliminary charge and discharge strategy can meet the requirements of equipment safety while taking into account operational rationality and battery health, thus avoiding the blind spots of strategy under single-dimensional constraints.

[0014] In conjunction with some embodiments of the first aspect, in some embodiments, the step of adjusting the initial charge / discharge strategy to obtain a final adjustable strategy plan table, constrained by the medium-to-long-term capacity contract information, specifically includes: comparing the strategy period in the initial charge / discharge strategy with the daily medium-to-long-term locked block table to determine whether there are any violations or conflicts, and generating a conflict list; processing the conflicting strategies in the conflict list according to preset adjustment rules, and redistributing the available energy generated by removing the conflicting strategies; and determining the final adjustable strategy plan table based on the strategies in the initial charge / discharge strategy that meet the contract conditions.

[0015] By adopting the above technical solutions, conflict identification is transformed from scattered manual inspections to one-time batch automated detection. The available energy generated after the conflict strategy is eliminated is redistributed to ensure that the system does not waste the planned charging energy due to compliance cuts. The final adjustable strategy plan maximizes the use of the daily schedulable energy under the premise of contract security, taking into account both performance certainty and energy scheduling efficiency.

[0016] In conjunction with some embodiments of the first aspect, in some embodiments, the criteria for determining whether there is a violation or conflict include at least one of the following: the discharge behavior in the initial charge-discharge strategy falls within the non-discharge retention period defined by the medium-to-long-term capacity contract information; the discharge behavior in the initial charge-discharge strategy leads to premature release, causing the independent energy storage power station's SOC to fail to meet the preset minimum power output requirement during the capacity lock-in period; the discharge behavior in the initial charge-discharge strategy exists within the capacity lock-in period, and the discharge power is not limited to the remaining power limit allowed by the medium-to-long-term capacity contract information; the charging behavior in the initial charge-discharge strategy is triggered prematurely during the capacity lock-in period, and the high-power compression time affects the subsequent release.

[0017] By adopting the above technical solution, multi-dimensional condition collaboration covers two types of scenarios: single-time period violations and cross-time period cascading violations, avoiding the omission of hidden conflicts by a single rule.

[0018] In conjunction with some embodiments of the first aspect, in some embodiments, the step of processing the conflict strategy according to preset adjustment rules and redistributing the available energy generated by eliminating the conflict strategy specifically includes: if the medium-to-long-term capacity contract information has a prohibited trading period, then the conflict strategy for that prohibited trading period is eliminated; if the medium-to-long-term capacity contract information has flexible capacity execution, then the planned power for the corresponding period is reduced and limited to the allowable remaining range; if the conflict strategy is unrewriteable and affects the SOC status of the capacity-locked period, then the pre-adjustment strategy is forcibly adjusted so that the SOC is restored to above the lockout standard line; conflict strategies that cannot be avoided and are non-compliant are discarded; for the available energy generated by the elimination or discarding of conflict strategies, a moderate electricity price period is determined as a supplementary execution point during non-capacity-locked periods for filling the gap, and the daily available energy efficiency is re-evaluated.

[0019] By adopting the above technical solution, conflicts are handled in a tiered manner according to the degree of contract rigidity: prohibited periods are directly eliminated, flexible periods are retained with reduced power, and non-rewriteable periods are restored to compliance through pre-emptive SOC compensation, forming a gradient response mechanism from hard constraints to soft constraints. The energy released by elimination or discard is directed to the moderate price range of the non-locked-out periods, which not only recovers the value of energy but also avoids the concentration of power exceeding the limit in the high-price range, thus maintaining a high level of daily energy utilization rate after compliance trimming.

[0020] In a second aspect, this application provides a converged trading system, which includes: one or more processors and a memory; the memory is coupled to the one or more processors, and the memory is used to store computer program code, the computer program code including computer instructions, and the one or more processors call the computer instructions to cause the converged trading system to perform the method described in the first aspect and any possible implementation thereof.

[0021] Thirdly, this application provides a computer-readable storage medium including instructions that, when executed on a fusion trading system, cause the fusion trading system to perform the method described in the first aspect and any possible implementation thereof.

[0022] Fourthly, this application provides a computer program product, including a computer program that, when run on a fusion trading system, causes the fusion trading system to perform the methods described in the first aspect and any possible implementation thereof. Attached Figure Description

[0023] Figure 1 This is a schematic diagram of a scenario for a medium-to-long-term and multi-day integrated trading method for independent energy storage power stations in the embodiments of this application;

[0024] Figure 2 This is a flowchart illustrating a medium-to-long-term and multi-day fusion trading method for independent energy storage power stations in an embodiment of this application.

[0025] Figure 3 This is a schematic diagram of the physical device structure of the fusion transaction system in the embodiments of this application. Detailed Implementation

[0026] The terminology used in the following embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. The singular expressions “a,” “an,” “the,” “the,” “the,” and “this” are intended to include the plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this application refers to and includes any or all possible combinations of one or more of the listed items.

[0027] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0028] The following describes a method for medium- to long-term and multi-day fusion trading for independent energy storage power stations, using a scenario from this embodiment as an example. Please refer to... Figure 1 , Figure 1 This is a schematic diagram of a scenario for a medium-to-long-term and multi-day integrated trading method for independent energy storage power stations in the embodiments of this application.

[0029] exist Figure 1In this scenario, independent energy storage power stations provide physical parameters to the energy storage strategy and reporting management system, while the power trading center / market data source provides day-ahead electricity price time series data. Simultaneously, medium- and long-term capacity contract information serves as an external constraint input. Upon receiving these inputs, the energy storage strategy and reporting management system internally generates a daily medium- and long-term locked block table and a preliminary charge-discharge strategy in parallel. These two are then merged to obtain the final adjustable strategy plan table. The final adjustable strategy plan table is then converted to generate day-ahead electricity reporting data, which is submitted to the grid dispatching and trading platform to complete the reporting. This scenario demonstrates that the energy storage strategy and reporting management system integrates medium- and long-term capacity contract constraints and day-ahead spot market trading strategies into a unified decision-making process. Under the premise of ensuring contract performance security, it automatically generates day-ahead electricity reporting data that meets both physical and contractual constraints, improving the decision-making efficiency of independent energy storage power stations participating in multi-market transactions.

[0030] For ease of understanding, the method provided in this implementation is described in process below. Please refer to [link / reference]. Figure 2 This is a flowchart illustrating a medium-to-long-term and multi-day fusion trading method for independent energy storage power stations in an embodiment of this application.

[0031] S101. Obtain the physical parameters and medium- to long-term capacity contract information of independent energy storage power stations;

[0032] Among them, physical parameters refer to the set of technical indicators characterizing the dispatch capability boundary of the independent energy storage power station, which may include at least the current state of charge (SOC), minimum SOC limit, maximum discharge power, minimum charging price, and technology cycle limit. The current SOC is used to represent the proportion of remaining available energy of the independent energy storage power station at the time of strategy generation; the minimum SOC limit is used to represent the proportion of energy that the system is allowed to discharge to the lower limit; the maximum discharge power is used to represent the upper limit of the power that the independent energy storage power station can output in a single time period; the minimum charging price is used to represent the lower limit threshold of the price at which the system is allowed to perform charging operations; and the technology cycle limit is used to represent the maximum number of charge-discharge cycles that the independent energy storage power station is allowed to perform in a single day.

[0033] Medium- to long-term capacity contract information refers to a structured set of data regarding the capacity availability obligations undertaken by the independent energy storage power station during the current execution period. This data may include the capacity contract number, validity period information, capacity lock-in period, minimum release power, minimum state maintenance requirements, behavioral restrictions, and contract default determination rules. The capacity contract number uniquely identifies the currently executing contract; the validity period information indicates the start and end date range of the contract execution; the capacity lock-in period indicates the specific hourly intervals during which capacity availability must be maintained; the minimum release power indicates the minimum power that the independent energy storage power station must be able to output at any time during the capacity lock-in period; the minimum state maintenance requirements indicate the minimum value that the State of Charge (SOC) must not fall below during the capacity lock-in period; the behavioral restrictions indicate the contractual constraints on the independent energy storage power station's participation in other markets or execution of other dispatching activities during the lock-in period; and the contract default determination rules indicate the specific conditions that trigger a contract default determination, such as penalties and credit impacts that may result from early capacity release.

[0034] The integrated trading system connects to the energy management system (EMS) of the independent energy storage power station via a data interface to read the physical parameters at the current moment. Simultaneously, the integrated trading system connects to the capacity market trading system or operation scheduling platform via the same data interface to obtain and store the medium- and long-term capacity contract information of the independent energy storage power station within the current execution cycle. For example, the integrated trading system reads that the current SOC is 85%, the minimum SOC limit is 20%, the maximum discharge power is 1000kW, the minimum charging price is 0.25 yuan / kWh, and the technology cycle limit is 3 times per day; it also obtains that the capacity lock-in period is from 15:00 to 21:00 daily, the minimum release power is 1MW, and the minimum state maintenance requirement is an SOC of no less than 30%.

[0035] Through this step, the integrated trading system has a complete grasp of the dispatch capacity boundaries and contractual obligations of the independent energy storage power station before the strategy is generated. This provides a complete parameter basis for the subsequent generation of the lock block table and the initial charge and release strategy, avoiding deviations in strategy generation or omissions in contract constraints due to missing data.

[0036] S102. Generate a daily medium- and long-term locked block table based on the medium- and long-term capacity contract information;

[0037] This step is executed during the initial phase of each trading day's strategy generation cycle. Its purpose is to transform the textual terms of medium- to long-term capacity contracts into a structured constraint table that can be queried by the program on a time-by-time basis.

[0038] The converged trading system first extracts the capacity availability obligation parameters undertaken by the independent energy storage power station in the current cycle from the medium- and long-term capacity contract information. Specifically, it reads the available capacity value, the start and end time of the capacity lock-in period, the power maintenance value, and the threshold settings in the alarm conditions. The converged trading system encapsulates the extracted capacity availability obligation parameters into the contract strategy management module for unified management, and then generates a temporary scheduling template based on the capacity lock-in requirements of each capacity lock-in period.

[0039] During the generation of temporary scheduling templates, the merging trading system analyzes the capacity locking requirements for each capacity-locked period, determining whether discharge operations are completely prohibited during that period, whether partial discharge below the power maintenance value is allowed, and the minimum SOC level that must be maintained. These rules are then written into the corresponding period record in the temporary scheduling template. Based on the temporary scheduling template and the next day's date, the merging trading system determines whether the next day falls within the valid period of the medium- to long-term capacity contract information. If it does, execution continues; otherwise, a blank locked block table allowing free scheduling throughout the entire period is generated. After confirming that the next day is within the valid period, the merging trading system subdivides the next day's timeline to hourly granularity, dividing the 24 hours into 24 independent hourly periods.

[0040] The converged trading system constructs a schedulable state dictionary at the hourly granularity, combining the constraint rules of the corresponding time period in the temporary scheduling template. The schedulable state dictionary refers to the structured record corresponding to each hourly granularity, which can include three fields: whether discharge is allowed, discharge intensity limit, and whether the SOC safety boundary must be maintained. For example, for hours falling within the capacity-locked period, whether discharge is allowed is set to "No", the discharge intensity limit is set to zero, and whether the SOC safety boundary must be maintained can be set to "Yes". For hours in the buffer zone before the capacity-locked period (i.e., within two hours before the start time of the capacity-locked period), whether discharge is allowed can be set to "Yes", the discharge intensity limit is set to the maximum discharge power, and whether the SOC safety boundary must be maintained is set to "Yes", indicating that although discharge is allowed, it must be ensured that the SOC after discharge can still meet the corresponding SOC level requirement when entering the capacity-locked period. For other non-locked periods, whether discharge is allowed is set to "Yes", the discharge intensity limit is set to the maximum discharge power, and whether the SOC safety boundary must be maintained is set to "No".

[0041] Simultaneously, the fused transaction system adds alarm trigger flags to the schedulable state dictionary based on alarm conditions. When a planned operation during a certain period may cause the SOC to approach the threshold set by the alarm conditions, this flag is activated to alert subsequent steps to the risks. After the schedulable state dictionary with 24-hour granularity is constructed, the fused transaction system arranges it in chronological order to generate a time-period lock control table as the final output of the daily medium- and long-term locked block table.

[0042] Please refer to Table 1 below, which shows an example of the daily medium-to-long-term locked block table generated by the converged trading system based on medium-to-long-term capacity contract information during the capacity lock period from 15:00 to 21:00.

[0043] Time period Dischargeable .... Limitations 00：00–07：00 yes .... Unlocked, recommended strategies can be freely configured. 08：00–10：00 yes .... Discharge is possible, but auxiliary service priority should be considered. .... .... .... .... 15：00–21：00 no .... Capacity lockout zone, prohibiting any active discharge behavior. 21：00–24：00 yes .... It is recommended to restore the SOC in preparation for the next day's lockdown.

[0044] Table 1

[0045] The schedulable state dictionary records corresponding to the buffer transition period between 10:00 and 15:00 are not shown in Table 1 above. As can be seen from Table 1, the schedulable state dictionary corresponding to each hourly granularity clearly indicates whether discharge is allowed during that period, the discharge intensity limit, and whether the SOC safety boundary must be maintained (not shown in the table). Among them, the periods within the capacity-locked period are marked as prohibiting active discharge and requiring the SOC safety boundary to be maintained, while the periods without lockout allow free scheduling.

[0046] S103. Obtain the day-ahead electricity price time series, and generate a preliminary charging and discharging strategy based on the physical parameters and the day-ahead electricity price time series;

[0047] Among them, the day-ahead electricity price time series refers to the time series data structure formed by arranging the hourly predicted electricity price or clearing electricity price data of each period of the next day obtained by the integrated trading system from the day-ahead market in chronological order; the preliminary discharge position refers to the set of time positions corresponding to the price point segment, indicating the preliminary judgment of the appropriate discharge period.

[0048] The fusion trading system executes this step after completing the daily medium- and long-term locked block table generation. The purpose is to identify high-yield discharge periods based on the day-ahead market price signal and generate an executable preliminary charge and discharge scheduling scheme in combination with physical parameter constraints.

[0049] The integrated trading system first obtains hourly forecasted electricity prices or clearing electricity price data for the day-ahead market. This data comes from the clearing electricity prices for each time period of the next day released by the power trading center or the day-ahead electricity price forecast values ​​generated by the internal forecasting module of the integrated trading system. The data covers all 24 hours of the next day, with each time period corresponding to an electricity price value. After being arranged in chronological order, the day-ahead electricity price time series is formed.

[0050] After obtaining the day-ahead electricity price time series, the converged trading system calculates the average electricity price for all time periods of the current day. This is achieved by summing the electricity price values ​​for all 24 time periods and dividing by 24. Next, it calculates the standard deviation of the electricity price, which is the sum of the squares of the differences between the electricity price for each time period and the average price, divided by the number of time periods, and then taking the square root. Based on the average and standard deviation of the electricity price, the converged trading system uses a set deviation rate as a screening threshold. It then checks whether the electricity price for each time period is higher than the product of the average price and the set deviation rate and the standard deviation. Time periods that meet this condition are extracted as price segments.

[0051] The integrated trading system records the time positions corresponding to all price segments as the initial discharge positions, which represent the optimal discharge time window based on pure price signals. The integrated trading system combines the initial discharge positions and physical parameters to generate an initial charge / discharge strategy. During this generation process, the integrated trading system determines the upper limit of discharge power for each discharge period based on the rated power in the physical parameters, and determines the total number of sustainable discharge periods based on the available capacity. When the total discharge volume of the periods included in the initial discharge position exceeds the available capacity, the periods within the available capacity range are selected according to the electricity price from high to low as the final discharge periods. The charging period is selected from the remaining non-discharge periods, choosing the continuous or discontinuous period with the lowest electricity price. The charging power is determined based on the rated power and charging efficiency, and the total charging volume must meet the energy balance requirement of the total discharge volume divided by the discharge efficiency and then divided by the charging efficiency.

[0052] The integrated trading system organizes the determined charging period, charging power, discharging period, and discharging power in chronological order to output a preliminary charging and discharging strategy. An exemplary preliminary charging and discharging strategy suggestion table is shown in Table 2.

[0053] 01：00-05：00 Charge 900kW 0.27 During off-peak electricity pricing periods, energy storage is used to support daytime power consumption demand. 09：00-11：00 Discharge 1000kW 0.85 Prioritize power discharging during periods of high electricity prices for optimal returns. 13：00-14：00 Discharge 800kW 0.81 Electricity prices are moderate, and discharge can be carried out under conditions of sufficient capacity. 15：00-21：00 Discharge 900kW 0.88 If it falls into the medium- to long-term capacity lock-in range, subsequent steps will be used for verification and removal.

[0054] Table 2

[0055] Table 2 above is a schematic diagram of the preliminary charging and discharging strategy generated based on electricity price screening and energy storage physical parameter constraints. The table records the operation type, execution power, corresponding electricity price and strategy description for each time period. Only typical time periods are listed in the table. The complete table contains the time series records for all 24 hours of the next day. For other time periods, the corresponding operation strategies are generated according to the same electricity price screening and capacity constraint logic.

[0056] S104. Using the medium- and long-term capacity contract information as a constraint, adjust the initial charge and discharge strategy to obtain the final adjustable strategy plan.

[0057] The merging trading system executes this step after generating the initial charge / discharge strategy. Its purpose is to ensure that the final output scheduling scheme does not violate the capacity availability obligations stipulated in the medium- to long-term capacity contract information. The merging trading system first compares the strategy period of each operation in the initial charge / discharge strategy with the daily medium- to long-term locked block table on a time-by-time basis. During the comparison, the merging trading system reads the schedulable state dictionary at the corresponding hourly granularity in the daily medium- to long-term locked block table to determine whether the operations arranged by the initial charge / discharge strategy during that time period contradict the constraints stipulated in the three fields: whether discharge is possible, discharge intensity limits, and whether the SOC safety boundary must be maintained. The merging trading system then summarizes all violations and conflicts to generate a conflict list.

[0058] Specifically, when the fusion trading system compares the initial charge / discharge strategy with the daily medium- and long-term locked block table on a time-by-time basis, it identifies violations and conflicts based on at least one of the following four criteria:

[0059] 1. The judgment condition is that the discharge behavior in the initial charge-discharge strategy falls within the non-discharge retention period defined by the medium- and long-term capacity contract information. The converged trading system reads the set of all time periods marked "no" for discharge in the daily medium- and long-term locked block table, and checks one by one whether there are any discharge operations scheduled within these time periods in the initial charge-discharge strategy. If the initial charge-discharge strategy arranges any non-zero power discharge operation within the non-discharge retention period, regardless of the discharge power, it is judged as a violation and conflict, because the entire capacity of the independent energy storage power station must be reserved for fulfilling contractual obligations during this period, and any active discharge constitutes a direct violation of the capacity availability commitment.

[0060] 2. The judgment condition is that the discharge behavior in the initial charge-discharge strategy leads to premature release, causing the SOC of the independent energy storage power station to fail to meet the preset minimum power output requirement during the capacity lock-in period. Starting from the initial SOC, the converged trading system calculates the SOC change trajectory after the execution of the initial charge-discharge strategy in chronological order. At the start of the capacity lock-in period, it checks whether the current SOC is not lower than the minimum SOC threshold corresponding to the product of the preset minimum power output requirement and the lock-in period duration. If the SOC at the start of the capacity lock-in period is lower than this threshold, the converged trading system retrospectively identifies the discharge operation that caused the insufficient SOC. Discharge operations performed before the lock-in period and within the buffer period marked as "yes" for whether the SOC safety boundary must be maintained are judged as violations, because although the discharge behavior did not directly occur within the lock-in period, its premature release indirectly resulted in the contractual obligations not being met.

[0061] 3. The judgment condition is that the discharge behavior in the initial charge / discharge strategy exists within the capacity lock-up period, and the discharge power is not limited to the remaining power limit allowed by the medium- and long-term capacity contract information. The converged trading system determines that under certain special contract terms, discharge is not completely prohibited during the capacity lock-up period, but rather the use of remaining power for market trading is allowed provided that the contract's capacity reservation obligation is met. The converged trading system reads the reserved power value agreed in the medium- and long-term capacity contract information, calculates the remaining power limit as the rated power minus the reserved power value, and checks whether the discharge power arranged by the initial charge / discharge strategy during the capacity lock-up period exceeds the remaining power limit. If the discharge power exceeds the remaining power limit, it is judged as a violation and conflict, because the excess will occupy the power share required to be reserved by the contract, thus violating the capacity availability obligation.

[0062] 4. The judgment condition is that the charging behavior in the initial charge-discharge strategy is triggered prematurely within the capacity lock-in period, and the high-power compression time affects the subsequent release. The converged trading system analyzes whether the initial charge-discharge strategy has arranged charging operations within the capacity lock-in period. If charging operations exist, the power level and duration of the charging operation are further evaluated. When the charging operation is executed at a high power close to the rated power, the battery enters the constant voltage charging stage in the high SOC range, resulting in a significant decrease in the charging rate. The actual charging time exceeds the expected time calculated based on constant power. This time extension effect will compress the remaining time window available for responding to dispatch instructions within the capacity lock-in period. The converged trading system calculates the remaining lock-in period length after the high-power charging is completed. If the remaining length is insufficient to support the continuous output time required by the preset minimum power output requirement, it is judged as a violation and conflict behavior, because although the charging arrangement itself does not consume capacity, its time occupation effect indirectly weakens the power output capability of the independent energy storage power station within the lock-in period.

[0063] By combining the above four judgment conditions, the integrated trading system can comprehensively identify various violations and conflicts between the initial charge and discharge strategy and the medium- and long-term capacity contract information. This covers a variety of conflict scenarios, including direct violations of the no-discharge constraint, indirect causes of insufficient SOC, power overruns, and time window compression. This ensures the completeness of the conflict list and provides a sufficient information basis for subsequent adjustment steps.

[0064] In some embodiments, after generating a conflict list, the fusion trading system processes each conflicting strategy in the list according to priority based on preset adjustment rules, while simultaneously collecting and redistributing the available energy generated during the processing. Specifically:

[0065] For prohibited trading periods explicitly forbidden by medium- and long-term capacity contracts, the integrated trading system identifies all conflicting strategies falling within the prohibited trading periods from the conflict list and performs a direct removal operation on these conflicting strategies. The removal operation sets the charging or discharging power of the period to zero, and the originally planned discharge energy corresponding to the period is marked as available energy and added to the energy pool to be redistributed.

[0066] For medium- and long-term capacity contracts with flexible capacity execution, the converged trading system identifies strategies marked as conflicting in the conflict list due to discharge power exceeding the remaining power limit. The system reads the contract's reserved power value for that period, calculates the allowable remaining range as the rated power minus the reserved power value, and reduces the planned power for that period from its original value to the upper limit of the allowable remaining range. The energy difference corresponding to the reduction—the difference between the original planned power and the adjusted power multiplied by the period duration—is marked as available energy and added to the energy pool awaiting reallocation. Through this process, the converged trading system ensures that the contract's capacity reservation obligation is met without completely abandoning trading opportunities for that period.

[0067] For conflicting strategies that cannot be rewritten and affect subsequent SOC states, including those during capacity-locked periods (e.g., SOC impacting operations from 15:00 to 21:00), the fused trading system determines that some conflicting strategies are located in the buffer zone before the capacity-locked period, and their discharge behavior causes the SOC to fall below the lockout threshold upon entering the lockout period. For such conflicting strategies, the fused trading system executes a forced adjustment of the preceding strategy. Specific methods include reducing the discharge power of adjacent periods before the lockout period, adding supplementary charging operations during low-price periods before the lockout period, or shifting the discharge operations before the lockout period to an earlier period to allow sufficient time for recharging after discharge. The fused trading system gradually adjusts the preceding strategy until the SOC trajectory calculation shows that the SOC at the start of the lockout period is not lower than the lockout threshold. The reduced discharge energy during the adjustment process is also marked as available energy and added to the energy pool to be redistributed.

[0068] The converged trading system discards any non-compliant strategies that cannot be avoided beyond the three scenarios mentioned above. After handling all conflicting strategies, it aggregates the total available energy in the energy pool awaiting reallocation. During non-capacity-locked periods, it selects periods where no discharge operations are currently scheduled or where the discharge power has not reached the rated power limit as candidate periods. It calculates the electricity price level for each candidate period and identifies periods with moderate electricity prices as supplementary execution points. The converged trading system selects periods with moderate electricity prices rather than the highest-price periods because the highest-price periods are usually already occupied in the initial charge / discharge strategy and their power has reached the limit, while periods with moderate electricity prices have power margins or have not yet been scheduled for operation. The converged trading system allocates available energy to each supplementary execution point in descending order of electricity price. The allocated power at each supplementary execution point does not exceed the rated power minus the remaining discharge power for that period, and the total allocated power does not exceed the total available energy.

[0069] After the integrated trading system completes the energy redistribution, it re-evaluates the available energy efficiency for the day. If the available energy efficiency for the day is lower than the minimum energy utilization threshold, an energy utilization alarm flag can be generated and attached to the final adjustable strategy plan table, prompting operators to pay attention to the low energy utilization rate caused by contract constraints for the day.

[0070] Finally, the fusion trading system merges the original operations in the initial charge-discharge strategy that were not marked as conflicting strategies with the new operations after adjustment and reallocation, and arranges them in chronological order to determine the final adjustable strategy plan. An example final adjustable strategy plan is shown in Table 3.

[0071] 01：00-05：00 Charge 900kW YES YES No contractual obligations, normal charging and energy storage 09：00-11：00 Discharge 1000kW YES YES Non-locked intervals, those without conflicts are executed first. 13：00-14：00 Discharge 800kW YES YES Between buffers, SOC checks satisfy conflict-free conditions. 15：00-21：00 Discharge —— NO —— Active discharge is prohibited during the contract capacity lock-in period.

[0072] Table 3

[0073] Table 3 above is an exemplary representation of the final adjustable strategy plan. It shows the charging and discharging execution arrangements for independent energy storage power stations during different time periods within a full trading day after conflict detection and adjustment. Table 3 includes six fields: time period, operating mode, execution command power (after limit), executable flag, fault tolerance check (SOC boundary), and restriction description. Although the period from 15:00 to 21:00 involves discharging operations, the executable flag is set to NO because this period is a contract capacity lock-up period where active discharging is prohibited; therefore, the corresponding execution command power and fault tolerance check are both marked as empty. This table clearly demonstrates the results of the converged trading system's handling of conflict strategies and the restrictive effect of contract constraints on charging and discharging scheduling.

[0074] S105. Based on the final adjustable strategy plan, generate daily electricity reporting data.

[0075] Among them, the day-ahead electricity declaration data refers to the structured declaration document generated by the integrated trading system based on all strategy records with the executable flag set to "YES" in the final adjustable strategy plan table, in accordance with the day-ahead electricity market declaration format requirements.

[0076] The integrated trading system iterates through all records in the final adjustable strategy plan table, filters strategy records with the executable flag set to "YES," and extracts their time period, operation mode, and execution command power fields. Based on the day-ahead electricity market's declaration format requirements, the integrated trading system converts records with the operation mode of "discharging" into positive electricity declaration data, and records with the operation mode of "charging" into negative electricity declaration data or electricity purchase declaration data. It also aligns the time period boundaries according to the market's required time granularity and rounds the execution command power values ​​according to power accuracy requirements. The integrated trading system also appends the fault tolerance verification results and limitation description fields from the final adjustable strategy plan table as supplementary information to the remarks area of ​​the declaration data for operators to confirm before submission. Finally, the integrated trading system encapsulates the generated day-ahead electricity declaration data into a standard file format conforming to market interface requirements and pushes it to the day-ahead electricity market trading platform to complete the declaration submission.

[0077] In this embodiment, the performance obligations of medium- and long-term capacity contracts and the day-ahead spot market trading strategy are optimized in the same decision-making process. This effectively solves the problem in the prior art where independent energy storage power stations, when participating in day-ahead spot market trading, lack systematic constraints and verification of the lock-in period of medium- and long-term capacity contracts, leading to conflicts between trading strategies and contractual obligations, and thus causing contract default risks or market revenue losses. This achieves the technical effect of maximizing the day-ahead spot market trading revenue of independent energy storage power stations while strictly ensuring the security of medium- and long-term capacity contract performance.

[0078] The fusion transaction system in this application embodiment is described below from the perspective of hardware processing. Please refer to [link / reference needed]. Figure 3 This is a schematic diagram of the physical device structure of the fusion transaction system in this application embodiment.

[0079] It should be noted that, Figure 3 The structure of the fusion trading system shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0080] like Figure 3 As shown, the converged trading system includes a Central Processing Unit (CPU) 301, which can perform various appropriate actions and processes based on programs stored in Read-Only Memory (ROM) 302 or programs loaded from storage section 308 into Random Access Memory (RAM) 303, such as performing the methods described in the above embodiments. The RAM 303 also stores various programs and data required for system operation. The CPU 301, ROM 302, and RAM 303 are interconnected via a bus 304. An Input / Output (I / O) interface 305 is also connected to the bus 304.

[0081] The following components are connected to I / O interface 305: input section 306 including audio input devices, push-button switches, etc.; output section 307 including a liquid crystal display (LCD) and audio output devices, indicator lights, etc.; storage section 308 including a hard disk, etc.; and communication section 309 including a network interface card such as a LAN (Local Area Network) card, modem, etc. Communication section 309 performs communication processing via a network such as the Internet. Drive 310 is also connected to I / O interface 305 as needed. Removable media 311, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 310 as needed so that computer programs read from them can be installed into storage section 308 as needed.

[0082] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program including a computer program for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 309, and / or installed from removable medium 311. When the computer program is executed by central processing unit (CPU) 301, it performs the various functions defined in this application.

[0083] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0084] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those shown in the drawings.

[0085] Specifically, the fusion trading system of this embodiment includes a processor and a memory. The memory stores a computer program. When the computer program is executed by the processor, it implements the medium- and long-term and multi-day fusion trading method for independent energy storage power stations provided in the above embodiment.

[0086] In another aspect, this application also provides a computer-readable storage medium, which may be included in the fusion trading system described in the above embodiments; or it may exist independently and not assembled into the fusion trading system. The storage medium carries one or more computer programs that, when executed by a processor of the fusion trading system, cause the fusion trading system to implement the medium- and long-term and multi-day fusion trading method for independent energy storage power stations provided in the above embodiments.

[0087] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit it. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

[0088] As used in the above embodiments, depending on the context, the term "when..." can be interpreted as meaning "if...", "after...", "in response to determining...", or "in response to detecting...". Similarly, depending on the context, the phrase "when determining..." or "if (the stated condition or event) is interpreted as meaning "if determining...", "in response to determining...", "when (the stated condition or event) is detected", or "in response to detecting (the stated condition or event)".

[0089] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This program can be stored in a computer-readable storage medium, and when executed, it can include the processes described in the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A method for medium- and long-term and multi-day integrated trading for independent energy storage power stations, characterized in that, The method includes: Obtain physical parameters and medium- to long-term capacity contract information for independent energy storage power stations; A daily table of medium- and long-term locked blocks is generated based on the medium- and long-term capacity contract information. Obtain the day-ahead electricity price time series, and generate a preliminary charging and discharging strategy based on the physical parameters and the day-ahead electricity price time series; Using the medium- and long-term capacity contract information as a constraint, the initial charge and discharge strategy is adjusted to obtain the final adjustable strategy plan. Based on the final adjustable strategy plan table, generate daily electricity reporting data.

2. The method according to claim 1, characterized in that, The steps for generating a daily medium-to-long-term locked block table based on the medium-to-long-term capacity contract information specifically include: Obtain the capacity availability obligation parameters of the independent energy storage power station in the current period from the medium and long-term capacity contract information. The capacity availability obligation parameters include at least the available capacity, capacity lock-in period, power maintenance and alarm conditions. The capacity availability obligation parameters are encapsulated into the contract strategy management module, and a temporary scheduling template is generated based on the capacity locking requirements for each capacity locking period. Based on the temporary scheduling template and the date of the next day, the daily timeline is subdivided to the hourly level; A schedulable state dictionary is constructed at each hourly granularity, and a time period lock control table is generated as the daily medium-to-long-term lock block table. The schedulable state dictionary includes whether discharge is possible, discharge intensity limits, and whether the SOC safety boundary must be maintained.

3. The method according to claim 1, characterized in that, The step of obtaining the day-ahead electricity price time series and generating a preliminary charging and discharging strategy based on the physical parameters and the day-ahead electricity price time series specifically includes: Obtain hourly forecast or clearing electricity price data for the day-ahead market to form the day-ahead electricity price time series; Calculate the current day's average electricity price and standard deviation of electricity price, extract price point segments that are higher than the set deviation rate, and record the time position corresponding to the price point segment as the initial discharge position; The initial charge-discharge strategy is generated by combining the initial discharge location and the physical parameters.

4. The method according to claim 1 or 3, characterized in that, The physical parameters include at least the current SOC, minimum SOC limit, maximum discharge power, minimum charging price, and technology cycle limit.

5. The method according to claim 1, characterized in that, The steps of adjusting the initial charge / discharge strategy to obtain the final adjustable strategy plan table, based on the aforementioned medium- and long-term capacity contract information, specifically include: The strategy period in the initial charge and release strategy is compared with the daily medium- and long-term locked block table to determine whether there are any violations or conflicts, and a conflict list is generated. For the conflict strategies in the conflict list, the conflict strategies are processed according to preset adjustment rules, and the available energy generated by removing the conflict strategies is redistributed. The final adjustable strategy plan is determined based on the strategies that meet the contract conditions in the initial charge / discharge strategy.

6. The method according to claim 5, characterized in that, The criteria for determining whether a violation or conflict exists include at least one of the following: The discharge behavior in the initial charge-discharge strategy falls within the non-discharge retention period defined by the medium- and long-term capacity contract information; The discharge behavior in the initial charge-discharge strategy leads to premature release, causing the SOC of the independent energy storage power station to fail to meet the preset minimum power output requirement during the capacity lock-in period. The discharge behavior in the initial charge-discharge strategy exists within the capacity lock-in period, and the discharge power is not limited to the remaining power limit allowed by the medium- and long-term capacity contract information. The charging behavior in the initial charge-discharge strategy is triggered in advance during the capacity lock period, and the high-power compression time affects the subsequent release.

7. The method according to claim 5, characterized in that, The step of processing the conflict strategy according to the preset adjustment rules and redistributing the available energy generated by eliminating the conflict strategy specifically includes: If the medium- and long-term capacity contract information has a prohibited trading period, then the conflict strategy for the prohibited trading period will be removed; If the medium- and long-term capacity contract information has flexible capacity execution, the planned power for the corresponding period will be reduced and limited to the allowable remaining range; If the conflict strategy is unchangeable and affects the SOC state during the capacity lock period, then the preceding strategy is forcibly adjusted so that the SOC is restored to above the lockout standard line. Discard any conflict strategies that are unavoidable and non-compliant. For available energy that is removed or discarded due to conflict strategies, a period with moderate electricity prices is identified during non-capacity-locked periods as a supplementary execution point for filling the gap, and the efficiency of available energy on that day is re-evaluated.

8. A converged trading system, characterized in that, The fusion trading system includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code including computer instructions, and the one or more processors call the computer instructions to cause the fusion trading system to perform the method as described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that, When the instruction is executed on the fusion trading system, it causes the fusion trading system to perform the method as described in any one of claims 1-7.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is run on the fusion trading system, it causes the fusion trading system to perform the method as described in any one of claims 1-7.

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