Method and device for determining optimal day-ahead declaration curve, equipment and medium

Abstract

The application discloses a kind of optimal day-ahead declaration curve determination method, optimal day-ahead declaration curve determination device, optimal day-ahead declaration curve determination equipment and computer readable storage medium, belong to the technical field of battery energy storage, in current period, the first day-ahead declaration curve and the second day-ahead declaration curve needed in next period are calculated, and the first cumulative income of the first day-ahead declaration curve corresponding to the predicted electricity price of last period and the second cumulative income of the second day-ahead declaration curve corresponding to the average real clearing electricity price of the period before last are determined in current period based on the predicted electricity price of last period, the target electricity price corresponding to the larger income of the cumulative income of both is used to maximize income optimization in current period, to obtain the optimal day-ahead declaration curve of every day in current period, so that the income of each period is maximum.

Description

Technical Field

[0001] This invention relates to the technical field of battery energy storage, and in particular to a method, apparatus, device, and computer-readable storage medium for determining the optimal day-ahead reporting curve. Background Technology

[0002] Currently, with the continuous development of energy storage technology, battery energy storage systems, under the existing peak-valley electricity pricing mechanism, can minimize the electricity purchase costs for users through peak-valley pricing and capacity management. The existing energy storage management system operates on a fixed peak-valley electricity price basis, with clear price and time characteristics, simple judgment logic, and no need for dynamic determination of energy storage operation mode. However, with the advancement of electricity market reform, users are beginning to sign long-term power purchase agreements with electricity companies, and electricity prices are beginning to fluctuate in a market-driven manner.

[0003] Electricity spot trading involves physical delivery of the electricity upon payment. The spot market comprises several components, including the energy market, capacity market, frequency regulation market, and reserve market, with the energy market having the strongest impact on electricity prices. The energy market is further divided into three parts: medium- and long-term trading, day-ahead trading, and real-time trading. The day-ahead trading market is the primary platform for the electricity spot market. It determines the generating capacity of the units for the following day in advance, adjusting the required power generation and consumption curves to align with the medium- and long-term contracts in the medium- and long-term trading market. This ensures a basic balance of power supply and demand for the following day, while also meeting grid security constraints. It provides a platform for market participants to fine-tune their power generation and consumption plans after the medium- and long-term trading market closes, addressing various forecast deviations and unplanned situations. The real-time trading market, on the day of operation, approximates the real-time operating conditions of the system, accurately reflecting the short-term resource scarcity and congestion levels. This allows for real-time power balance and safe grid operation.

[0004] While the generating capacity of the units can be roughly determined a day in advance to adjust for significant deviations in the required power generation and consumption curves and medium- and long-term contracts in the medium- and long-term trading market, the refined impact of hourly electricity price fluctuations is largely unaccounted for. In a price-based spot market, electricity prices fluctuate over a shorter timescale. Existing energy storage management systems, by merely adjusting for larger deviations, struggle to obtain an optimal day-ahead reporting curve and accurately output a planned power operation curve that maximizes profitability. Summary of the Invention

[0005] The main objective of this invention is to provide a method, apparatus, device, and computer-readable storage medium for determining the optimal date-of-declaration curve, aiming to solve the technical problem in the prior art of obtaining an optimal date-of-declaration curve that maximizes profitability.

[0006] To achieve the above objectives, the present invention provides a method for determining the optimal date-of-arrival reporting curve, the method comprising the following steps:

[0007] The first cumulative return for the previous period is determined based on the reporting curve before the first day of the previous period, and the second cumulative return for the previous period is determined based on the reporting curve before the second day of the previous period.

[0008] The electricity price corresponding to the larger of the first cumulative revenue and the second cumulative revenue is determined as the target electricity price. Based on the target electricity price, the optimal daily reporting curve for each day in the current period is determined by maximizing revenue optimization.

[0009] The first day-ahead reporting curve is the day-ahead reporting curve for each day of each cycle determined by optimizing the maximum return based on the predicted electricity price for each day of each cycle. The second day-ahead reporting curve is the day-ahead reporting curve for each day of each cycle determined by optimizing the maximum return based on the average real clearing price for each day of the previous cycle.

[0010] Optionally, the method for determining the optimal date-of-report curve further includes:

[0011] Obtain the actual battery state of charge of the battery energy storage system at the preset time of the day before the application deadline, and the planned guidance power of the interval from the preset time of the previous day to 24:00 of the previous day in the optimal application curve of the previous day;

[0012] The predicted battery state of charge at 0:00 on the second day is determined based on the actual battery state of charge and the interval planned guidance power.

[0013] Based on the predicted electricity price and the predicted battery state of charge, the order curve corresponding to the predicted electricity price on the second day is determined by maximizing profit optimization; based on the average real clearing price and the predicted battery state of charge, the order curve corresponding to the predicted electricity price on the second day is determined by maximizing profit optimization.

[0014] Optionally, after the step of determining the first-day advance bid curve corresponding to the predicted electricity price for the second day based on the predicted electricity price and the predicted battery state of charge through maximum profit optimization; and after determining the second-day advance bid curve corresponding to the predicted electricity price for the second day based on the average true clearing price and the predicted battery state of charge through maximum profit optimization, the method further includes:

[0015] The first and second day-ahead reporting curves are corrected based on the charging and discharging losses of the battery energy storage system. The first cumulative revenue for the current period is determined based on the corrected first day-ahead reporting curve, and the second cumulative revenue for the current period is determined based on the corrected second day-ahead reporting curve.

[0016] Optionally, the step of correcting the first-day reporting curve based on the charging and discharging losses of the battery energy storage system includes:

[0017] If the planned guidance power corresponding to the current preset sub-time period of the first day-declared curve is the charging power, then the first battery state of charge of the battery energy storage system at the beginning of the current preset sub-time period and the second battery state of charge of the battery energy storage system at the end of the current preset sub-time period are determined.

[0018] If the state of charge of the second battery is greater than the preset upper limit of the state of charge of the battery, then the first safe power is determined based on the state of charge difference between the preset upper limit of the state of charge of the battery and the first battery, the installed capacity of the battery energy storage system and the duration of the current preset sub-time period, and the first target power of the current preset sub-time period is determined based on the first safe power and the charging loss of the battery energy storage system.

[0019] Optionally, after determining the first battery state of charge of the battery energy storage system at the start time of the current preset sub-time period and the second battery state of charge of the battery energy storage system at the end time of the current preset sub-time period, the method further includes:

[0020] If the state of charge of the second battery is not greater than the preset upper limit of the state of charge of the battery, then the first target power of the current preset sub-time period is determined according to the installed rated power of the battery energy storage system and the charging loss of the battery energy storage system.

[0021] Optionally, the step of correcting the first-day reporting curve based on the charging and discharging losses of the battery energy storage system includes:

[0022] If the planned guidance power corresponding to the current preset sub-time period is the discharge power, then the third battery state of charge of the battery energy storage system at the beginning of the current preset sub-time period and the fourth battery state of charge of the battery energy storage system at the end of the current preset sub-time period are determined.

[0023] If the state of charge of the fourth battery is less than the preset state of charge limit, then the second safe power is determined based on the state of charge difference between the third battery state of charge and the preset state of charge limit, the installed capacity of the battery energy storage system and the duration of the current preset sub-time period, and the second target power of the current preset sub-time period is determined based on the second safe power and the discharge loss of the battery energy storage system.

[0024] Optionally, after determining the third battery state of charge of the battery energy storage system at the start time of the current preset sub-time period and the fourth battery state of charge of the battery energy storage system at the end time of the current preset sub-time period, the method further includes:

[0025] If the state of charge of the fourth battery is not less than the preset minimum state of charge of the battery, then the second target power for the current preset sub-time period is determined based on the installed rated power of the battery energy storage system and the discharge loss of the battery energy storage system.

[0026] Optionally, the step of determining the predicted battery state of charge at 00:00 on the second day based on the actual battery state of charge and the interval planned guidance power includes:

[0027] The ending battery charge state of the current preset sub-time period is determined based on the starting battery charge state of the battery energy storage system at the start time of the preset sub-time period, the planned guidance power of the current preset sub-time period, and the duration of the preset sub-time period; wherein, the starting battery charge state of the preset sub-time period in which the preset time is located is the actual battery charge state.

[0028] The starting battery charge state for the next preset sub-period is determined based on the comparison between the ending battery charge state and the preset upper and lower limits of the battery charge state, until the predicted battery charge state at 0:00 on the second day is determined.

[0029] Optionally, the step of determining the starting battery charge state of the next preset sub-time period based on the comparison result between the ending battery charge state and the preset upper and lower limits of battery charge state includes:

[0030] If the comparison result is that the end battery charge state is less than the preset battery charge state limit, then the start battery charge state of the next preset sub-time period is the preset battery charge state limit.

[0031] If the comparison result is that the end battery charge state is greater than the preset battery charge state upper limit, then the start battery charge state of the next preset sub-time period is the preset battery charge state upper limit.

[0032] If the comparison result is that the ending battery charge state is not less than the preset battery charge state limit and not greater than the preset battery charge state upper limit, then the ending battery charge state is taken as the starting battery charge state of the next preset sub-time period.

[0033] Furthermore, to achieve the above objectives, the present invention also provides an apparatus for determining the optimal date-of-arrival reporting curve, the apparatus comprising:

[0034] The profit determination module is used to determine the first cumulative profit of the previous period based on the declaration curve before the first day of the previous period, and to determine the second cumulative profit of the previous period based on the declaration curve before the second day of the previous period.

[0035] The curve determination module is used to determine the electricity price corresponding to the larger of the first cumulative revenue and the second cumulative revenue as the target electricity price, and to determine the optimal daily reporting curve for each day in the current period by optimizing the maximum revenue based on the target electricity price.

[0036] The first day-ahead reporting curve is the day-ahead reporting curve for each day of each cycle determined by optimizing the maximum return based on the predicted electricity price for each day of each cycle. The second day-ahead reporting curve is the day-ahead reporting curve for each day of each cycle determined by optimizing the maximum return based on the average real clearing price for each day of the previous cycle.

[0037] In addition, to achieve the above objectives, the present invention also provides an apparatus for determining the optimal date of filing, the apparatus comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the method for determining the optimal date of filing as described above.

[0038] In addition, to achieve the above objectives, the present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the method for determining the optimal day-ahead reporting curve as described above.

[0039] This invention provides a method, apparatus, device, and computer-readable storage medium for determining the optimal day-ahead reporting curve. The method determines the first cumulative revenue of the previous period based on the first day-ahead reporting curve of the previous period, and the second cumulative revenue of the previous period based on the second day-ahead reporting curve of the previous period. The method determines the electricity price corresponding to the larger of the first and second cumulative revenues as the target electricity price, and determines the optimal day-ahead reporting curve for each day of the current period through maximum revenue optimization based on the target electricity price. The first day-ahead reporting curve is the day-ahead reporting curve for each day of each period determined by maximum revenue optimization based on the predicted electricity price for each day of each period, and the second day-ahead reporting curve is the day-ahead reporting curve for each day of each period determined by maximum revenue optimization based on the average true clearing price for each day of the previous period.

[0040] First, the first cumulative revenue of the previous period is determined based on the first-day advance declaration curve of the previous period, and the second cumulative revenue of the previous period is determined based on the second-day advance declaration curve of the previous period. Then, the target electricity price corresponding to the larger of the first and second cumulative revenues is used, and the optimal advance declaration curve for each day in the current period is determined by maximizing revenue based on the target electricity price. At the same time, the first-day advance declaration curve for each day of the current period is determined by maximizing revenue based on the predicted electricity price for each day of the current period, and the second-day advance declaration curve for each day of the current period is determined by maximizing revenue based on the average real clearing price for each day of the previous period. The first-day advance declaration curve and the second-day advance declaration curve of the current period are used to determine the cumulative revenue and target electricity price for the next period.

[0041] The process involves obtaining the first cumulative revenue corresponding to the first-day advance declaration curve optimized based on the predicted electricity price and the second cumulative revenue corresponding to the second-day advance declaration curve optimized based on the average true clearing electricity price. The electricity price corresponding to the larger cumulative revenue is determined as the target electricity price. This allows for the determination of the optimal daily advance declaration curve for each day within the current period, based on the target electricity price, to maximize revenue. Furthermore, the process calculates the first-day and second-day advance declaration curves needed for the next period within the current period. Based on the first cumulative revenue of the first-day advance declaration curve corresponding to the predicted electricity price of the previous period and the second cumulative revenue of the second-day advance declaration curve corresponding to the average true clearing electricity price of the period before that, the target electricity price corresponding to the larger of these two cumulative revenues is determined for maximizing revenue. This yields the optimal daily advance declaration curve for each day of the current period, ensuring that the revenue for each period is maximized. Attached Figure Description

[0042] Figure 1 This is a schematic diagram of the structure of the operating device of the hardware operating environment involved in the embodiments of the present invention;

[0043] Figure 2 This is a flowchart illustrating an embodiment of a method for determining the optimal date-of-report curve according to the present invention.

[0044] Figure 3 This is a flowchart illustrating another embodiment of the method for determining the optimal date-of-report curve of the present invention.

[0045] Figure 4 This is a schematic diagram of the grid connection point in one embodiment of the method for determining the optimal day-ahead reporting curve of the present invention;

[0046] Figure 5 This is a schematic diagram of an embodiment of the apparatus for determining the optimal date-of-declaration curve of the present invention.

[0047] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0048] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0049] Reference Figure 1 , Figure 1 This is a schematic diagram of the operating device of the hardware operating environment involved in the embodiments of the present invention.

[0050] like Figure 1 As shown, the operating device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to enable communication between these components. The user interface 1003 may include a display screen or an input unit such as a keyboard; optionally, the user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface). The memory 1005 may be a high-speed random access memory (RAM) or a stable non-volatile memory (NVM), such as a disk drive. The memory 1005 may also optionally be a storage device independent of the aforementioned processor 1001.

[0051] Those skilled in the art will understand that Figure 1 The structure shown does not constitute a limitation on the operating equipment and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0052] like Figure 1 As shown, the memory 1005, which serves as a storage medium, may include an operating system, a data storage module, a network communication module, a user interface module, and computer programs.

[0053] exist Figure 1 In the illustrated operating device, the network interface 1004 is mainly used for data communication with other devices; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and memory 1005 in the operating device of the present invention can be installed in the operating device, and the operating device calls the computer program stored in the memory 1005 through the processor 1001 and performs the following operations:

[0054] The first cumulative return for the previous period is determined based on the reporting curve before the first day of the previous period, and the second cumulative return for the previous period is determined based on the reporting curve before the second day of the previous period.

[0055] The electricity price corresponding to the larger of the first cumulative revenue and the second cumulative revenue is determined as the target electricity price. Based on the target electricity price, the optimal daily reporting curve for each day in the current period is determined by maximizing revenue optimization.

[0056] The first day-ahead reporting curve is the day-ahead reporting curve for each day of each cycle determined by optimizing the maximum return based on the predicted electricity price for each day of each cycle. The second day-ahead reporting curve is the day-ahead reporting curve for each day of each cycle determined by optimizing the maximum return based on the average real clearing price for each day of the previous cycle.

[0057] Furthermore, the processor 1001 can call a computer program stored in the memory 1005 and also perform the following operations:

[0058] The method for determining the optimal pre-dated reporting curve also includes:

[0059] Obtain the actual battery state of charge of the battery energy storage system at the preset time of the day before the application deadline, and the planned guidance power of the interval from the preset time of the previous day to 24:00 of the previous day in the optimal application curve of the previous day;

[0060] The predicted battery state of charge at 0:00 on the second day is determined based on the actual battery state of charge and the interval planned guidance power.

[0061] Based on the predicted electricity price and the predicted battery state of charge, the order curve corresponding to the predicted electricity price on the second day is determined by maximizing profit optimization; based on the average real clearing price and the predicted battery state of charge, the order curve corresponding to the predicted electricity price on the second day is determined by maximizing profit optimization.

[0062] Furthermore, the processor 1001 can call a computer program stored in the memory 1005 and also perform the following operations:

[0063] Following the step of determining the first-day advance bid curve corresponding to the predicted electricity price for the second day based on the predicted electricity price and the predicted battery state of charge through maximum profit optimization; and after determining the second-day advance bid curve corresponding to the predicted electricity price for the second day based on the average real clearing price and the predicted battery state of charge through maximum profit optimization, the method further includes:

[0064] The first and second day-ahead reporting curves are corrected based on the charging and discharging losses of the battery energy storage system. The first cumulative revenue for the current period is determined based on the corrected first day-ahead reporting curve, and the second cumulative revenue for the current period is determined based on the corrected second day-ahead reporting curve.

[0065] Furthermore, the processor 1001 can call a computer program stored in the memory 1005 and also perform the following operations:

[0066] The step of correcting the first-day reported curve based on the charging and discharging losses of the battery energy storage system includes:

[0067] If the planned guidance power corresponding to the current preset sub-time period of the first day-declared curve is the charging power, then the first battery state of charge of the battery energy storage system at the beginning of the current preset sub-time period and the second battery state of charge of the battery energy storage system at the end of the current preset sub-time period are determined.

[0068] If the state of charge of the second battery is greater than the preset upper limit of the state of charge of the battery, then the first safe power is determined based on the state of charge difference between the preset upper limit of the state of charge of the battery and the first battery, the installed capacity of the battery energy storage system and the duration of the current preset sub-time period, and the first target power of the current preset sub-time period is determined based on the first safe power and the charging loss of the battery energy storage system.

[0069] Furthermore, the processor 1001 can call a computer program stored in the memory 1005 and also perform the following operations:

[0070] After the steps of determining the first battery state of charge of the battery energy storage system at the start time of the current preset sub-time period and the second battery state of charge of the battery energy storage system at the end time of the current preset sub-time period, the method further includes:

[0071] If the state of charge of the second battery is not greater than the preset upper limit of the state of charge of the battery, then the first target power of the current preset sub-time period is determined according to the installed rated power of the battery energy storage system and the charging loss of the battery energy storage system.

[0072] Furthermore, the processor 1001 can call a computer program stored in the memory 1005 and also perform the following operations:

[0073] The step of correcting the first-day reported curve based on the charging and discharging losses of the battery energy storage system includes:

[0074] If the planned guidance power corresponding to the current preset sub-time period is the discharge power, then the third battery state of charge of the battery energy storage system at the beginning of the current preset sub-time period and the fourth battery state of charge of the battery energy storage system at the end of the current preset sub-time period are determined.

[0075] If the state of charge of the fourth battery is less than the preset state of charge limit, then the second safe power is determined based on the state of charge difference between the third battery state of charge and the preset state of charge limit, the installed capacity of the battery energy storage system and the duration of the current preset sub-time period, and the second target power of the current preset sub-time period is determined based on the second safe power and the discharge loss of the battery energy storage system.

[0076] Furthermore, the processor 1001 can call a computer program stored in the memory 1005 and also perform the following operations:

[0077] After the steps of determining the third battery state of charge of the battery energy storage system at the start time of the current preset sub-time period and the fourth battery state of charge of the battery energy storage system at the end time of the current preset sub-time period, the method further includes:

[0078] If the state of charge of the fourth battery is not less than the preset minimum state of charge of the battery, then the second target power for the current preset sub-time period is determined based on the installed rated power of the battery energy storage system and the discharge loss of the battery energy storage system.

[0079] Furthermore, the processor 1001 can call a computer program stored in the memory 1005 and also perform the following operations:

[0080] The step of determining the predicted battery state of charge at 00:00 on the second day based on the actual battery state of charge and the interval planned guidance power includes:

[0081] The ending battery charge state of the current preset sub-time period is determined based on the starting battery charge state of the battery energy storage system at the start time of the preset sub-time period, the planned guidance power of the current preset sub-time period, and the duration of the preset sub-time period; wherein, the starting battery charge state of the preset sub-time period in which the preset time is located is the actual battery charge state.

[0082] The starting battery charge state for the next preset sub-period is determined based on the comparison between the ending battery charge state and the preset upper and lower limits of the battery charge state, until the predicted battery charge state at 0:00 on the second day is determined.

[0083] Furthermore, the processor 1001 can call a computer program stored in the memory 1005 and also perform the following operations:

[0084] The step of determining the starting battery charge state of the next preset sub-time period based on the comparison result between the ending battery charge state and the preset upper and lower limits of battery charge state includes:

[0085] If the comparison result is that the end battery charge state is less than the preset battery charge state limit, then the start battery charge state of the next preset sub-time period is the preset battery charge state limit.

[0086] If the comparison result is that the end battery charge state is greater than the preset battery charge state upper limit, then the start battery charge state of the next preset sub-time period is the preset battery charge state upper limit.

[0087] If the comparison result is that the ending battery charge state is not less than the preset battery charge state limit and not greater than the preset battery charge state upper limit, then the ending battery charge state is taken as the starting battery charge state of the next preset sub-time period.

[0088] Reference Figure 2 , Figure 2 This is a flowchart illustrating an embodiment of a method for determining the optimal date-of-arrival filing curve according to the present invention. This embodiment of the present invention provides a method for determining the optimal date-of-arrival filing curve, which includes the following steps:

[0089] Step S10: Determine the first cumulative return of the previous period based on the reporting curve before the first day of the previous period, and determine the second cumulative return of the previous period based on the reporting curve before the second day of the previous period.

[0090] The period refers to the period for statistical revenue, which can be a week or a month, etc. The daily reporting curve refers to the planned power operation curve for each day of any period. Revenue refers to the positive revenue from the battery energy storage system discharging into the grid and the negative revenue from charging from the grid. Revenue = (discharge time * discharge power * corresponding discharge electricity price) - (charging time * charging power * corresponding charging electricity price). In this embodiment, a statistical period is defined as half a month or 15 days.

[0091] Step S20: Determine the electricity price corresponding to the larger of the first cumulative revenue and the second cumulative revenue as the target electricity price, and determine the optimal daily reporting curve for each day in the current period based on the target electricity price through maximum revenue optimization;

[0092] The first day-ahead reporting curve is the day-ahead reporting curve for each day of each cycle determined by optimizing the maximum return based on the predicted electricity price for each day of each cycle. The second day-ahead reporting curve is the day-ahead reporting curve for each day of each cycle determined by optimizing the maximum return based on the average real clearing price for each day of the previous cycle.

[0093] The larger of the first and second cumulative revenues is determined, and a target electricity price is set as the price corresponding to the larger revenue. Then, based on the target electricity price, the optimal daily reporting curve for each day within the current period is determined through maximum revenue optimization. In this embodiment, the method of maximum revenue optimization is not limited. If maximum revenue optimization is performed based on the predicted electricity price for each day within each period, the first daily reporting curve for each day within each period can be determined; if maximum revenue optimization is performed based on the average true clearing price for each day in the previous period, the second daily reporting curve for each day within each period can be determined.

[0094] Table 1

[0095]

[0096] Taking Table 1 as an example, since there is no average real clearing price for each day of the previous period (which does not exist) in the first period, there is no second cumulative revenue in the first period. Therefore, in the first period, the predicted electricity price PA1 is used to determine the optimal daily reporting curve for each day in the current period through the maximum revenue optimization, and the first cumulative revenue profit (PA1) is obtained.

[0097] In the second cycle, the average real clearing price PB1 of the previous cycle (the first cycle) is used to determine the optimal daily reporting curve for each day in the current cycle through maximum profit optimization, and the second cumulative profit (PB1) is obtained. At the same time, in the second cycle, the predicted price PA2 is used to determine the optimal daily reporting curve for each day in the current cycle through maximum profit optimization, and the first cumulative profit (PA2) is obtained.

[0098] In the third cycle, the target electricity price MAX(profit(PA2), profit(PB1)) corresponding to the larger of the first cumulative profit (PA2) and the second cumulative profit (PB1) of the second cycle is adopted. Based on the target electricity price MAX(profit(PA2), profit(PB1)), the optimal daily reporting curve for each day in the current cycle is determined by maximizing the profit.

[0099] In this embodiment, the first cumulative revenue of the previous period is determined based on the first day-ahead reporting curve of the previous period, and the second cumulative revenue of the previous period is determined based on the second day-ahead reporting curve of the previous period. The electricity price corresponding to the larger revenue between the first and second cumulative revenues is determined as the target electricity price. The optimal day-ahead reporting curve for each day in the current period is determined by maximizing revenue optimization based on the target electricity price. The first day-ahead reporting curve is the day-ahead reporting curve for each day in each period determined by maximizing revenue optimization based on the predicted electricity price for each day in each period, and the second day-ahead reporting curve is the day-ahead reporting curve for each day in each period determined by maximizing revenue optimization based on the average real clearing price for each day in the previous period.

[0100] First, the first cumulative revenue of the previous period is determined based on the first-day advance declaration curve of the previous period, and the second cumulative revenue of the previous period is determined based on the second-day advance declaration curve of the previous period. Then, the target electricity price corresponding to the larger of the first and second cumulative revenues is used, and the optimal advance declaration curve for each day in the current period is determined by maximizing revenue based on the target electricity price. At the same time, the first-day advance declaration curve for each day of the current period is determined by maximizing revenue based on the predicted electricity price for each day of the current period, and the second-day advance declaration curve for each day of the current period is determined by maximizing revenue based on the average real clearing price for each day of the previous period. The first-day advance declaration curve and the second-day advance declaration curve of the current period are used to determine the cumulative revenue and target electricity price for the next period.

[0101] The process involves obtaining the first cumulative revenue corresponding to the first-day advance declaration curve optimized based on the predicted electricity price and the second cumulative revenue corresponding to the second-day advance declaration curve optimized based on the average true clearing electricity price. The electricity price corresponding to the larger cumulative revenue is determined as the target electricity price. This allows for the determination of the optimal daily advance declaration curve for each day within the current period, based on the target electricity price, to maximize revenue. Furthermore, the process calculates the first-day and second-day advance declaration curves needed for the next period within the current period. Based on the first cumulative revenue of the first-day advance declaration curve corresponding to the predicted electricity price of the previous period and the second cumulative revenue of the second-day advance declaration curve corresponding to the average true clearing electricity price of the period before that, the target electricity price corresponding to the larger of these two cumulative revenues is determined for maximizing revenue. This yields the optimal daily advance declaration curve for each day of the current period, ensuring that the revenue for each period is maximized.

[0102] Reference Figure 3 In another embodiment of the method for determining the optimal date-of-arrival reporting curve provided by the present invention, the method further includes:

[0103] Step A: Obtain the actual battery state of charge of the battery energy storage system at the preset time before the application deadline, and the planned guidance power of the interval from the preset time of the previous day to 24:00 of the previous day in the optimal application curve of the previous day.

[0104] To participate in day-ahead electricity trading, the battery energy storage system's planned power operation curve for the following day (D+1) must be submitted to the provincial electricity trading center before the preset time T on day D. Therefore, before submission, assuming the planned power operation curve for day D is the same as or close to the planned power operation curve for the previous day (D-1), the predicted battery state of charge (SOC) at 24:00 on day D is estimated based on the planned guidance power X_Before[T, 24:00] from the preset time T on day D-1 to 24:00 on day D-1 in the planned power operation curve X_Before. This estimate is also based on the actual battery state of charge (SOC) of the battery energy storage system at the preset time on day D before the submission deadline T.

[0105] Step B: Determine the predicted battery state of charge at 0:00 on the second day based on the actual battery state of charge and the interval planned guidance power;

[0106] Optionally, the step of determining the predicted battery state of charge at 00:00 on the second day based on the actual battery state of charge and the interval planned guidance power includes:

[0107] The ending battery charge state of the current preset sub-time period is determined based on the starting battery charge state of the battery energy storage system at the start time of the preset sub-time period, the planned guidance power of the current preset sub-time period, and the duration of the preset sub-time period; wherein, the starting battery charge state of the preset sub-time period in which the preset time is located is the actual battery charge state.

[0108] The starting battery charge state for the next preset sub-period is determined based on the comparison between the ending battery charge state and the preset upper and lower limits of the battery charge state, until the predicted battery charge state at 0:00 on the second day is determined.

[0109] In this embodiment, a day is divided into 24 sub-time periods i, with one sub-time period i corresponding to each hour, or into 24*4 sub-time periods i, with 4 sub-time periods i corresponding to each hour. The ending battery charge state SOC_END_i of the current preset sub-time period is determined based on the starting battery charge state SOC_START_i of the battery energy storage system at the beginning of the preset sub-time period, the planned guidance power X_Before[T, 24:00] of the current preset sub-time period, and the duration t of the preset sub-time period. The starting battery charge state SOC_START_i of the preset sub-time period at the preset time T is the actual battery charge state SOC. Then, the starting battery charge state SOC_START_i of the next preset sub-time period is determined based on the comparison between the ending battery charge state SOC_END and the preset upper and lower limits of battery charge state (SOC_up: upper limit of SOC; SOC_down: lower limit of SOC), until the predicted battery charge state SOC_P at 0:00 on the second day is determined.

[0110] Optionally, the step of determining the starting battery charge state of the next preset sub-time period based on the comparison result between the ending battery charge state and the preset upper and lower limits of battery charge state includes:

[0111] If the comparison result is that the end battery charge state is less than the preset battery charge state limit, then the start battery charge state of the next preset sub-time period is the preset battery charge state limit.

[0112] If the comparison result is that the end battery charge state is greater than the preset battery charge state upper limit, then the start battery charge state of the next preset sub-time period is the preset battery charge state upper limit.

[0113] If the comparison result is that the ending battery charge state is not less than the preset battery charge state limit and not greater than the preset battery charge state upper limit, then the ending battery charge state is taken as the starting battery charge state of the next preset sub-time period.

[0114] If the ending battery charge state SOC_END_i is less than the preset battery charge state limit SOC_down, the starting battery charge state SOC_START_i+1 of the next preset sub-period is the preset battery charge state limit SOC_down. If the ending battery charge state SOC_END_i is greater than the preset battery charge state upper limit SOC_up, the starting battery charge state SOC_START_i+1 of the next preset sub-period is the preset battery charge state limit SOC_up. If the ending battery charge state SOC_END_i is not less than the preset battery charge state limit SOC_down and not greater than the preset battery charge state upper limit SOC_up, falling between the preset battery charge state upper and lower limits, the ending battery charge state SOC_END_i is used as the starting battery charge state SOC_START_i+1 of the next preset sub-period.

[0115] Step C: Based on the predicted electricity price and the predicted battery state of charge, determine the first-day advance declaration curve corresponding to the predicted electricity price for the second day through maximum profit optimization; based on the average real clearing price and the predicted battery state of charge, determine the second-day advance declaration curve corresponding to the predicted electricity price for the second day through maximum profit optimization.

[0116] After determining the predicted battery state of charge (SOC), the first-day reporting curve corresponding to the predicted SOC for the second day is determined through maximum revenue optimization based on the predicted electricity price and the predicted SOC. Similarly, the second-day reporting curve corresponding to the predicted SOC for the second day is determined through maximum revenue optimization based on the average real clearing price and the predicted SOC. By continuously adjusting the planned guidance power under the predicted electricity price and the average real clearing price, and obtaining the energy storage revenue corresponding to different planned guidance powers, the first-day reporting curve and the second-day reporting curve corresponding to the maximum energy storage revenue are obtained.

[0117] In another embodiment of the method for determining the optimal day-ahead reporting curve provided by the present invention, after the steps of determining the first day-ahead reporting curve corresponding to the predicted electricity price on the second day through maximum profit optimization based on the predicted electricity price and the predicted battery state of charge, and determining the second day-ahead reporting curve corresponding to the predicted electricity price on the second day through maximum profit optimization based on the average real clearing price and the predicted battery state of charge, the method further includes:

[0118] The first and second day-ahead reporting curves are corrected based on the charging and discharging losses of the battery energy storage system. The first cumulative revenue for the current period is determined based on the corrected first day-ahead reporting curve, and the second cumulative revenue for the current period is determined based on the corrected second day-ahead reporting curve.

[0119] Reference Figure 4Suppose that at a certain moment, the battery energy storage system is charged at a rated power of 1000KW, and the declared charging power of 1000KW is given to the grid connection point. However, the equipment connected to the grid connection point includes not only the energy storage equipment, but also the daily electricity consumption of other electrical equipment, such as the system losses of station transformers, and the daily electricity consumption of the monitoring room, such as air conditioning and lighting. Therefore, the charging power received by the energy storage equipment will not reach 1000KW.

[0120] In other words, because both charging and discharging of the battery energy storage system incur losses at the grid connection point, the power declared at the grid connection point based on the power output of the algorithm execution cannot meet the energy storage power requirements of the battery energy storage system. That is to say, the actual declared power delivered to the grid connection point is not 100% allocated to the battery energy storage system, and there is a discrepancy between the target power output of the algorithm execution at the battery energy storage system and the power that the battery energy storage system can ultimately obtain and desires. Therefore, it is necessary to correct and convert the declaration curves from the first and second days prior to the algorithm execution output into the power at the grid connection point to ensure that it matches the actual power requirements of the battery energy storage system.

[0121] In this embodiment, the charging loss (ChargEFiciency) and discharging loss (disChargEFiciency) of the battery energy storage system are used to correct the first and second day-ahead reporting curves, thereby correcting the charging and discharging power output by the algorithm. This prevents deviations in the actual execution of the reported power due to overcharging or over-discharging of the State of Charge (SOC) at a certain time period (SOC exceeding the preset upper and lower limits of battery state of charge), which would cause deviations in the assessment. Then, the first cumulative revenue for the current period is determined accurately and without deviation based on the corrected first day-ahead reporting curve, and the second cumulative revenue for the current period is determined accurately and without deviation based on the corrected second day-ahead reporting curve.

[0122] Optionally, the step of correcting the first-day reporting curve based on the charging and discharging losses of the battery energy storage system includes:

[0123] If the planned guidance power corresponding to the current preset sub-time period of the first day-declared curve is the charging power, then the first battery state of charge of the battery energy storage system at the beginning of the current preset sub-time period and the second battery state of charge of the battery energy storage system at the end of the current preset sub-time period are determined.

[0124] If the state of charge of the second battery is greater than the preset upper limit of the state of charge of the battery, then the first safe power is determined based on the state of charge difference between the preset upper limit of the state of charge of the battery and the first battery, the installed capacity of the battery energy storage system and the duration of the current preset sub-time period, and the first target power of the current preset sub-time period is determined based on the first safe power and the charging loss of the battery energy storage system.

[0125] Considering the direction of current, when the grid charges the battery energy storage system through the grid connection point, the conversion correction needs to be made using the formula: declared energy storage power ÷ charging efficiency (ChargEFiciency). When the battery energy storage system discharges to the grid through the grid connection point, the conversion correction needs to be made using the formula: declared energy storage power × discharging efficiency (disChargEFiciency). Charging loss refers to the ratio between the charging power that the energy storage station can obtain and the charging power obtained by the grid connection point. The energy storage station will specify standard operating conditions, such as the charging and discharging efficiency under 25%, 50%, 75%, and 100% output values. The charging and discharging efficiency under other non-standard operating conditions can be calculated by interpolation (first, third, etc.) based on the standard operating conditions.

[0126] In this embodiment, the correction of the declaration curve before the first day is used as an example. The correction of the declaration curve before the second day is similar to the correction of the declaration curve before the first day, and will not be described again here.

[0127] If the planned guidance power corresponding to the curve submitted on the first day is the charging power for the current preset sub-time period, then the first battery state of charge (SOC) of the battery energy storage system at the beginning of the current preset sub-time period and the second battery SOC of the battery energy storage system at the end of the current preset sub-time period are determined. If the second battery SOC is greater than the preset upper limit of battery SOC_up, then the first safe power (power1) is determined based on the difference in SOC between the preset upper limit of battery SOC_up and the first battery SOC, the installed capacity of the battery energy storage system, and the duration t of the current preset sub-time period. Charging with the first safe power (power1) ensures that the second battery SOC of the battery energy storage system is exactly the preset upper limit of battery SOC_up at the end of the current preset sub-time period, preventing overcharging of the battery energy storage system. The first target power for the current preset sub-time period is determined based on the first safe power (power1) and the charging loss (ChargEFiciency) of the battery energy storage system. The first target power = first safe power (power1) ÷ charging efficiency (ChargEFiciency).

[0128] Optionally, after determining the first battery state of charge of the battery energy storage system at the start time of the current preset sub-time period and the second battery state of charge of the battery energy storage system at the end time of the current preset sub-time period, the method further includes:

[0129] If the state of charge of the second battery is not greater than the preset upper limit of the state of charge of the battery, then the first target power of the current preset sub-time period is determined according to the installed rated power of the battery energy storage system and the charging loss of the battery energy storage system.

[0130] If the state of charge of the second battery is not greater than the preset upper limit of the battery state of charge SOC_up, then the first target power of the current preset sub-time period is determined according to the installed rated power rated and the charging efficiency ChargEFiciency of the battery energy storage system. The first target power = installed rated power rated ÷ charging efficiency ChargEFiciency. During the current preset sub-time period, the battery energy storage system can be charged according to the installed rated power rated, and it will not cause the state of charge of the second battery of the battery energy storage system to exceed the preset upper limit of the battery state of charge SOC_up at the end of the current preset sub-time period, thus preventing the battery energy storage system from being overcharged.

[0131] Optionally, the step of correcting the first-day reporting curve based on the charging and discharging losses of the battery energy storage system includes:

[0132] If the planned guidance power corresponding to the current preset sub-time period is the discharge power, then the third battery state of charge of the battery energy storage system at the beginning of the current preset sub-time period and the fourth battery state of charge of the battery energy storage system at the end of the current preset sub-time period are determined.

[0133] If the state of charge of the fourth battery is less than the preset state of charge limit, then the second safe power is determined based on the state of charge difference between the third battery state of charge and the preset state of charge limit, the installed capacity of the battery energy storage system and the duration of the current preset sub-time period, and the second target power of the current preset sub-time period is determined based on the second safe power and the discharge loss of the battery energy storage system.

[0134] If the planned guidance power corresponding to the curve submitted on the first day is the discharge power for the current preset sub-time period, then determine the third battery state of charge (SOC) of the battery energy storage system at the start of the current preset sub-time period and the fourth battery SOC of the battery energy storage system at the end of the current preset sub-time period; if the fourth battery SOC is less than the preset battery SOC down limit,

[0135] The second safety power, power2, is determined based on the state of charge difference between the third battery and the preset state of charge limit (SOC_down), the installed capacity of the battery energy storage system, and the duration t of the current preset sub-time period. Charging with the second safety power, power2, ensures that the state of charge of the fourth battery in the battery energy storage system is exactly at the preset state of charge limit (SOC_down) at the end of the current preset sub-time period, preventing over-discharge of the battery energy storage system. The second target power for the current preset sub-time period is determined based on the second safety power, power2, and the discharge loss of the battery energy storage system, disChargEFiciency. The second target power = second safety power, power2 × discharge efficiency, disChargEFiciency.

[0136] Optionally, after determining the third battery state of charge of the battery energy storage system at the start time of the current preset sub-time period and the fourth battery state of charge of the battery energy storage system at the end time of the current preset sub-time period, the method further includes:

[0137] If the state of charge of the fourth battery is not less than the preset minimum state of charge of the battery, then the second target power for the current preset sub-time period is determined based on the installed rated power of the battery energy storage system and the discharge loss of the battery energy storage system.

[0138] If the fourth battery's state of charge is not less than the preset battery state of charge limit SOC_down, then the second target power for the current preset sub-period is determined based on the installed rated power rated and the discharge loss disChargEFiciency of the battery energy storage system. The second target power = installed rated power rated × discharge loss disChargEFiciency. During the current preset sub-period, the battery energy storage system can be discharged according to its installed rated power rated, and the fourth battery's state of charge will not fall below the preset battery state of charge limit SOC_down at the end of the current preset sub-period, thus preventing over-discharge of the battery energy storage system.

[0139] In addition, refer to Figure 5 This invention also provides an apparatus for determining the optimal date-of-arrival reporting curve, the apparatus comprising:

[0140] The revenue determination module M1 is used to determine the first cumulative revenue of the previous period based on the reporting curve before the first day of the previous period, and to determine the second cumulative revenue of the previous period based on the reporting curve before the second day of the previous period.

[0141] The curve determination module M2 is used to determine the electricity price corresponding to the larger of the first cumulative revenue and the second cumulative revenue as the target electricity price, and to determine the optimal daily reporting curve for each day in the current period by optimizing the maximum revenue based on the target electricity price.

[0142] The first day-ahead reporting curve is the day-ahead reporting curve for each day of each cycle determined by optimizing the maximum return based on the predicted electricity price for each day of each cycle. The second day-ahead reporting curve is the day-ahead reporting curve for each day of each cycle determined by optimizing the maximum return based on the average real clearing price for each day of the previous cycle.

[0143] Optionally, the device for determining the optimal date-of-declaration curve further includes:

[0144] The acquisition module is used to acquire the actual battery state of charge of the battery energy storage system at a preset time before the application deadline, as well as the planned guidance power of the interval from the preset time of the previous day to 24:00 of the previous day in the optimal application curve of the previous day.

[0145] The prediction module is used to determine the predicted battery state of charge at 0:00 on the second day based on the actual battery state of charge and the interval planned guidance power.

[0146] The optimization module is used to determine the first-day advance declaration curve corresponding to the predicted electricity price on the second day through maximum profit optimization based on the predicted electricity price and the predicted battery state of charge; and to determine the second-day advance declaration curve corresponding to the predicted electricity price on the second day through maximum profit optimization based on the average real clearing price and the predicted battery state of charge.

[0147] Optionally, the device for determining the optimal date-of-declaration curve further includes:

[0148] The correction module is used to correct the first and second day-ahead reporting curves based on the charging and discharging losses of the battery energy storage system, determine the first cumulative revenue for the current period based on the corrected first day-ahead reporting curve, and determine the second cumulative revenue for the current period based on the corrected second day-ahead reporting curve.

[0149] Optional, a correction module is used for:

[0150] If the planned guidance power corresponding to the current preset sub-time period of the first day-declared curve is the charging power, then the first battery state of charge of the battery energy storage system at the beginning of the current preset sub-time period and the second battery state of charge of the battery energy storage system at the end of the current preset sub-time period are determined.

[0151] If the state of charge of the second battery is greater than the preset upper limit of the state of charge of the battery, then the first safe power is determined based on the state of charge difference between the preset upper limit of the state of charge of the battery and the first battery, the installed capacity of the battery energy storage system and the duration of the current preset sub-time period, and the first target power of the current preset sub-time period is determined based on the first safe power and the charging loss of the battery energy storage system.

[0152] Optional, a correction module is used for:

[0153] If the state of charge of the second battery is not greater than the preset upper limit of the state of charge of the battery, then the first target power of the current preset sub-time period is determined according to the installed rated power of the battery energy storage system and the charging loss of the battery energy storage system.

[0154] Optional, a correction module is used for:

[0155] If the planned guidance power corresponding to the current preset sub-time period is the discharge power, then the third battery state of charge of the battery energy storage system at the beginning of the current preset sub-time period and the fourth battery state of charge of the battery energy storage system at the end of the current preset sub-time period are determined.

[0156] If the state of charge of the fourth battery is less than the preset state of charge limit, then the second safe power is determined based on the state of charge difference between the third battery state of charge and the preset state of charge limit, the installed capacity of the battery energy storage system and the duration of the current preset sub-time period, and the second target power of the current preset sub-time period is determined based on the second safe power and the discharge loss of the battery energy storage system.

[0157] Optional, a correction module is used for:

[0158] If the state of charge of the fourth battery is not less than the preset minimum state of charge of the battery, then the second target power for the current preset sub-time period is determined based on the installed rated power of the battery energy storage system and the discharge loss of the battery energy storage system.

[0159] Optional, prediction module, used for:

[0160] The ending battery charge state of the current preset sub-time period is determined based on the starting battery charge state of the battery energy storage system at the start time of the preset sub-time period, the planned guidance power of the current preset sub-time period, and the duration of the preset sub-time period; wherein, the starting battery charge state of the preset sub-time period in which the preset time is located is the actual battery charge state.

[0161] The starting battery charge state for the next preset sub-period is determined based on the comparison between the ending battery charge state and the preset upper and lower limits of the battery charge state, until the predicted battery charge state at 0:00 on the second day is determined.

[0162] Optional, prediction module, used for:

[0163] If the comparison result is that the end battery charge state is less than the preset battery charge state limit, then the start battery charge state of the next preset sub-time period is the preset battery charge state limit.

[0164] If the comparison result is that the end battery charge state is greater than the preset battery charge state upper limit, then the start battery charge state of the next preset sub-time period is the preset battery charge state upper limit.

[0165] If the comparison result is that the ending battery charge state is not less than the preset battery charge state limit and not greater than the preset battery charge state upper limit, then the ending battery charge state is taken as the starting battery charge state of the next preset sub-time period.

[0166] The apparatus for determining the optimal date of filing provides this invention employs the method for determining the optimal date of filing in the above embodiments, solving the technical problem in the prior art that it is difficult to obtain an optimal date of filing that maximizes benefits. Compared with the prior art, the beneficial effects of the apparatus for determining the optimal date of filing provided in this invention are the same as those of the method for determining the optimal date of filing in the above embodiments, and other technical features in the apparatus for determining the optimal date of filing are the same as those disclosed in the method of the above embodiments, and will not be repeated here.

[0167] Furthermore, embodiments of the present invention also provide an apparatus for determining the optimal date-of-report curve. The apparatus for determining the optimal date-of-report curve includes: a memory, a processor, and a computer program stored in the memory and executable on the processor. The computer program is configured to implement the steps of the method for determining the optimal date-of-report curve as described above.

[0168] Furthermore, embodiments of the present invention also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the method for determining the optimal day-ahead reporting curve as described above.

[0169] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0170] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0171] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0172] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A method for determining the optimal pre-dated reporting curve, characterized in that, The method for determining the optimal pre-dated reporting curve includes the following steps: The first cumulative profit of the previous period is determined based on the first day-ahead reporting curve of the previous period, and the second cumulative profit of the previous period is determined based on the second day-ahead reporting curve of the previous period. The day-ahead reporting curve refers to the planned power operation curve for each day of any period. The electricity price corresponding to the larger of the first cumulative revenue and the second cumulative revenue is determined as the target electricity price. Based on the target electricity price, the optimal daily reporting curve for each day in the current period is determined by maximizing revenue optimization. The method for determining the first and second day-ahead reporting curves is as follows: obtain the actual battery charge status of the battery energy storage system at a preset time before the reporting deadline, and the planned guidance power of the interval from the preset time of the previous day to 24:00 of the previous day in the optimal day-ahead reporting curve of the previous day. The predicted battery state of charge at 0:00 on the second day is determined based on the actual battery state of charge and the interval planned guidance power. Based on the predicted electricity price and the predicted battery state of charge, the order curve corresponding to the predicted electricity price on the second day is determined by maximizing profit optimization; based on the average real clearing price and the predicted battery state of charge, the order curve corresponding to the predicted electricity price on the second day is determined by maximizing profit optimization.

2. The method for determining the optimal pre-dated reporting curve as described in claim 1, characterized in that, Following the step of determining the first-day advance bid curve corresponding to the predicted electricity price for the second day based on the predicted electricity price and the predicted battery state of charge through maximum profit optimization; and after determining the second-day advance bid curve corresponding to the predicted electricity price for the second day based on the average real clearing price and the predicted battery state of charge through maximum profit optimization, the method further includes: The first and second day-ahead reporting curves are corrected based on the charging and discharging losses of the battery energy storage system. The first cumulative revenue for the current period is determined based on the corrected first day-ahead reporting curve, and the second cumulative revenue for the current period is determined based on the corrected second day-ahead reporting curve.

3. The method for determining the optimal pre-dated reporting curve as described in claim 2, characterized in that, The step of correcting the first-day reported curve based on the charging and discharging losses of the battery energy storage system includes: If the planned guidance power corresponding to the current preset sub-time period of the first day-declared curve is the charging power, then the first battery state of charge of the battery energy storage system at the beginning of the current preset sub-time period and the second battery state of charge of the battery energy storage system at the end of the current preset sub-time period are determined. If the state of charge of the second battery is greater than the preset upper limit of the state of charge of the battery, then the first safe power is determined based on the state of charge difference between the preset upper limit of the state of charge of the battery and the first battery, the installed capacity of the battery energy storage system and the duration of the current preset sub-time period, and the first target power of the current preset sub-time period is determined based on the first safe power and the charging loss of the battery energy storage system.

4. The method for determining the optimal pre-dated reporting curve as described in claim 3, characterized in that, After the steps of determining the first battery state of charge of the battery energy storage system at the start time of the current preset sub-time period and the second battery state of charge of the battery energy storage system at the end time of the current preset sub-time period, the method further includes: If the state of charge of the second battery is not greater than the preset upper limit of the state of charge of the battery, then the first target power of the current preset sub-time period is determined according to the installed rated power of the battery energy storage system and the charging loss of the battery energy storage system.

5. The method for determining the optimal pre-dated reporting curve as described in claim 2, characterized in that, The step of correcting the first-day reported curve based on the charging and discharging losses of the battery energy storage system includes: If the planned guidance power corresponding to the current preset sub-time period is the discharge power, then the third battery state of charge of the battery energy storage system at the beginning of the current preset sub-time period and the fourth battery state of charge of the battery energy storage system at the end of the current preset sub-time period are determined. If the state of charge of the fourth battery is less than the preset state of charge limit, then the second safe power is determined based on the state of charge difference between the third battery state of charge and the preset state of charge limit, the installed capacity of the battery energy storage system and the duration of the current preset sub-time period, and the second target power of the current preset sub-time period is determined based on the second safe power and the discharge loss of the battery energy storage system.

6. The method for determining the optimal pre-dated reporting curve as described in claim 5, characterized in that, After the steps of determining the third battery state of charge of the battery energy storage system at the start time of the current preset sub-time period and the fourth battery state of charge of the battery energy storage system at the end time of the current preset sub-time period, the method further includes: If the state of charge of the fourth battery is not less than the preset minimum state of charge of the battery, then the second target power for the current preset sub-time period is determined based on the installed rated power of the battery energy storage system and the discharge loss of the battery energy storage system.

7. The method for determining the optimal day-ahead reporting curve as described in claim 1, characterized in that, The step of determining the predicted battery state of charge at 00:00 on the second day based on the actual battery state of charge and the interval planned guidance power includes: The ending battery charge state of the current preset sub-time period is determined based on the starting battery charge state of the battery energy storage system at the start time of the preset sub-time period, the planned guidance power of the current preset sub-time period, and the duration of the preset sub-time period; wherein, the starting battery charge state of the preset sub-time period in which the preset time is located is the actual battery charge state. The starting battery charge state for the next preset sub-period is determined based on the comparison between the ending battery charge state and the preset upper and lower limits of the battery charge state, until the predicted battery charge state at 0:00 on the second day is determined.

8. The method for determining the optimal pre-dated reporting curve as described in claim 7, characterized in that, The step of determining the starting battery charge state of the next preset sub-time period based on the comparison result between the ending battery charge state and the preset upper and lower limits of battery charge state includes: If the comparison result is that the end battery charge state is less than the preset battery charge state limit, then the start battery charge state of the next preset sub-time period is the preset battery charge state limit. If the comparison result is that the end battery charge state is greater than the preset battery charge state upper limit, then the start battery charge state of the next preset sub-time period is the preset battery charge state upper limit. If the comparison result is that the ending battery charge state is not less than the preset battery charge state limit and not greater than the preset battery charge state upper limit, then the ending battery charge state is taken as the starting battery charge state of the next preset sub-time period.

9. A device for determining the optimal date-of-declaration curve, characterized in that, The device for determining the optimal date-of-declaration curve includes: The revenue determination module is used to determine the first cumulative revenue of the previous period based on the first day-ahead reporting curve of the previous period, and to determine the second cumulative revenue of the previous period based on the second day-ahead reporting curve of the previous period. The day-ahead reporting curve refers to the planned power operation curve for each day of any period. The curve determination module is used to determine the electricity price corresponding to the larger of the first cumulative revenue and the second cumulative revenue as the target electricity price, and to determine the optimal daily reporting curve for each day in the current period by optimizing the maximum revenue based on the target electricity price. The device for determining the optimal date-of-declaration curve further includes: The acquisition module is used to acquire the actual battery state of charge of the battery energy storage system at a preset time before the application deadline, as well as the planned guidance power of the interval from the preset time of the previous day to 24:00 of the previous day in the optimal application curve of the previous day. The prediction module is used to determine the predicted battery state of charge at 0:00 on the second day based on the actual battery state of charge and the interval planned guidance power. The optimization module is used to determine the first-day advance declaration curve corresponding to the predicted electricity price on the second day through maximum profit optimization based on the predicted electricity price and the predicted battery state of charge; and to determine the second-day advance declaration curve corresponding to the predicted electricity price on the second day through maximum profit optimization based on the average real clearing price and the predicted battery state of charge.

10. A device for determining the optimal date-of-declaration curve, characterized in that, The device for determining the optimal date-of-report curve includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the method for determining the optimal date-of-report curve as described in any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the method for determining the optimal day-ahead reporting curve as described in any one of claims 1 to 8.

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