Method, device and medium for determining optimal plan guide power

Abstract

The application discloses a kind of optimal plan guiding power determination method, equipment and medium, belong to the technical field of battery energy storage, by electricity price time curve determines the second day of battery energy storage system optimization time period, adjusts the power of each preset sub time period in optimization time period and obtains plan guiding power, obtains the energy storage income corresponding to each preset sub time period plan guiding power, determines the plan guiding power corresponding to maximum energy storage income as the optimal plan guiding power of corresponding preset sub time period.The power of each preset sub time period in optimization time period is adjusted, and the energy storage income corresponding to each preset sub time period plan guiding power is determined, and the plan guiding power corresponding to maximum energy storage income is determined as the optimal plan guiding power of each preset sub time period.By optimization, the optimal plan guiding power of each time period corresponding to maximum user energy storage income is obtained, so as to accurately control the charge and discharge power of battery energy storage system at each moment within a day.

Description

Technical Field

[0001] This invention relates to the technical field of battery energy storage, and in particular to a method for determining optimal planned guidance power, a device for determining optimal planned guidance power, and a computer-readable storage medium. Background Technology

[0002] Currently, BESS (Battery Energy Storage System) can achieve peak shaving and valley filling by discharging during peak loads and charging during off-peak loads. For the power grid, using battery energy storage systems for peak shaving and valley filling can postpone equipment capacity upgrades, improve equipment utilization, and save on equipment replacement costs. For users, peak shaving and valley filling can generate economic benefits from the peak-valley electricity price difference. However, achieving peak shaving and valley filling by discharging during peak loads and charging during off-peak loads only roughly considers the relationship between the current load size and electricity price. It does not consider the impact of current charging and discharging actions on the future energy storage benefits and safety of the battery energy storage system for users, nor can it accurately control the discharge power of the battery energy storage system during peak loads and the charging power during off-peak loads to maximize the energy storage benefits for users. Summary of the Invention

[0003] The main objective of this invention is to provide a method for determining the optimal planned guidance power, a device for determining the optimal planned guidance power, and a computer-readable storage medium, aiming to solve the technical problem in the prior art that it is difficult to accurately control the charging and discharging power of a battery energy storage system at different times of the day.

[0004] To achieve the above objectives, the present invention provides a method for determining the optimal planning guidance power, the method comprising the following steps:

[0005] Determine the optimal time period for the next day based on the electricity price time curve;

[0006] The planned guidance power is obtained by adjusting the power of each preset sub-time period in the optimization time period, and the energy storage revenue corresponding to the planned guidance power of each preset sub-time period is obtained.

[0007] The planned guidance power corresponding to the maximum energy storage revenue of the battery energy storage system during the optimization period is determined as the optimal planned guidance power for each preset sub-time period.

[0008] Optionally, the step of determining the optimal time period for the next day based on the electricity price time curve includes:

[0009] The electricity price time curve is marked with time period characteristics to determine the characteristic time period of the electricity price on the second day. The characteristic time period includes peak period and valley period. The start time of the optimization time period is 0:00 on the second day.

[0010] If the last characteristic period of the electricity price time curve is a peak period, then the end time of the optimization period is 24:00;

[0011] If the last characteristic period of the electricity price time curve is a valley period, then the end time of the optimization time period is the start time of the valley period.

[0012] Optionally, before the step of obtaining the energy storage revenue corresponding to the planned guided power for each preset sub-time period, the method further includes:

[0013] The charging power boundary and discharging power boundary of the battery energy storage system in each preset sub-time period are determined based on the overload boundary and reverse current boundary of the transformer of the battery energy storage system and the predicted load of each preset sub-time period.

[0014] If the planned guidance power is less than the discharge power boundary, then the discharge power boundary shall be used as the planned guidance power;

[0015] If the planned guidance power is greater than the charging power boundary, then the charging power boundary is taken as the planned guidance power; wherein, the discharge power is a negative value and the charging power is a positive value.

[0016] Optionally, the step of determining the charging power boundary and discharging power boundary of the battery energy storage system for each preset sub-time period based on the overload boundary and reverse current boundary of the battery energy storage system transformer and the predicted load of each preset sub-time period includes:

[0017] The predicted load for each preset sub-time period is determined based on the preset predicted load curve;

[0018] The charging power boundary for each preset sub-time period is determined to be the smaller value between the overload boundary and the difference between the predicted load and the maximum charging limit of the battery energy storage system.

[0019] The discharge power boundary for each preset sub-time period is determined to be the larger value between the difference between the predicted load and the reverse current boundary and the maximum discharge limit of the battery energy storage system.

[0020] Optionally, the step of obtaining the energy storage revenue corresponding to the planned guidance power for each preset sub-time period includes:

[0021] Determine the first state of charge of the battery energy storage system at the start time of each preset sub-time period, and determine the first comparison result between the first state of charge and the preset upper and lower limits of the battery state of charge.

[0022] Determine the second battery state of charge of the battery energy storage system at the end of the current preset sub-time period, and determine the second comparison result between the second battery state of charge and the preset upper and lower limits of the battery state of charge;

[0023] The energy storage revenue corresponding to the planned guidance power in the preset sub-time period is determined based on the first comparison result and the second comparison result; wherein, the energy storage revenue is negative when the battery energy storage system is charging, and positive when the battery energy storage system is discharging.

[0024] Optionally, the step of determining the energy storage revenue corresponding to the planned guidance power for the preset sub-time period based on the first comparison result and the second comparison result includes:

[0025] If the first comparison result indicates that the first battery state of charge is between the preset upper and lower limits of the battery state of charge, then

[0026] When the planned guidance power is the charging power, if the second comparison result is that the second battery state of charge is less than the preset upper limit of battery state of charge, then the energy storage revenue of the current preset sub-time period is determined according to the electricity price of the current preset sub-time period, the planned guidance power, and the duration of the current preset sub-time period; if the second comparison result is that the second battery state of charge is not less than the preset upper limit of battery state of charge, then the energy storage revenue of the current preset sub-time period is determined according to the electricity price of the current preset sub-time period, the state of charge difference between the preset upper limit of battery state of charge and the first battery state of charge, and the installed capacity of the battery energy storage system.

[0027] When the planned guidance power is the discharge power, if the second comparison result is that the state of charge of the second battery is greater than the preset battery state of charge limit, then the energy storage revenue for the current preset sub-time period is determined based on the electricity price of the current preset sub-time period, the planned guidance power, and the duration of the current preset sub-time period; if the second comparison result is that the state of charge of the second battery is not greater than the preset battery state of charge limit, then the energy storage revenue for the current preset sub-time period is determined based on the state of charge difference between the state of charge of the first battery and the preset battery state of charge limit, the installed capacity of the battery energy storage system, and the electricity price of the current preset sub-time period.

[0028] Optionally, the step of determining the energy storage revenue corresponding to the planned guidance power for the preset sub-time period based on the first comparison result and the second comparison result further includes:

[0029] If the first comparison result indicates that the first battery state of charge is greater than the preset upper limit of battery state of charge, then

[0030] When the planned guidance power is the charging power, the energy storage revenue is the current energy storage revenue minus the preset revenue penalty value;

[0031] When the planned guidance power is the discharge power, if the second comparison result is that the state of charge of the second battery is greater than the preset battery state of charge limit, then the energy storage revenue for the current preset sub-time period is determined based on the electricity price of the current preset sub-time period, the planned guidance power, and the duration of the current preset sub-time period; if the second comparison result is that the state of charge of the second battery is not greater than the preset battery state of charge limit, then the energy storage revenue for the current preset sub-time period is determined based on the state of charge difference between the state of charge of the first battery and the preset battery state of charge limit, the installed capacity of the battery energy storage system, and the electricity price of the current preset sub-time period.

[0032] Optionally, the step of determining the energy storage revenue corresponding to the planned guidance power for the preset sub-time period based on the first comparison result and the second comparison result further includes:

[0033] If the first comparison result indicates that the state of charge of the first battery is less than the preset lower limit of the battery state of charge, then

[0034] When the planned guidance power is the charging power, if the second comparison result is that the second battery state of charge is less than the preset upper limit of battery state of charge, then the energy storage revenue of the current preset sub-time period is determined according to the electricity price of the current preset sub-time period, the planned guidance power, and the duration of the current preset sub-time period; if the second comparison result is that the second battery state of charge is not less than the preset upper limit of battery state of charge, then the energy storage revenue of the current preset sub-time period is determined according to the electricity price of the current preset sub-time period, the state of charge difference between the preset upper limit of battery state of charge and the first battery state of charge, and the installed capacity of the battery energy storage system.

[0035] When the planned guidance power is the discharge power, the energy storage revenue is the current energy storage revenue minus a preset revenue penalty value.

[0036] Optionally, the step of obtaining the energy storage revenue corresponding to the planned guided power for each preset sub-time period further includes:

[0037] Obtain the total amount of temporary charging and the total amount of temporary discharging corresponding to the end time of each preset sub-time period, and determine the equivalent number of full charging times based on the total amount of temporary charging and the installed capacity of the battery energy storage system, and determine the equivalent number of full discharging times based on the total amount of temporary discharging and the installed capacity of the battery energy storage system.

[0038] If the equivalent number of full charge cycles exceeds the preset charging cycle limit or the equivalent number of full discharge cycles exceeds the preset discharging cycle limit, then the energy storage revenue is the current energy storage revenue minus the preset revenue penalty value.

[0039] Optionally, after the step of obtaining the energy storage revenue corresponding to the planned guided power for each preset sub-time period, the method further includes:

[0040] The surplus power of the battery energy storage system at the start of the optimization period, the total discharge and total charge at the end of the optimization period are determined, and the effective total discharge of the battery energy storage system is determined as the difference between the total discharge and the surplus power. Based on the energy storage revenue, the total discharge and the effective total discharge, the effective total revenue of the battery energy storage system at the end of the optimization period is determined.

[0041] The average effective revenue per kilowatt-hour is determined based on the total effective revenue and the total charging amount. If the average effective revenue is less than the preset peak-valley price difference arbitrage lower limit, the energy storage revenue of the battery energy storage system during the optimization period is determined to be the current energy storage revenue minus the preset revenue penalty value.

[0042] Optionally, after the step of determining the planned guidance power corresponding to the maximum energy storage revenue of the battery energy storage system during the optimization period as the optimal planned guidance power for each preset sub-time period, the method further includes:

[0043] If the last characteristic period of the electricity price time curve is a valley period, then the charging power boundary of each preset sub-period of the valley period is determined according to the overload boundary of the transformer of the battery energy storage system, the predicted load of each preset sub-period of the valley period, and the maximum charging limit of the battery energy storage system.

[0044] The optimal planned guidance power for each preset sub-time period of the valley period is determined as the charging power boundary for each preset sub-time period of the valley period, until the end of the valley period or until the battery state of charge during the valley period is equal to the preset upper limit of the battery state of charge of the battery energy storage system.

[0045] Furthermore, to achieve the above objectives, the present invention also provides an apparatus for determining optimal planning guidance power, 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 optimal planning guidance power as described above.

[0046] Furthermore, to achieve the above objectives, the present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method for determining the optimal planning guidance power as described above.

[0047] This invention provides a method, device, and computer-readable storage medium for determining optimal planned guidance power. The method involves determining the optimization period for the next day based on an electricity price time curve; adjusting the power of each preset sub-period within the optimization period to obtain the planned guidance power; acquiring the energy storage revenue corresponding to the planned guidance power in each preset sub-period; and determining the planned guidance power corresponding to the maximum energy storage revenue of the battery energy storage system during the optimization period as the optimal planned guidance power for that preset sub-period.

[0048] First, the optimization period for the battery energy storage system on the second day is determined by the electricity price time curve. Then, the power of each preset sub-period in the optimization period is adjusted to obtain the planned guidance power. The energy storage revenue corresponding to the planned guidance power of each preset sub-period is obtained. Finally, the planned guidance power corresponding to the maximum energy storage revenue of the battery energy storage system in the optimization period is determined as the optimal planned guidance power for each preset sub-period.

[0049] By continuously adjusting the power of each preset sub-time period within the optimization period and determining the energy storage benefit corresponding to the planned guidance power of each preset sub-time period, the planned guidance power corresponding to the maximum energy storage benefit is determined as the optimal planned guidance power for each preset sub-time period. Thus, based on peak shaving and valley filling, the optimal planned guidance power for each time period corresponding to maximizing user energy storage benefit is determined through optimization, thereby precisely controlling the charging and discharging power of the battery energy storage system at various times throughout the day. Attached Figure Description

[0050] 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;

[0051] Figure 2 This is a flowchart illustrating an embodiment of a method for determining optimal planning guidance power according to the present invention;

[0052] Figure 3 This is a flowchart illustrating step S10 in one embodiment of the method for determining optimal planning guidance power according to the present invention.

[0053] Figure 4 This is a schematic diagram of the first step S20 in an embodiment of the method for determining the optimal planning guidance power of the present invention;

[0054] Figure 5 This is a schematic diagram of the second step S20 in an embodiment of the method for determining the optimal planning guidance power of the present invention;

[0055] Figure 6 This is a flowchart illustrating another embodiment of the method for determining the optimal planning guidance power according to the present invention.

[0056] 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

[0057] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0058] 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.

[0059] 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 and 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 Wireless Fidelity (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. Optionally, the memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0060] 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.

[0061] 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.

[0062] exist Figure 1In 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:

[0063] Determine the optimal time period for the next day based on the electricity price time curve;

[0064] The planned guidance power is obtained by adjusting the power of each preset sub-time period in the optimization time period, and the energy storage revenue corresponding to the planned guidance power of each preset sub-time period is obtained.

[0065] The planned guidance power corresponding to the maximum energy storage revenue of the battery energy storage system during the optimization period is determined as the optimal planned guidance power for each preset sub-time period.

[0066] Furthermore, the processor 1001 can call a computer program stored in the memory 1005 and also perform the following operations:

[0067] The step of determining the optimal time period for the next day based on the electricity price time curve includes:

[0068] The electricity price time curve is marked with time period characteristics to determine the characteristic time period of the electricity price on the second day. The characteristic time period includes peak period and valley period. The start time of the optimization time period is 0:00 on the second day.

[0069] If the last characteristic period of the electricity price time curve is a peak period, then the end time of the optimization period is 24:00;

[0070] If the last characteristic period of the electricity price time curve is a valley period, then the end time of the optimization time period is the start time of the valley period.

[0071] Furthermore, the processor 1001 can call a computer program stored in the memory 1005 and also perform the following operations:

[0072] Before the step of obtaining the energy storage revenue corresponding to the planned guidance power for each preset sub-time period, the method further includes:

[0073] The charging power boundary and discharging power boundary of the battery energy storage system in each preset sub-time period are determined based on the overload boundary and reverse current boundary of the transformer of the battery energy storage system and the predicted load of each preset sub-time period.

[0074] If the planned guidance power is less than the discharge power boundary, then the discharge power boundary shall be used as the planned guidance power;

[0075] If the planned guidance power is greater than the charging power boundary, then the charging power boundary is taken as the planned guidance power; wherein, the discharge power is a negative value and the charging power is a positive value.

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

[0077] The step of determining the charging power boundary and discharging power boundary of the battery energy storage system for each preset sub-time period based on the overload boundary and reverse current boundary of the battery energy storage system transformer and the predicted load of each preset sub-time period includes:

[0078] The predicted load for each preset sub-time period is determined based on the preset predicted load curve;

[0079] The charging power boundary for each preset sub-time period is determined to be the smaller value between the overload boundary and the difference between the predicted load and the maximum charging limit of the battery energy storage system.

[0080] The discharge power boundary for each preset sub-time period is determined to be the larger value between the difference between the predicted load and the reverse current boundary and the maximum discharge limit of the battery energy storage system.

[0081] Furthermore, the processor 1001 can call a computer program stored in the memory 1005 and also perform the following operations:

[0082] The step of obtaining the energy storage revenue corresponding to the planned guidance power for each preset sub-time period includes:

[0083] Determine the first state of charge of the battery energy storage system at the start time of each preset sub-time period, and determine the first comparison result between the first state of charge and the preset upper and lower limits of the battery state of charge.

[0084] Determine the second battery state of charge of the battery energy storage system at the end of the current preset sub-time period, and determine the second comparison result between the second battery state of charge and the preset upper and lower limits of the battery state of charge;

[0085] The energy storage revenue corresponding to the planned guidance power in the preset sub-time period is determined based on the first comparison result and the second comparison result; wherein, the energy storage revenue is negative when the battery energy storage system is charging, and positive when the battery energy storage system is discharging.

[0086] Furthermore, the processor 1001 can call a computer program stored in the memory 1005 and also perform the following operations:

[0087] The step of determining the energy storage revenue corresponding to the planned guidance power for the preset sub-time period based on the first comparison result and the second comparison result includes:

[0088] If the first comparison result indicates that the first battery state of charge is between the preset upper and lower limits of the battery state of charge, then

[0089] When the planned guidance power is the charging power, if the second comparison result is that the second battery state of charge is less than the preset upper limit of battery state of charge, then the energy storage revenue of the current preset sub-time period is determined according to the electricity price of the current preset sub-time period, the planned guidance power, and the duration of the current preset sub-time period; if the second comparison result is that the second battery state of charge is not less than the preset upper limit of battery state of charge, then the energy storage revenue of the current preset sub-time period is determined according to the electricity price of the current preset sub-time period, the state of charge difference between the preset upper limit of battery state of charge and the first battery state of charge, and the installed capacity of the battery energy storage system.

[0090] When the planned guidance power is the discharge power, if the second comparison result is that the state of charge of the second battery is greater than the preset battery state of charge limit, then the energy storage revenue for the current preset sub-time period is determined based on the electricity price of the current preset sub-time period, the planned guidance power, and the duration of the current preset sub-time period; if the second comparison result is that the state of charge of the second battery is not greater than the preset battery state of charge limit, then the energy storage revenue for the current preset sub-time period is determined based on the state of charge difference between the state of charge of the first battery and the preset battery state of charge limit, the installed capacity of the battery energy storage system, and the electricity price of the current preset sub-time period.

[0091] Furthermore, the processor 1001 can call a computer program stored in the memory 1005 and also perform the following operations:

[0092] The step of determining the energy storage revenue corresponding to the planned guidance power for the preset sub-time period based on the first comparison result and the second comparison result further includes:

[0093] If the first comparison result indicates that the first battery state of charge is greater than the preset upper limit of battery state of charge, then

[0094] When the planned guidance power is the charging power, the energy storage revenue is the current energy storage revenue minus the preset revenue penalty value;

[0095] When the planned guidance power is the discharge power, if the second comparison result is that the state of charge of the second battery is greater than the preset battery state of charge limit, then the energy storage revenue for the current preset sub-time period is determined based on the electricity price of the current preset sub-time period, the planned guidance power, and the duration of the current preset sub-time period; if the second comparison result is that the state of charge of the second battery is not greater than the preset battery state of charge limit, then the energy storage revenue for the current preset sub-time period is determined based on the state of charge difference between the state of charge of the first battery and the preset battery state of charge limit, the installed capacity of the battery energy storage system, and the electricity price of the current preset sub-time period.

[0096] Furthermore, the processor 1001 can call a computer program stored in the memory 1005 and also perform the following operations:

[0097] The step of determining the energy storage revenue corresponding to the planned guidance power for the preset sub-time period based on the first comparison result and the second comparison result further includes:

[0098] If the first comparison result indicates that the state of charge of the first battery is less than the preset lower limit of the battery state of charge, then

[0099] When the planned guidance power is the charging power, if the second comparison result is that the second battery state of charge is less than the preset upper limit of battery state of charge, then the energy storage revenue of the current preset sub-time period is determined according to the electricity price of the current preset sub-time period, the planned guidance power, and the duration of the current preset sub-time period; if the second comparison result is that the second battery state of charge is not less than the preset upper limit of battery state of charge, then the energy storage revenue of the current preset sub-time period is determined according to the electricity price of the current preset sub-time period, the state of charge difference between the preset upper limit of battery state of charge and the first battery state of charge, and the installed capacity of the battery energy storage system.

[0100] When the planned guidance power is the discharge power, the energy storage revenue is the current energy storage revenue minus a preset revenue penalty value.

[0101] Furthermore, the processor 1001 can call a computer program stored in the memory 1005 and also perform the following operations:

[0102] The step of obtaining the energy storage revenue corresponding to the planned guidance power for each preset sub-time period further includes:

[0103] Obtain the total amount of temporary charging and the total amount of temporary discharging corresponding to the end time of each preset sub-time period, and determine the equivalent number of full charging times based on the total amount of temporary charging and the installed capacity of the battery energy storage system, and determine the equivalent number of full discharging times based on the total amount of temporary discharging and the installed capacity of the battery energy storage system.

[0104] If the equivalent number of full charge cycles exceeds the preset charging cycle limit or the equivalent number of full discharge cycles exceeds the preset discharging cycle limit, then the energy storage revenue is the current energy storage revenue minus the preset revenue penalty value.

[0105] Furthermore, the processor 1001 can call a computer program stored in the memory 1005 and also perform the following operations:

[0106] After the step of obtaining the energy storage revenue corresponding to the planned guidance power for each preset sub-time period, the method further includes:

[0107] The surplus power of the battery energy storage system at the start of the optimization period, the total discharge and total charge at the end of the optimization period are determined, and the effective total discharge of the battery energy storage system is determined as the difference between the total discharge and the surplus power. Based on the energy storage revenue, the total discharge and the effective total discharge, the effective total revenue of the battery energy storage system at the end of the optimization period is determined.

[0108] The average effective revenue per kilowatt-hour is determined based on the total effective revenue and the total charging amount. If the average effective revenue is less than the preset peak-valley price difference arbitrage lower limit, the energy storage revenue of the battery energy storage system during the optimization period is determined to be the current energy storage revenue minus the preset revenue penalty value.

[0109] Reference Figure 2 , Figure 2 This is a flowchart illustrating an embodiment of a method for determining optimal planning guidance power according to the present invention. This embodiment of the present invention provides a method for determining optimal planning guidance power, which includes the following steps:

[0110] Step S10: Determine the optimal time period for the next day based on the electricity price time curve;

[0111] The electricity price time curve represents the functional relationship between electricity prices at different times. Peak hours are when the battery storage system discharges, and off-peak hours are when it charges, thus achieving peak shaving and valley filling. There is a standard electricity price for peak hours and off-peak hours; prices above this standard are considered high, and prices below are considered low. The standard varies by region and province, resulting in different published high and low prices. In this embodiment, the source of the electricity price time curve is not limited; it can be published by different regions and provinces, or it can be based on predicted local electricity prices at different times for the location of the battery storage system. After determining the electricity price time curve for the next day, the optimization period for the next day is determined based on this curve. Within the optimization period, the power of each preset sub-period is adjusted to obtain the optimal planned guidance power for each preset sub-period corresponding to the maximum energy storage revenue.

[0112] Optional, refer to Figure 3 The step of determining the optimal time period for the next day based on the electricity price time curve includes:

[0113] Step S101: Mark the time period characteristics of the electricity price time curve to determine the characteristic time period of the electricity price on the second day. The characteristic time period includes peak period and valley period. The start time of the optimization time period is 0:00 on the second day.

[0114] Step S102: If the last characteristic period of the electricity price time curve is a peak period, then the end time of the optimization period is 24:00.

[0115] Step S103: If the last characteristic period of the electricity price time curve is a valley period, then the end time of the optimization time period is the start time of the valley period.

[0116] First, the start time of the optimization period is determined to be 00:00 on the second day. Then, the electricity price time curve is marked with period characteristics to identify the peak periods with high electricity prices and the off-peak periods with low electricity prices on the second day. Finally, if the last characteristic period of the electricity price time curve is a peak period, the end time of the optimization period is determined to be 24:00; if the last characteristic period of the electricity price time curve is an off-peak period, the end time of the optimization period is determined to be the start time of the last off-peak period. If the last characteristic period is an off-peak period, then optimization is not required for the last off-peak period; low-price charging of the battery storage system is sufficient. Therefore, the optimization period for the second day is determined to be from 00:00 on the second day until the end time of the last peak period.

[0117] Step S20: Adjust the power of each preset sub-time period in the optimization time period to obtain the planned guidance power, and obtain the energy storage revenue corresponding to the planned guidance power in each preset sub-time period.

[0118] A preset number of sub-time periods are pre-set within the optimization period. After determining the optimization period for the next day, the power of each preset sub-time period within the optimization period is continuously adjusted to obtain the planned guidance power, and the energy storage revenue corresponding to the planned guidance power of each preset sub-time period is obtained. In this embodiment, the number of sub-time periods and the duration of each sub-time period are not limited. Preferably, a 24-hour day is divided into 96 sub-time periods, each sub-time period is 15 minutes long, and one or more sub-time periods are included in peak and off-peak periods.

[0119] Step S30: Determine the planned guidance power corresponding to each preset sub-time period for the maximum energy storage benefit during the optimization period of the battery energy storage system as the optimal planned guidance power for each preset sub-time period.

[0120] After determining the energy storage revenue for each preset sub-time period, the energy storage revenues of all preset sub-time periods are summed to determine the planned guidance power for each preset sub-time period corresponding to the maximum energy storage revenue of the battery energy storage system during the optimization period. The planned guidance power corresponding to the maximum revenue is then taken as the optimal planned guidance power for each preset sub-time period.

[0121] In this embodiment, the optimization time period for the next day is determined based on the electricity price time curve; the power of each preset sub-time period in the optimization time period is adjusted to obtain the planned guidance power, and the energy storage revenue corresponding to the planned guidance power in each preset sub-time period is obtained; the planned guidance power corresponding to the maximum energy storage revenue of the battery energy storage system in the optimization time period is determined as the optimal planned guidance power for each preset sub-time period.

[0122] First, the optimization period for the battery energy storage system on the second day is determined by the electricity price time curve. Then, the power of each preset sub-period in the optimization period is adjusted to obtain the planned guidance power. The energy storage revenue corresponding to the planned guidance power of each preset sub-period is obtained. Finally, the planned guidance power corresponding to the maximum energy storage revenue of the battery energy storage system in the optimization period is determined as the optimal planned guidance power for each preset sub-period.

[0123] By continuously adjusting the power of each preset sub-time period within the optimization period and determining the energy storage benefit corresponding to the planned guidance power of each preset sub-time period, the planned guidance power corresponding to the maximum energy storage benefit is determined as the optimal planned guidance power for each preset sub-time period. Thus, based on peak shaving and valley filling, the optimal planned guidance power for each time period corresponding to maximizing user energy storage benefit is determined through optimization, thereby precisely controlling the charging and discharging power of the battery energy storage system at various times throughout the day.

[0124] In another embodiment of the method for determining the optimal planned guidance power provided by the present invention, before the step of obtaining the energy storage revenue corresponding to the planned guidance power for each preset sub-time period, the method further includes:

[0125] The charging power boundary and discharging power boundary of the battery energy storage system in each preset sub-time period are determined based on the overload boundary and reverse current boundary of the transformer of the battery energy storage system and the predicted load of each preset sub-time period.

[0126] If the planned guidance power is less than the discharge power boundary, then the discharge power boundary shall be used as the planned guidance power;

[0127] If the planned guidance power is greater than the charging power boundary, then the charging power boundary is taken as the planned guidance power; wherein, the discharge power is a negative value and the charging power is a positive value.

[0128] In the optimization process, in addition to maximizing the user's energy storage benefits, it is also necessary to consider and ensure the safety of the battery energy storage system. In this embodiment, based on the overload boundary and reverse current boundary of the battery energy storage system transformer, as well as the predicted load Load i for each preset sub-time period (i represents the sequence number of the preset sub-time period, and the same applies below), the charging power boundary charge_up_i and the discharging power boundary dis_charge_up_i of the battery energy storage system in each preset sub-time period are determined.

[0129] If the planned guidance power X[i] is less than the discharge power boundary dis_charge_up_i, then the discharge power boundary dis_charge_up_i is used as the planned guidance power X[i]. If the planned guidance power X[i] is greater than the charging power boundary charge_up_i, then the charging power boundary charge_up_i is used as the planned guidance power X[i]. Here, discharge power is negative and charging power is positive, and the positive and negative values ​​of charge and discharge power are manually set. This ensures that the planned guidance power X[i] is within the range of discharge power boundary dis_charge_up_i ≤ X[i] ≤ charging power boundary charge_up_i, guaranteeing the charging and discharging safety of the battery energy storage system.

[0130] Optionally, the step of determining the charging power boundary and discharging power boundary of the battery energy storage system for each preset sub-time period based on the overload boundary and reverse current boundary of the battery energy storage system transformer and the predicted load of each preset sub-time period includes:

[0131] The predicted load for each preset sub-time period is determined based on the preset predicted load curve;

[0132] The charging power boundary for each preset sub-time period is determined to be the smaller value between the overload boundary and the difference between the predicted load and the maximum charging limit of the battery energy storage system.

[0133] The discharge power boundary for each preset sub-time period is determined to be the larger value between the difference between the predicted load and the reverse current boundary and the maximum discharge limit of the battery energy storage system.

[0134] When determining the charging power boundary charge_up_i and discharging power boundary dis_up_i of the battery energy storage system for each preset sub-time period, the predicted load Load i for each preset sub-time period is first determined according to the preset predicted load curve. Here, the load is the power demand of the user-side equipment. Similar to the electricity price time curve, the preset predicted load curve is a function relationship of the load corresponding to different times.

[0135] Then, the charging power boundary charge_up_i for each preset sub-time period is determined to be the smaller value between the difference between the overload boundary and the predicted load Load i and the maximum charging limit of the battery energy storage system, that is, charge_up_i = MI N(overload boundary - Load i, maximum charging limit of energy storage), where the difference between the overload boundary and the predicted load Load i is the remaining safe charging power of the battery energy storage system, the overload boundary is the maximum load that the transformer can withstand, and the overload boundary = transformer capacity C * power factor PF * transformer derating factor - DI custom overload threshold.

[0136] Finally, the discharge power boundary di s_charge_up_i for each preset sub-time period is determined to be the larger value between the difference between the predicted load Load i and the reverse current boundary and the maximum discharge limit of the battery energy storage system, i.e., di s_charge_up_i = -MIN(Load i - reverse current boundary, - maximum discharge limit of energy storage), where the maximum discharge limit of energy storage is preceded by a negative sign to unify the expression with the negative discharge power. The reverse current boundary is a custom threshold D, and when the power is less than D, the battery energy storage system can be considered to be in reverse.

[0137] Furthermore, in cases where the battery storage system malfunctions or has low charge, it cannot be charged at its rated power. Therefore, there is a real-time maximum charging power limit. The minimum value is then selected when compared with the maximum discharge limit of the battery storage system, ensuring that the battery storage system has the corresponding charging power capability and ultimately guaranteeing the charging and discharging safety of the battery storage system.

[0138] Reference Figure 4 In another embodiment of the method for determining the optimal planned guidance power provided by the present invention, the step of obtaining the energy storage revenue corresponding to the planned guidance power for each preset sub-time period includes:

[0139] Step S201: Determine the first battery state of charge of the battery energy storage system at the start time of each preset sub-time period, and determine the first comparison result between the first battery state of charge and the preset upper and lower limits of the battery state of charge.

[0140] Step S202: Determine the second battery state of charge of the battery energy storage system at the end of the current preset sub-time period, and determine the second comparison result between the second battery state of charge and the preset upper and lower limits of the battery state of charge;

[0141] Step S203: Determine the energy storage revenue corresponding to the planned guidance power in the preset sub-time period based on the first comparison result and the second comparison result; wherein, the energy storage revenue is negative when the battery energy storage system is charging, and positive when the battery energy storage system is discharging.

[0142] When calculating the energy storage revenue corresponding to the planned guidance power X[i] for each preset sub-time period, the first battery state of charge (SBC) of the battery energy storage system at the start of each preset sub-time period is determined, along with the first comparison result between the first SBC and the preset upper and lower limits of the battery SBC. Then, the second SBC of the battery energy storage system at the end of the current preset sub-time period is determined, along with the second comparison result between the second SBC and the preset upper and lower limits of the battery SBC. Finally, the energy storage revenue corresponding to the planned guidance power X[i] for the preset sub-time period is determined based on the first and second comparison results, thus determining the energy storage revenue under different battery SBCs based on different comparison results. The energy storage revenue is negative when the battery energy storage system is charging and positive when it is discharging, thus providing a unified representation with the negative value of the discharge power. The preset upper and lower limits of the battery SBC are artificially set safety boundaries (0%, 100%) for the battery SBC, and do not correspond to endpoints, representing the inability to completely discharge or fully charge the battery energy storage system.

[0143] The first battery state of charge (SOC) at the start of the optimization period of the battery energy storage system (0:00 on the current day) is the battery state of charge at 24:00 on the previous day (the current day). The second battery state of charge (tmpSOC) at the end of the first preset sub-period is calculated based on the sub-period duration (t), the battery state of charge at 0:00 on the current day, and the planned guidance power (X[i]) of the first preset sub-period. The second battery state of charge at the end of the first preset sub-period is the first battery state of charge at the start of the second preset sub-period. Thus, the first battery state of charge (SOC) at the start of any subsequent preset sub-period is calculated in the same way. That is, tmpSOC = SOC + (X[i] * t / capacity).

[0144] Optionally, the step of determining the energy storage revenue corresponding to the planned guidance power for the preset sub-time period based on the first comparison result and the second comparison result includes:

[0145] If the first comparison result indicates that the first battery state of charge is between the preset upper and lower limits of the battery state of charge, then

[0146] When the planned guidance power is the charging power, if the second comparison result is that the second battery state of charge is less than the preset upper limit of battery state of charge, then the energy storage revenue of the current preset sub-time period is determined according to the electricity price of the current preset sub-time period, the planned guidance power, and the duration of the current preset sub-time period; if the second comparison result is that the second battery state of charge is not less than the preset upper limit of battery state of charge, then the energy storage revenue of the current preset sub-time period is determined according to the electricity price of the current preset sub-time period, the state of charge difference between the preset upper limit of battery state of charge and the first battery state of charge, and the installed capacity of the battery energy storage system.

[0147] When the planned guidance power is the discharge power, if the second comparison result is that the state of charge of the second battery is greater than the preset battery state of charge limit, then the energy storage revenue for the current preset sub-time period is determined based on the electricity price of the current preset sub-time period, the planned guidance power, and the duration of the current preset sub-time period; if the second comparison result is that the state of charge of the second battery is not greater than the preset battery state of charge limit, then the energy storage revenue for the current preset sub-time period is determined based on the state of charge difference between the state of charge of the first battery and the preset battery state of charge limit, the installed capacity of the battery energy storage system, and the electricity price of the current preset sub-time period.

[0148] When determining the energy storage revenue corresponding to the planned guidance power X[i] for the preset sub-time period based on the first comparison result and the second comparison result, if the first comparison result indicates that the first battery state of charge is between the preset upper and lower limits of the battery state of charge, i.e., the preset lower limit of the battery state of charge SOC_down ≤ SOC (State of Charge, or the current remaining battery capacity) ≤ the preset upper limit of the battery state of charge SOC_up, then

[0149] When the planned guidance power is the charging power and X[i] > 0, if the second comparison result is that the second battery state of charge tmpSOC is less than the preset battery state of charge upper limit SOC_up, then the energy storage revenue benef it for the current preset sub-period is determined according to the electricity price Ei of the current preset sub-period, the planned guidance power X[i], and the duration t of the current preset sub-period, i.e., benef it = benef it - Ei * X[i] * t; if the second comparison result is that the second battery state of charge tmpSOC is not less than the preset battery state of charge upper limit SOC_up, then the energy storage revenue for the current preset sub-period is determined according to the electricity price Ei of the current preset sub-period, the state of charge difference between the preset battery state of charge upper limit SOC_up and the first battery state of charge SOC, and the installed capacity capacity of the battery energy storage system, i.e., benef it = benef it - (SOC_up - SOC) * capacity * Ei;

[0150] When the planned guidance power is the discharge power and X[i] < 0, if the second comparison result is that the second battery state of charge tmpSOC is greater than the preset battery state of charge limit SOC_down, then the energy storage revenue benef it for the current preset sub-period is determined based on the electricity price Ei of the current preset sub-period, the planned guidance power X[i], and the duration t of the current preset sub-period, i.e., benef it = benef it - Ei * X[i] * t; if the second comparison result is that the second battery state of charge tmpSOC is not greater than the preset battery state of charge limit SOC_down, then the energy storage revenue for the current preset sub-period is determined based on the state of charge difference between the first battery state of charge SOC and the preset battery state of charge limit SOC_down, the installed capacity of the battery energy storage system, and the electricity price Ei of the current preset sub-period, i.e., benef it = benef it + (SOC - SOC_down) * capacity * Ei.

[0151] Optionally, the step of determining the energy storage revenue corresponding to the planned guidance power for the preset sub-time period based on the first comparison result and the second comparison result further includes:

[0152] If the first comparison result indicates that the first battery state of charge is greater than the preset upper limit of battery state of charge, then

[0153] When the planned guidance power is the charging power, the energy storage revenue is the current energy storage revenue minus the preset revenue penalty value;

[0154] When the planned guidance power is the discharge power, if the second comparison result is that the state of charge of the second battery is greater than the preset battery state of charge limit, then the energy storage revenue for the current preset sub-time period is determined based on the electricity price of the current preset sub-time period, the planned guidance power, and the duration of the current preset sub-time period; if the second comparison result is that the state of charge of the second battery is not greater than the preset battery state of charge limit, then the energy storage revenue for the current preset sub-time period is determined based on the state of charge difference between the state of charge of the first battery and the preset battery state of charge limit, the installed capacity of the battery energy storage system, and the electricity price of the current preset sub-time period.

[0155] When determining the energy storage revenue corresponding to the planned guidance power X[i] for the preset sub-time period based on the first comparison result and the second comparison result, if the first comparison result is that the first battery state of charge (SOC) is greater than the preset upper limit of battery state of charge (SOC_up), then

[0156] When the planned guidance power X[i] is the charging power and X[i] > 0, the energy storage benefit is the current energy storage benefit minus the preset benefit penalty value, that is, benefit = benefit - penalty;

[0157] When the planned guidance power X[i] is the discharge power, if the second comparison result is that the second battery state of charge tmpSOC is greater than the preset battery state of charge limit SOC_down, then the energy storage benefit of the current preset sub-period is determined according to the electricity price Ei of the current preset sub-period, the planned guidance power X[i], and the duration t of the current preset sub-period, i.e., benefit it = benefit - (E i) * X[i] * t; if the second comparison result is that the second battery state of charge tmpSOC is not greater than the preset battery state of charge limit SOC_down, then the energy storage benefit of the current preset sub-period is determined according to the state of charge difference between the first battery state of charge SOC and the preset battery state of charge limit SOC_down, the installed capacity of the battery energy storage system, and the electricity price Ei of the current preset sub-period, i.e., benefit it = benefit it + (SOC - SOC_down) * capacity * Ei.

[0158] Optionally, the step of determining the energy storage revenue corresponding to the planned guidance power for the preset sub-time period based on the first comparison result and the second comparison result further includes:

[0159] If the first comparison result indicates that the state of charge of the first battery is less than the preset lower limit of the battery state of charge, then

[0160] When the planned guidance power is the charging power, if the second comparison result is that the second battery state of charge is less than the preset upper limit of battery state of charge, then the energy storage revenue of the current preset sub-time period is determined according to the electricity price of the current preset sub-time period, the planned guidance power, and the duration of the current preset sub-time period; if the second comparison result is that the second battery state of charge is not less than the preset upper limit of battery state of charge, then the energy storage revenue of the current preset sub-time period is determined according to the electricity price of the current preset sub-time period, the state of charge difference between the preset upper limit of battery state of charge and the first battery state of charge, and the installed capacity of the battery energy storage system.

[0161] When the planned guidance power is the discharge power, the energy storage revenue is the current energy storage revenue minus a preset revenue penalty value.

[0162] When determining the energy storage revenue corresponding to the planned guidance power X[i] for a preset sub-time period based on the first comparison result and the second comparison result, if the first comparison result indicates that the state of charge (SOC) of the first battery is less than the preset battery state of charge limit (SOC_down), then

[0163] When the planned guidance power X[i] is the charging power, if the second comparison result is that the second battery state of charge tmpSOC is less than the preset battery state of charge upper limit SOC_up, then the energy storage benefit benef it for the current preset sub-period is determined according to the electricity price Ei of the current preset sub-period, the planned guidance power X[i], and the duration t of the current preset sub-period, i.e., benef it = benef it - Ei * X[i] * t; if the second comparison result is that the second battery state of charge tmpSOC is not less than the preset battery state of charge upper limit SOC_up, then the energy storage benefit for the current preset sub-period is determined according to the electricity price Ei of the current preset sub-period, the state of charge difference between the preset battery state of charge upper limit SOC_up and the first battery state of charge SOC, and the installed capacity capacity of the battery energy storage system, i.e., benef it = benef it - (SOC_up - SOC) * capacity * Ei;

[0164] When the planned guidance power X[i] is the charging power and X[i] > 0, the energy storage benefit is the current energy storage benefit minus the preset benefit penalty value, i.e., benefit = benefit - penalty.

[0165] Reference Figure 5 In another embodiment of the method for determining the optimal planned guidance power provided by the present invention, the step of obtaining the energy storage revenue corresponding to the planned guidance power for each preset sub-time period further includes:

[0166] Step S204: Obtain the total temporary charging amount and the total temporary discharging amount corresponding to the end time of each preset sub-time period, and determine the equivalent number of full charging times based on the total temporary charging amount and the installed capacity of the battery energy storage system, and determine the equivalent number of full discharging times based on the total temporary discharging amount and the installed capacity of the battery energy storage system.

[0167] Step S205: If the equivalent number of full charge cycles is greater than the preset charging cycle limit or the equivalent number of full discharge cycles is greater than the preset discharging cycle limit, then the energy storage revenue is the current energy storage revenue minus the preset revenue penalty value.

[0168] In this embodiment, for safety reasons, the number of charge and discharge cycles is limited within the optimization time period. The temporary charging total (Charge_Sum) and temporary discharging total (DisCharge_Sum) corresponding to the end time of each preset sub-time period are obtained. If the planned guidance power X[i] > 0, then Charge_Sum = Charge_Sum + X[i] * t; if the planned guidance power X[i] < 0, then DisCharge_Sum = DisCharge_Sum + X[i] * t.

[0169] The equivalent number of full charge cycles is determined based on the temporary charging total (Charge_Sum) and the installed capacity (capacity) of the battery energy storage system: Charge_Sum / capacity. The equivalent number of full discharge cycles is determined based on the temporary discharging total (DisCharge_Sum) and the installed capacity (capacity) of the battery energy storage system: DisCharge_Sum / capacity. If the equivalent number of full charge cycles exceeds the preset charging cycle limit (limitCount) or the equivalent number of full discharge cycles exceeds the preset discharging cycle limit (limitCount), then the energy storage benefit is the current energy storage benefit minus the preset benefit penalty value (penalty), i.e., benefit = benefit - penalty.

[0170] Reference Figure 6 In another embodiment of the method for determining the optimal planned guidance power provided by the present invention, after the step of obtaining the energy storage revenue corresponding to the planned guidance power for each preset sub-time period, the method further includes:

[0171] Step S50: Determine the surplus power of the battery energy storage system at the start of the optimization period, the total discharge and total charge at the end of the optimization period, and determine the effective total discharge of the battery energy storage system as the difference between the total discharge and the surplus power. Based on the energy storage revenue, the total discharge and the effective total discharge, determine the effective total revenue of the battery energy storage system at the end of the optimization period.

[0172] Step S60: Determine the average effective revenue per kilowatt-hour based on the total effective revenue and the total charging amount. If the average effective revenue is less than the preset peak-valley price difference arbitrage lower limit, then determine the energy storage revenue of the battery energy storage system during the optimization period as the current energy storage revenue minus the preset revenue penalty value.

[0173] After obtaining the energy storage benefit corresponding to the planned guidance power X[i] for each preset sub-time period, the cost of peak shaving and valley filling charging and discharging also needs to be considered. The profit cannot be too low, and the lower limit of the profit cannot be too small; it needs to cover costs and equipment losses, etc. In this embodiment, a swarm intelligence algorithm is used to solve for the optimal planned guidance power. The basic parameters of the swarm intelligence optimization algorithm are population size and number of optimizations. After a single optimization of the 96 sub-time periods of the optimization period, the total discharge and total charging amount corresponding to the best planned guidance power X[i] in the population size of each sub-time period are counted, that is, the total charging amount sum_charge_capacity and the total discharging amount sum_discharge_capacity are calculated. Among them, the total charging amount is the value when i=96 in the temporary total charging amount Charge_Sum=Charge_Sum+X[i]*t, and the total discharging amount is the value when i=96 in the temporary total discharging amount DisCharge_Sum=DisCharge_Sum+X[i]*t.

[0174] The goal of a battery energy storage system is to fully discharge the previous day's electricity and the current day's electricity as well, maximizing energy storage benefits by discharging all the electricity each day. If the battery energy storage system still has electricity remaining after midnight (24:00), it indicates that the system still has unused profit potential. This unused electricity must be subtracted during the optimization process the following day, which means subtracting the remaining profit from the previous day. Therefore, the surplus electricity at the start of the optimization period is the unused electricity remaining from the previous day, i.e., surplus electricity = SOC0 * capacity, where SOC0 is the SOC at midnight of the current day and also the SOC at midnight of the previous day. Thus, the effective total discharge capacity of the battery energy storage system is determined as the difference between the total discharge capacity and the surplus electricity, i.e., effective total discharge capacity = sum_discharge_capacity - SOC0 * capacity.

[0175] Then, based on the energy storage revenue, total discharge, and effective total discharge, the effective total revenue of the battery energy storage system at the end of the optimization period is determined as averageProfit. The effective total revenue is also an estimated value after deducting the revenue from the previous day from today's discharge, i.e., averageProfit = benefit * (sum_discharge_capacity - SOC0 * capacity) / sum_discharge_capacity.

[0176] Finally, the average effective profit per kilowatt-hour (kWh) is determined based on the total effective profit (averageProfit) and the total charging capacity (sum_discharge_capacity), i.e., everyProfit = averageProfit / sum_charge_capacity. If the average effective profit (everyProfit) is less than the preset peak-valley price arbitrage lower limit (costLimit), then the energy storage profit for the battery energy storage system during the optimization period is determined to be the current energy storage profit minus the preset profit penalty (penalty), i.e., the updated energy storage profit (benefit) = beefit - penalty.

[0177] In another embodiment of the method for determining the optimal planned guidance power provided by the present invention, after the step of determining the planned guidance power corresponding to each preset sub-time period for the maximum energy storage revenue of the battery energy storage system during the optimization period as the optimal planned guidance power for each preset sub-time period, the method further includes:

[0178] If the last characteristic period of the electricity price time curve is a valley period, then the charging power boundary of each preset sub-period of the valley period is determined according to the overload boundary of the transformer of the battery energy storage system, the predicted load of each preset sub-period of the valley period, and the maximum charging limit of the battery energy storage system.

[0179] The optimal planned guidance power for each preset sub-time period of the valley period is determined as the charging power boundary for each preset sub-time period of the valley period, until the end of the valley period or until the battery state of charge during the valley period is equal to the preset upper limit of the battery state of charge of the battery energy storage system.

[0180] In addition to obtaining the optimal planned guidance power through optimization during the optimization period, when the last characteristic period of the electricity price time curve is a valley period, the battery energy storage system can also be charged according to the charging power boundary of each preset sub-period of the valley period as the optimal planned guidance power, until the end of the valley period or until the battery state of charge during the valley period equals the preset upper limit of the battery state of charge of the battery energy storage system, thus obtaining the maximum energy storage benefit of the last characteristic period of the electricity price time curve. Specifically, the charging power boundary of each preset sub-period of the valley period is determined based on the overload boundary of the battery energy storage system transformer, the predicted load Load i of each preset sub-period of the valley period, and the maximum charging limit of the battery energy storage system. That is, the charging power boundary charge_up_i of each preset sub-period is determined as the smaller value between the difference between the overload boundary and the predicted load Load i and the maximum charging limit of the battery energy storage system, where charge_up_i = MIN(overload boundary - Load i, maximum charging limit).

[0181] Furthermore, embodiments of the present invention also provide an apparatus for determining optimal planning guidance power, 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 optimal planning guidance power as described above.

[0182] 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 planning guidance power as described above.

[0183] 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.

[0184] 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.

[0185] 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.

[0186] 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 planning guidance power, characterized in that, The method for determining the optimal planned guidance power includes the following steps: Determine the optimal time period for the next day based on the electricity price time curve; The planned guidance power is obtained by adjusting the power of each preset sub-time period in the optimization time period, and the energy storage revenue corresponding to the planned guidance power of each preset sub-time period is obtained. The planned guidance power corresponding to the maximum energy storage revenue of the battery energy storage system during the optimization period is determined as the optimal planned guidance power for each preset sub-time period. The steps for obtaining the energy storage revenue corresponding to the planned guided power for each preset sub-time period include: Determine the first state of charge of the battery energy storage system at the start time of each preset sub-time period, and determine the first comparison result between the first state of charge and the preset upper and lower limits of the battery state of charge. Determine the second battery state of charge of the battery energy storage system at the end of the current preset sub-time period, and determine the second comparison result between the second battery state of charge and the preset upper and lower limits of the battery state of charge; The energy storage revenue corresponding to the planned guidance power in the preset sub-time period is determined based on the first comparison result and the second comparison result; wherein, the energy storage revenue is negative when the battery energy storage system is charging, and positive when the battery energy storage system is discharging.

2. The method for determining the optimal planning guidance power as described in claim 1, characterized in that, The step of determining the optimal time period for the next day based on the electricity price time curve includes: The electricity price time curve is marked with time period characteristics to determine the characteristic time period of the electricity price on the second day. The characteristic time period includes peak period and valley period. The start time of the optimization time period is 0:00 on the second day. If the last characteristic period of the electricity price time curve is a peak period, then the end time of the optimization period is 24:00; If the last characteristic period of the electricity price time curve is a valley period, then the end time of the optimization period is the start time of the valley period.

3. The method for determining the optimal planning guidance power as described in claim 1, characterized in that, Before the step of obtaining the energy storage revenue corresponding to the planned guidance power for each preset sub-time period, the method further includes: The charging power boundary and discharging power boundary of the battery energy storage system in each preset sub-time period are determined based on the overload boundary and reverse current boundary of the transformer of the battery energy storage system and the predicted load of each preset sub-time period. If the planned guidance power is less than the discharge power boundary, then the discharge power boundary shall be used as the planned guidance power; If the planned guidance power is greater than the charging power boundary, then the charging power boundary is taken as the planned guidance power; wherein, the discharging power is a negative value and the charging power is a positive value.

4. The method for determining the optimal planning guidance power as described in claim 3, characterized in that, The step of determining the charging power boundary and discharging power boundary of the battery energy storage system for each preset sub-time period based on the overload boundary and reverse current boundary of the battery energy storage system transformer and the predicted load of each preset sub-time period includes: The predicted load for each preset sub-time period is determined based on the preset predicted load curve; The charging power boundary for each preset sub-time period is determined to be the smaller value between the overload boundary and the difference between the predicted load and the maximum charging limit of the battery energy storage system. The discharge power boundary for each preset sub-time period is determined to be the larger value between the difference between the predicted load and the reverse current boundary and the maximum discharge limit of the battery energy storage system.

5. The method for determining the optimal planning guidance power as described in claim 1, characterized in that, The step of determining the energy storage revenue corresponding to the planned guidance power for the preset sub-time period based on the first comparison result and the second comparison result includes: If the first comparison result indicates that the first battery state of charge is between the preset upper and lower limits of the battery state of charge, then When the planned guidance power is the charging power, if the second comparison result is that the second battery state of charge is less than the preset upper limit of battery state of charge, then the energy storage revenue of the current preset sub-time period is determined according to the electricity price of the current preset sub-time period, the planned guidance power, and the duration of the current preset sub-time period; if the second comparison result is that the second battery state of charge is not less than the preset upper limit of battery state of charge, then the energy storage revenue of the current preset sub-time period is determined according to the electricity price of the current preset sub-time period, the state of charge difference between the preset upper limit of battery state of charge and the first battery state of charge, and the installed capacity of the battery energy storage system. When the planned guidance power is the discharge power, if the second comparison result is that the state of charge of the second battery is greater than the preset battery state of charge limit, then the energy storage revenue for the current preset sub-time period is determined based on the electricity price of the current preset sub-time period, the planned guidance power, and the duration of the current preset sub-time period; if the second comparison result is that the state of charge of the second battery is not greater than the preset battery state of charge limit, then the energy storage revenue for the current preset sub-time period is determined based on the state of charge difference between the state of charge of the first battery and the preset battery state of charge limit, the installed capacity of the battery energy storage system, and the electricity price of the current preset sub-time period.

6. The method for determining the optimal planning guidance power as described in claim 1, characterized in that, The step of determining the energy storage revenue corresponding to the planned guidance power for the preset sub-time period based on the first comparison result and the second comparison result further includes: If the first comparison result indicates that the first battery state of charge is greater than the preset upper limit of battery state of charge, then When the planned guidance power is the charging power, the energy storage revenue is the current energy storage revenue minus the preset revenue penalty value; When the planned guidance power is the discharge power, if the second comparison result is that the state of charge of the second battery is greater than the preset battery state of charge limit, then the energy storage revenue for the current preset sub-time period is determined based on the electricity price of the current preset sub-time period, the planned guidance power, and the duration of the current preset sub-time period; if the second comparison result is that the state of charge of the second battery is not greater than the preset battery state of charge limit, then the energy storage revenue for the current preset sub-time period is determined based on the state of charge difference between the state of charge of the first battery and the preset battery state of charge limit, the installed capacity of the battery energy storage system, and the electricity price of the current preset sub-time period.

7. The method for determining the optimal planning guidance power as described in claim 1, characterized in that, The step of determining the energy storage revenue corresponding to the planned guidance power for the preset sub-time period based on the first comparison result and the second comparison result further includes: If the first comparison result indicates that the state of charge of the first battery is less than the preset lower limit of the battery state of charge, then When the planned guidance power is the charging power, if the second comparison result is that the second battery state of charge is less than the preset upper limit of battery state of charge, then the energy storage revenue of the current preset sub-time period is determined according to the electricity price of the current preset sub-time period, the planned guidance power, and the duration of the current preset sub-time period; if the second comparison result is that the second battery state of charge is not less than the preset upper limit of battery state of charge, then the energy storage revenue of the current preset sub-time period is determined according to the electricity price of the current preset sub-time period, the state of charge difference between the preset upper limit of battery state of charge and the first battery state of charge, and the installed capacity of the battery energy storage system. When the planned guidance power is the discharge power, the energy storage revenue is the current energy storage revenue minus a preset revenue penalty value.

8. The method for determining the optimal planning guidance power as described in claim 1, characterized in that, The step of obtaining the energy storage revenue corresponding to the planned guidance power for each preset sub-time period further includes: Obtain the total amount of temporary charging and the total amount of temporary discharging corresponding to the end time of each preset sub-time period, and determine the equivalent number of full charging times based on the total amount of temporary charging and the installed capacity of the battery energy storage system, and determine the equivalent number of full discharging times based on the total amount of temporary discharging and the installed capacity of the battery energy storage system. If the equivalent number of full charge cycles exceeds the preset charging cycle limit or the equivalent number of full discharge cycles exceeds the preset discharging cycle limit, then the energy storage revenue is the current energy storage revenue minus the preset revenue penalty value.

9. The method for determining the optimal planning guidance power as described in claim 1, characterized in that, After the step of obtaining the energy storage revenue corresponding to the planned guidance power for each preset sub-time period, the method further includes: The surplus power of the battery energy storage system at the start of the optimization period, the total discharge and total charge at the end of the optimization period are determined, and the effective total discharge of the battery energy storage system is determined as the difference between the total discharge and the surplus power. Based on the energy storage revenue, the total discharge and the effective total discharge, the effective total revenue of the battery energy storage system at the end of the optimization period is determined. The average effective revenue per kilowatt-hour is determined based on the total effective revenue and the total charging amount. If the average effective revenue is less than the preset peak-valley price difference arbitrage lower limit, the energy storage revenue of the battery energy storage system during the optimization period is determined to be the current energy storage revenue minus the preset revenue penalty value.

10. The method for determining the optimal planning guidance power as described in claim 1, characterized in that, After the step of determining the planned guidance power corresponding to the maximum energy storage revenue of the battery energy storage system during the optimization period as the optimal planned guidance power for each preset sub-time period, the method further includes: If the last characteristic period of the electricity price time curve is a valley period, then the charging power boundary of each preset sub-period of the valley period is determined according to the overload boundary of the transformer of the battery energy storage system, the predicted load of each preset sub-period of the valley period, and the maximum charging limit of the battery energy storage system. The optimal planned guidance power for each preset sub-time period of the valley period is determined as the charging power boundary for each preset sub-time period of the valley period, until the end of the valley period or until the battery state of charge during the valley period is equal to the preset upper limit of the battery state of charge of the battery energy storage system.

11. A device for determining optimal planning guidance power, characterized in that, The device for determining the optimal planning guidance power 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 planning guidance power as described in any one of claims 1 to 10.

12. 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 planning guidance power as described in any one of claims 1 to 10.

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