CN115759630A

CN115759630A - Method, apparatus, and medium for determining optimal planning guide power

Info

Publication number: CN115759630A
Application number: CN202211441891.5A
Authority: CN
Inventors: 高强; 高林; 崔小伟; 闫宇; 范玉林
Original assignee: Sungrow Renewables Development Co Ltd
Current assignee: Sungrow Renewables Development Co Ltd
Priority date: 2022-11-17
Filing date: 2022-11-17
Publication date: 2023-03-07

Abstract

The invention discloses a method, equipment and a medium for determining optimal planning guidance power, which belong to the technical field of battery energy storage. And determining the plan guidance power corresponding to the maximum energy storage benefit as the optimal plan guidance power corresponding to each preset sub-time period by continuously adjusting the power of each preset sub-time period in the optimization time period and determining the energy storage benefit corresponding to the plan guidance power of each preset sub-time period. And determining to obtain the optimal planned guide power of each time period corresponding to the maximized user energy storage income through optimization, thereby accurately controlling the charging and discharging power of the battery energy storage system at each moment in a day.

Description

Method, apparatus, and medium for determining optimal planning guide power

Technical Field

The present invention relates to the field of battery energy storage technologies, and in particular, to a method for determining optimal plan guidance power, an apparatus for determining optimal plan guidance power, and a computer-readable storage medium.

Background

Currently, the BESS (Battery Energy Storage System) can realize the peak clipping and valley filling functions for the load by discharging at the peak of the load and charging at the valley of the load. For a power grid, the capacity of equipment can be delayed from upgrading by utilizing peak clipping and valley filling of a battery energy storage system, the utilization rate of the equipment is improved, and the updating cost of the equipment is saved; for users, the peak clipping and valley filling of the battery energy storage system can obtain economic benefits by using peak-valley electricity price difference. However, when peak clipping and valley filling are realized by discharging at the peak load and charging at the valley load, only the relation between the load size and the electricity price at the current time interval is roughly considered, the influence of the current charge-discharge action on the energy storage income of a user and the energy storage safety of the battery energy storage system at the future moment is not considered, the discharging power of the battery energy storage system at the peak load and the charging power of the battery energy storage system at the valley load can not be accurately controlled, and the user can obtain the maximum energy storage income.

Disclosure of Invention

The invention mainly aims to provide a method for determining optimal plan guide power, a device for determining optimal plan guide power and a computer readable storage medium, and aims to solve the technical problem that the charging and discharging power of a battery energy storage system at each moment in a day is difficult to accurately control in the prior art.

In order to achieve the above object, the present invention provides a method for determining optimal plan guidance power, including the steps of:

determining the optimizing time period of the next day according to the electricity price time curve;

adjusting the power of each preset sub-time period in the optimizing time period to obtain a planned guide power, and obtaining an energy storage benefit corresponding to the planned guide power in each preset sub-time period;

and determining the plan guidance power of the battery energy storage system corresponding to each preset sub-time period by the maximum energy storage profit of the optimizing time period as the optimal plan guidance power corresponding to each preset sub-time period.

Optionally, the step of determining the optimizing time period of the next day according to the power rate time curve includes:

performing time interval characteristic marking on the electricity price time curve, and determining a characteristic time interval of the electricity price on the second day, wherein the characteristic time interval comprises a peak time interval and a valley time interval, and the starting time of the optimizing time interval is 0 point of the second day;

if the last characteristic time interval of the electricity price time curve is a peak time interval, the end time of the optimizing time interval is 24 points;

and if the last characteristic time interval of the electricity price time curve is a flat valley time interval, the ending time of the optimizing time interval is the starting time of the flat valley time interval.

Optionally, before the step of obtaining the energy storage benefit corresponding to the planned guidance power for each preset sub-time period, the method further includes:

determining a charging power boundary and a discharging power boundary of the battery energy storage system in each preset sub-time period according to an overload boundary and a reverse flow boundary of a transformer of the battery energy storage system and the predicted load of each preset sub-time period;

if the planned guide power is smaller than the discharge power boundary, taking the discharge power boundary as the planned guide power;

if the planned guide power is larger than the charging power boundary, taking the charging power boundary as the planned guide power; the discharging power is a negative value, and the charging power is a positive value.

Optionally, the step of determining the charging power boundary and the discharging power boundary of each preset sub-time period of the battery energy storage system according to the overload boundary and the reverse flow boundary of the transformer of the battery energy storage system and the predicted load of each preset sub-time period includes:

determining the predicted load of each preset sub-time period according to a preset predicted load curve;

determining the charging power boundary of each preset sub-time period as the smaller value between the difference between the overload boundary and the predicted load and the maximum energy storage charging limit value of the battery energy storage system;

and determining the discharging power boundary of each preset sub-time period as a larger value between the difference between the predicted load and the reverse flow boundary and the energy storage maximum discharging limit value of the battery energy storage system.

Optionally, the step of obtaining an energy storage benefit corresponding to the planned guide power for each preset sub-time period includes:

determining a first battery charge state of the battery energy storage system at the starting moment of each preset sub-time period, and determining a first comparison result of the first battery charge state and the upper and lower limits of the preset battery charge state;

determining a second battery charge state of the battery energy storage system at the end moment of the current preset sub-time period, and determining a second comparison result of the second battery charge state and the upper and lower limits of the preset battery charge state;

determining energy storage benefits corresponding to the plan guidance power in a preset sub-time period according to the first comparison result and the second comparison result; and when the battery energy storage system is charged, the energy storage profit is negative, and when the battery energy storage system is discharged, the energy storage profit is positive.

Optionally, the step of determining an energy storage benefit corresponding to the planned guidance power in a preset sub-time period according to the first comparison result and the second comparison result includes:

if the first comparison result shows that the first battery SOC is between the upper limit and the lower limit of the preset battery SOC, the first comparison result shows that the first battery SOC is between the upper limit and the lower limit of the preset battery SOC

When the plan guidance power is charging power, if the second comparison result is that the second battery state of charge is smaller than the upper limit of the preset battery state of charge, determining the energy storage benefit of the current preset sub-time period according to the electricity price of the current preset sub-time period, the plan 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 smaller than the preset battery state of charge upper limit, determining the energy storage benefit of the current preset sub-time period according to the electricity price of the current preset sub-time period, the state of charge difference between the preset battery state of charge upper limit and the first battery state of charge and the installed capacity of the battery energy storage system;

when the plan guidance power is the discharge power, if the second comparison result is that the second battery state of charge is larger than the lower limit of the preset battery state of charge, determining the energy storage benefit of the current preset sub-time period according to the electricity price of the current preset sub-time period, the plan guidance power and the duration of the current preset sub-time period; and if the second comparison result shows that the second battery SOC is not greater than the lower limit of the preset battery SOC, determining the energy storage profit of the current preset sub-time period according to the SOC difference between the first battery SOC and the lower limit of the preset battery SOC, the installed capacity of the battery energy storage system and the electricity price of the current preset sub-time period.

Optionally, the step of determining an energy storage benefit corresponding to the planned guidance power in a preset sub-time period according to the first comparison result and the second comparison result further includes:

if the first comparison result is that the first battery SOC is greater than the upper limit of the preset battery SOC, the method comprises the following steps

When the plan guidance power is charging power, the energy storage benefit is obtained by subtracting a preset benefit penalty value from the current energy storage benefit;

when the plan guidance power is the discharge power, if the second comparison result is that the second battery state of charge is larger than the lower limit of the preset battery state of charge, determining the energy storage benefit of the current preset sub-time period according to the electricity price of the current preset sub-time period, the plan guidance power and the duration of the current preset sub-time period; and if the second comparison result shows that the second battery SOC is not greater than the lower limit of the preset battery SOC, determining the energy storage benefit of the current preset sub-time period according to the SOC difference between the first battery SOC and the lower limit of the preset battery SOC, the installed capacity of the battery energy storage system and the electricity price of the current preset sub-time period.

if the first comparison result shows that the first battery SOC is smaller than the lower limit of the preset battery SOC, the first comparison result shows that the first battery SOC is smaller than the lower limit of the preset battery SOC

and when the plan guidance power is the discharge power, the energy storage benefit is obtained by subtracting a preset benefit penalty value from the current energy storage benefit.

Optionally, the step of obtaining an energy storage benefit corresponding to the planned guide power in each preset sub-time period further includes:

acquiring a temporary charging total amount and a temporary discharging total amount corresponding to the ending moment of each preset sub-time period, determining equivalent full charging times according to the temporary charging total amount and the installed capacity of the battery energy storage system, and determining equivalent discharging times according to the temporary discharging total amount and the installed capacity of the battery energy storage system;

and if the equivalent full charge times are larger than a preset charge time limit value or the equivalent discharge times are larger than a preset discharge time limit value, subtracting a preset profit penalty value from the current energy storage profit by the energy storage profit.

Optionally, after the step of obtaining the energy storage benefit corresponding to the planned guidance power for each preset sub-time period, the method further includes:

determining surplus electric quantity of the battery energy storage system at the starting moment of the optimizing time period, total discharge quantity and total charge quantity at the ending moment of the optimizing time period, determining effective total discharge quantity of the battery energy storage system as the difference between the total discharge quantity and the surplus electric quantity, and determining effective total profit of the battery energy storage system at the ending moment of the optimizing time period based on the energy storage profit, the total discharge quantity and the effective total discharge quantity;

and determining the average effective income of each degree of electricity according to the effective total income and the total charging amount, and if the average effective income is smaller than a preset peak-valley price difference arbitrage lower limit value, determining that the energy storage income of the optimization time period of the battery energy storage system is the current energy storage income minus a preset income penalty value.

Optionally, after the step of determining that the plan guidance power corresponding to each preset sub-time period is the optimal plan guidance power corresponding to each preset sub-time period for the maximum energy storage benefit of the optimization time period of the battery energy storage system, the method further includes:

if the last characteristic time interval of the electricity price time curve is a flat valley time interval, determining a charging power boundary of each preset sub-time interval of the flat valley time interval according to an overload boundary of a transformer of a battery energy storage system, a predicted load of each preset sub-time interval of the flat valley time interval and an energy storage maximum charging limit value of the battery energy storage system;

and determining the optimal plan guidance power of each preset sub-time period in the flat valley period as a charging power boundary of each preset sub-time period in the flat valley period until the end time of the flat valley period or until the battery charge state of the flat valley period is equal to the upper limit of the preset battery charge state of the battery energy storage system.

Further, to achieve the above object, the present invention also provides an optimal plan guidance power determining apparatus including: a memory, a processor and a computer program stored on the memory and executable on the processor, the computer program being configured to implement the steps of the method of determining optimal plan directed power as described above.

Further, to achieve the above object, the present invention also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the method for determining an optimal plan guidance power as described above.

The optimal plan guide power determining method, the optimal plan guide power determining device and the computer readable storage medium provided by the embodiment of the invention determine the optimization time period of the next day according to the electricity price time curve; adjusting the power of each preset sub-time period in the optimizing time period to obtain a planned guide power, and obtaining an energy storage benefit corresponding to the planned guide power in each preset sub-time period; and determining the plan guidance power of the battery energy storage system corresponding to each preset sub-time period according to the maximum energy storage profit of the optimizing time period as the optimal plan guidance power corresponding to each preset sub-time period.

Firstly, determining an optimization time period of the battery energy storage system in the next day through an electricity price time curve, then adjusting the power of each preset sub-time period in the optimization time period to obtain a planned guide power, obtaining energy storage income corresponding to the planned guide power of each preset sub-time period, and finally determining the planned guide power of each preset sub-time period corresponding to the maximum energy storage income of the battery energy storage system in the optimization time period as the optimal planned guide power corresponding to each preset sub-time period.

And determining the plan guidance power corresponding to the maximum energy storage benefit as the optimal plan guidance power corresponding to each preset sub-time period by continuously adjusting the power of each preset sub-time period in the optimization time period and determining the energy storage benefit corresponding to the plan guidance power of each preset sub-time period. Therefore, on the basis of realizing peak clipping and valley filling, the optimal planned guide power of each time period corresponding to the maximized user energy storage income is determined and obtained through optimization, and therefore the charging and discharging power of the battery energy storage system at each moment in a day is accurately controlled.

Drawings

FIG. 1 is a schematic diagram of a hardware execution environment execution device according to an embodiment of the present invention;

FIG. 2 is a flowchart illustrating an embodiment of a method for determining optimal planning guidance power according to the present invention;

FIG. 3 is a flowchart illustrating step S10 of an embodiment of a method for determining optimal planning guidance power according to the present invention;

FIG. 4 is a first flowchart of step S20 in an embodiment of the method for determining optimal planning guidance power according to the present invention;

FIG. 5 is a second flowchart of step S20 in an embodiment of the method for determining optimal planning guidance power of the present invention;

FIG. 6 is a flowchart illustrating a method for determining optimal planning guidance power according to another embodiment of the present invention.

The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.

Detailed Description

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

Referring to fig. 1, fig. 1 is a schematic structural diagram of an operating device of a hardware operating environment according to an embodiment of the present invention.

As shown in fig. 1, the operation device may include: the processor 1001 is, for example, a Central Processing Unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a display screen (Di sp ay), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., a WI re l ess-F I de l ity, WI-F I) interface). The Memory 1005 may be a Random Access Memory (RAM) Memory, or a Non-Vo l at i e Memory (NVM), such as a disk Memory. The memory 1005 may alternatively be a storage device separate from the processor 1001.

Those skilled in the art will appreciate that the configuration shown in FIG. 1 does not constitute a limitation of the operating device and may include more or fewer components than shown, or some components may be combined, or a different arrangement of components.

As shown in fig. 1, a memory 1005, which is a kind of storage medium, may include therein an operating system, a data storage module, a network communication module, a user interface module, and a computer program.

In the operating device shown in fig. 1, the network interface 1004 is mainly used for data communication with other devices; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 in the execution device of the present invention may be provided in an execution device that calls the computer program stored in the memory 1005 by the processor 1001 and performs the following operations:

and determining the plan guidance power of the battery energy storage system corresponding to each preset sub-time period according to the maximum energy storage profit of the optimizing time period as the optimal plan guidance power corresponding to each preset sub-time period.

Further, the processor 1001 may call the computer program stored in the memory 1005, and also perform the following operations:

the step of determining the optimizing time period of the next day according to the power rate time curve comprises the following steps:

before the step of obtaining the energy storage benefit corresponding to the planned guide power in each preset sub-time period, the method further includes:

if the planned guide power is larger than the charging power boundary, taking the charging power boundary as the planned guide power; the discharge power is a negative value, and the charge power is a positive value.

the step of determining the charging power boundary and the discharging power boundary of each preset sub-time period of the battery energy storage system according to the overload boundary and the reverse flow boundary of the transformer of the battery energy storage system and the predicted load of each preset sub-time period comprises the following steps:

the step of obtaining the energy storage benefit corresponding to the planned guide power in each preset sub-time period comprises the following steps:

the step of determining the energy storage benefit corresponding to the planned guidance power in the preset sub-time period according to the first comparison result and the second comparison result comprises the following steps:

the step of determining the energy storage benefit corresponding to the planned guidance power in the preset sub-time period according to the first comparison result and the second comparison result further includes:

if the first comparison result shows that the first battery SOC is greater than the upper limit of the preset battery SOC, the first comparison result shows that the first battery SOC is greater than the upper limit of the preset battery SOC

and when the planning guidance power is the discharge power, the energy storage benefit is obtained by subtracting a preset benefit punishment value from the current energy storage benefit.

the step of obtaining the energy storage benefit corresponding to the planned guidance power in each preset sub-time period further includes:

after the step of obtaining the energy storage benefit corresponding to the planned guide power in each preset sub-time period, the method further includes:

determining surplus electric quantity of the battery energy storage system at the starting time of the optimization time period, total discharge quantity and total charge quantity at the ending time of the optimization time period, determining effective total discharge quantity of the battery energy storage system as the difference between the total discharge quantity and the surplus electric quantity, and determining effective total income of the battery energy storage system at the ending time of the optimization time period based on the energy storage income, the total discharge quantity and the effective total discharge quantity;

Referring to fig. 2, fig. 2 is a flowchart illustrating an embodiment of a method for determining optimal planning guidance power according to the present invention. The embodiment of the invention provides a method for determining optimal plan guide power, which comprises the following steps:

step S10: determining the optimizing time period of the next day according to the electricity price time curve;

the electricity price time curve is a functional relation of electricity prices corresponding to different times, the battery energy storage system discharges when the electricity price time curve is a peak, and the battery energy storage system charges when the electricity price time curve is a flat valley, so that peak clipping and valley filling are realized; the high electricity price corresponding to the peak and the low electricity price corresponding to the flat valley have an electricity price standard, the high electricity price is higher than the electricity price standard, the low electricity price is lower than the electricity price standard, and the electricity price standard of each region and province is different, so that the issued high electricity price and low electricity price are different. In this embodiment, the source of the electricity price time curve is not limited, and the electricity price time curve may be an electricity price time curve issued by different regions and provinces, or may be a local electricity price at different time at the location of the battery energy storage system based on prediction. After the electricity price time curve of the next day is determined, the optimizing time period of the next day is determined according to the electricity price time curve, the power of each preset sub-time period is adjusted in the optimizing time period, and the optimizing is conducted to obtain the optimal plan guiding power of the maximum energy storage income corresponding to each preset sub-time period.

Optionally, referring to fig. 3, the step of determining the optimization time period of the next day according to the power rate time curve includes:

step S101, carrying out time interval characteristic marking on the electricity price time curve, and determining a characteristic time interval of electricity price on the second day, wherein the characteristic time interval comprises a peak time interval and a valley time interval, and the starting time of the optimizing time interval is 0 point of the second day;

step S102, if the last characteristic time interval of the electricity price time curve is a peak time interval, the end time of the optimizing time interval is 24 points;

step S103, if the last characteristic time interval of the electricity price time curve is a flat valley time interval, the ending time of the optimizing time interval is the starting time of the flat valley time interval.

Firstly, determining the starting time of an optimizing time period as 0 point of the next day; then, carrying out time interval characteristic marking on the electricity price time curve, and determining the peak time interval of high electricity price and the flat time interval of low electricity price on the next day; and finally, when the last characteristic period of the electricity price time curve is determined to be a peak period, the ending time of the optimizing time period is determined to be 24 points, and when the last characteristic period of the electricity price time curve is determined to be a flat valley period, the ending time of the optimizing time period is determined to be the starting time of the last flat valley period. If the last characteristic time interval is the flat valley time interval, optimizing the last flat valley time interval is not needed, and the battery energy storage system is charged at a low price, so that the optimizing time interval of the next day is determined to be 0 point of the next day until the end time of the last peak time interval.

Step S20: and adjusting the power of each preset sub-time period in the optimizing time period to obtain a planned guide power, and obtaining the energy storage benefit corresponding to the planned guide power in each preset sub-time period.

Presetting a preset number of sub-time periods in the optimizing time period, continuously adjusting the power of each preset sub-time period in the optimizing time period to obtain the planned guide power after the optimizing time period of the next day is determined, and obtaining the energy storage benefit corresponding to the planned guide power of each preset sub-time period. In the present embodiment, the number of sub-periods and the duration of each sub-period are not limited, and preferably, 24 hours a day are divided into 96 sub-periods, each sub-period is 15 minutes, and one or more sub-periods are included in the peak period and the valley period.

Step S30: and determining the plan guidance power of the battery energy storage system corresponding to each preset sub-time period according to the maximum energy storage profit of the optimizing time period as the optimal plan guidance power corresponding to each preset sub-time period.

After the energy storage gain of each preset sub-time period is determined, the energy storage gains of all the preset sub-time periods are added, the plan guidance power of the battery energy storage system in each preset sub-time period corresponding to the maximum energy storage gain of the optimization time period is determined, and the plan guidance power corresponding to the maximum gain is used as the optimal plan guidance power corresponding to each preset sub-time period.

In the embodiment, the optimizing time period of the next day is determined according to the electricity price time curve; adjusting the power of each preset sub-time period in the optimizing time period to obtain a planned guide power, and obtaining an energy storage benefit corresponding to the planned guide power in each preset sub-time period; and determining the plan guidance power of the battery energy storage system corresponding to each preset sub-time period according to the maximum energy storage profit of the optimizing time period as the optimal plan guidance power corresponding to each preset sub-time period.

And continuously adjusting the power of each preset sub-time period in the optimizing time period and determining the energy storage income corresponding to the plan guidance power of each preset sub-time period, and determining the plan guidance power corresponding to the maximum energy storage income as the optimal plan guidance power corresponding to each preset sub-time period. Therefore, on the basis of realizing peak clipping and valley filling, the optimal planned guide power of each time period corresponding to the maximized user energy storage income is determined and obtained through optimization, and therefore the charging and discharging power of the battery energy storage system at each moment in a day is accurately controlled.

In another embodiment of the method for determining an optimal planning guidance power, before the step of obtaining the energy storage benefit corresponding to the planning guidance power in each preset sub-time period, the method further includes:

In the optimizing process, besides the maximum energy storage benefit of the user, the safety of the battery energy storage system needs to be considered and ensured. In this embodiment, the charging power boundary charge _ up _ i and the discharging power boundary d i s _ charge _ up _ i of the battery energy storage system in each preset sub-time period are determined according to the overload boundary and the reverse flow boundary of the battery energy storage system transformer and the predicted Load i (i represents the serial number of the preset sub-time period, and the same is true hereinafter) of each preset sub-time period.

If the planned guide power X [ i ] is smaller than the discharging power boundary d i s _ charge _ up _ i, taking the discharging power boundary d i s _ charge _ up _ i as the planned guide power X [ i ]; if the planned guide power X [ i ] is larger than the charging power boundary charge _ up _ i, taking the charging power boundary charge _ up _ i as the planned guide power X [ i ]; the discharging power is a negative value, the charging power is a positive value, and the positive value and the negative value of the charging and discharging power are both set artificially. Therefore, the planned guide power X [ i ] is determined to be in the range of the discharging power boundary d i s _ charging _ up _ i which is not less than X [ i ] but not more than charging power boundary charging _ up _ i, and the charging and discharging safety of the battery energy storage system is guaranteed.

When determining a charging power boundary charge _ up _ i and a discharging power boundary d i s _ charge _ up _ i of each preset sub-time period of the battery energy storage system, firstly, determining a predicted Load i of each preset sub-time period according to a preset predicted Load curve, wherein the Load is the required power of equipment at a user side, and the preset predicted Load curve is a functional relation of loads corresponding to different times, and is similar to an electricity price time curve.

Then, determining a charging power boundary, charge _ up _ I, of each preset sub-period as a smaller value between a difference between the overload boundary and the predicted Load I and an energy storage maximum charging limit value of the battery energy storage system, namely, charge _ up _ I = mn (overload boundary-Load I, energy storage maximum charging limit value), wherein the difference between the overload boundary and the predicted Load I is a remaining safe chargeable power of the battery energy storage system, the overload boundary is a maximum bearable Load of the transformer, and the overload boundary = a transformer capacity C power factor PF transformer derating coefficient-D I self-defined overload threshold value.

And finally, determining a discharging power boundary D I s _ charge _ up _ I of each preset sub-period as a difference between the predicted Load I and the countercurrent boundary and a larger value between the energy storage maximum discharging limit values of the battery energy storage system, namely D I s _ charge _ up _ I = -M I N (Load I-countercurrent boundary, -energy storage maximum discharging limit value), wherein the energy storage maximum discharging limit value is represented by a negative sign in front, so that the energy storage maximum discharging limit value is uniformly expressed with the discharging power being a negative value, the countercurrent boundary is a threshold value D set by self-definition, and the battery energy storage system can be considered to be in countercurrent when the power is less than D.

In addition, when the battery energy storage system has a fault or the electric quantity is low, the battery cannot be charged at the rated power, so that the maximum charging limit power exists in real time. Therefore, the minimum value is obtained in comparison with the maximum energy storage discharge limit, the charging capacity of the battery energy storage system corresponding to the charging power is guaranteed, and finally the charging and discharging safety of the battery energy storage system is guaranteed.

Referring to fig. 4, in another embodiment of the method for determining an optimal planned guidance power provided by the present invention, the step of obtaining an energy storage benefit corresponding to the planned guidance power for each preset sub-time period includes:

step S201, determining a first battery charge state of the battery energy storage system at the starting moment of each preset sub-time period, and determining a first comparison result between the first battery charge state and the upper and lower limits of the preset battery charge state;

step S202, determining a second battery charge state of the battery energy storage system at the end moment of the current preset sub-time period, and determining a second comparison result between the second battery charge state and the upper and lower limits of the preset battery charge state;

step S203, determining energy storage benefits corresponding to the plan guidance power in a preset sub-time period according to the first comparison result and the second comparison result; and when the battery energy storage system is charged, the energy storage income is negative, and when the battery energy storage system is discharged, the energy storage income is positive.

When calculating and obtaining the energy storage income corresponding to the planned guide power xi of each preset sub-time period, firstly determining a first battery charge state of the battery energy storage system at the starting moment of each preset sub-time period and a first comparison result between the first battery charge state and the upper limit and the lower limit of the preset battery charge state; then determining a second battery charge state of the battery energy storage system at the end moment of the current preset sub-time period and a second comparison result of the second battery charge state and the upper limit and the lower limit of the preset battery charge state; finally, determining the energy storage income corresponding to the planned guidance power xi of the preset sub-time period according to the first comparison result and the second comparison result, and accordingly determining the energy storage income under different battery charge states based on different comparison results; the energy storage profit is negative when the battery energy storage system is charged, and the energy storage profit is positive when the battery energy storage system is discharged, so that the energy storage profit and the discharge power are uniformly expressed as a negative value. The preset upper and lower limits of the battery charge state are safety boundaries (0%, 100%) of the battery charge state set manually, do not correspond to end points, and represent that the electric quantity of the battery energy storage system cannot be completely discharged and cannot be completely filled.

The first battery charge state of the starting time (0 point of the day) of the optimization time period of the battery energy storage system is the battery charge state of 24 points of the previous day (the day), the second battery charge state tmploc state of the ending time of the first preset sub-time period is obtained by calculation according to the time length t of the sub-time period, the battery charge state of the 0 point of the day and the planning guidance power X [ i ] of the first preset sub-time period, the second battery charge state of the ending time of the first preset sub-time period is the first battery charge state of the starting time of the second preset sub-time period, and therefore the first battery charge state SOC of the starting time of any subsequent preset sub-time period is obtained by analogy in the calculation mode. That is, tmpSOC = SOC + (X [ i ]. T/capac timing).

When the energy storage gain corresponding to the planned guide power xi Of the preset sub-time period is determined according to the first comparison result and the second comparison result, if the first battery State Of Charge is between the upper limit and the lower limit Of the preset battery State Of Charge, namely the lower limit SOC _ down Of the preset battery State Of Charge is less than or equal to SOC (State Of Charge, battery State Of Charge or current remaining battery capacity) is less than or equal to the upper limit SOC _ up Of the preset battery State Of Charge, then the energy storage gain corresponding to the planned guide power xi Of the preset sub-time period is determined according to the first comparison result and the second comparison result, and the energy storage gain corresponding to the planned guide power xi Of the preset sub-time period is determined according to the first comparison result and the second comparison result

When the planned guide power is charging power and X [ i ] > 0, if the second comparison result is that the second battery state of charge tmpLOC is smaller than the preset battery state of charge upper limit SOC _ up, determining the energy storage gain benef it of the current preset sub-time period according to the electricity price Ei of the current preset sub-time period, the planned guide power X [ i ] and the time t of the current preset sub-time period, namely benef it = benef i t-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, determining the energy storage benefit of the current preset sub-time period according to the electricity price Ei of the current preset sub-time 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 capact of the battery energy storage system, namely benef it = benef it- (SOC _ up-SOC) icaactei;

when the planned guide power is the discharge power and X [ i ] < 0, if the second comparison result is that the second battery state of charge tmpLOC is greater than the preset battery state of charge lower limit SOC _ down, determining the energy storage gain benef it of the current preset sub-time period according to the electricity price Ei of the current preset sub-time period, the planned guide power X [ i ] and the time length t of the current preset sub-time period, namely 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 lower limit SOC _ down, determining the energy storage benefit of the current preset sub-period according to the state of charge difference between the first battery state of charge SOC and the preset battery state of charge lower limit SOC _ down, the installed capacity capact of the battery energy storage system, and the electricity price Ei of the current preset sub-period, that is benef it = benef it + (SOC-SOC _ down) · capact E i.

When the energy storage income corresponding to the planned guidance power xi of the preset sub-time period is determined according to the first comparison result and the second comparison result, if the first battery SOC is larger than the preset battery SOC upper limit SOC _ up according to the first comparison result, judging that the preset sub-time period plan guidance power xi is the energy storage income corresponding to the planned guidance power xi of the preset sub-time period plan guidance power

When the plan guidance power X [ i ] is charging power and X [ i ] is greater than 0, the energy storage benefit is obtained by subtracting a preset benefit penalty value penta l ty from the current energy storage benefit, namely benefit = benef i t-penta l ty;

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 lower limit SOC _ down, determining the energy storage benefit of the current preset sub-time period according to the electricity price E i, the planned guidance power X [ i ] and the duration t of the current preset sub-time period, namely benef it = benef it- (E i) X [ i ]. T; and if the second comparison result shows that the second battery state of charge tmpSOC is not greater than the preset battery state of charge lower limit SOC _ down, determining the energy storage benefit of the current preset sub-period, namely benef it = benef it + (SOC-SOC _ down) · capacity Ei, according to the state of charge difference between the first battery state of charge SOC and the preset battery state of charge lower limit SOC _ down, the installed capacity of the battery energy storage system and the electricity price Ei of the current preset sub-period.

When the energy storage income corresponding to the planned guide power xi in the preset sub-time period is determined according to the first comparison result and the second comparison result, if the first battery SOC is smaller than the preset battery SOC lower limit SOC _ down according to the first comparison result, determining that the energy storage income corresponds to the planned guide power xi in the preset sub-time period

When the planned guide power X [ i ] is charging power, if the second comparison result is that the second battery state of charge tmpLOC is smaller than the preset battery state of charge upper limit SOC _ up, determining the energy storage gain benef it of the current preset sub-time period according to the electricity price Ei of the current preset sub-time period, the planned guide power X [ i ] and the time length t of the current preset sub-time period, namely benef it = benef i t-Ei X [ i ] t; if the second comparison result shows that the second battery state of charge tmpSOC is not less than the preset battery state of charge upper limit SOC _ up, determining the energy storage benefit of the current preset sub-time period according to the electricity price E i of the current preset sub-time 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 capact of the battery energy storage system, namely benef it = benef it- (SOC _ up-SOC) icaact E i;

when the plan guidance power X [ i ] is charging power and X [ i ] is greater than 0, the energy storage benefit is obtained by subtracting a preset benefit penalty value penta l ty from the current energy storage benefit, namely benefit = benef i t-penta l ty.

Referring to fig. 5, in another embodiment of the method for determining an optimal planning guidance power provided by the present invention, the step of obtaining an energy storage benefit corresponding to the planning guidance power for each preset sub-time period further includes:

step S204, acquiring a temporary charging total amount and a temporary discharging total amount corresponding to the ending time of each preset sub-time period, determining equivalent full charging times according to the temporary charging total amount and the installed capacity of the battery energy storage system, and determining equivalent discharging times according to the temporary discharging total amount and the installed capacity of the battery energy storage system;

in step S205, if the equivalent full charge time is greater than the preset charge time limit or the equivalent discharge time is greater than the preset discharge time limit, the energy storage benefit is obtained by subtracting a preset benefit penalty value from the current energy storage benefit.

In this embodiment, the number of times of charge and discharge is limited within the seek period for safety reasons. Acquiring a temporary charging total amount, namely, charge _ Sum and a temporary discharging total amount, namely, di sCharge _ Sum, corresponding to the end time of each preset sub-time period, and if the scheduled guidance power X [ i ] > 0, charging _ Sum = Charge _ Sum + X [ i ]. T; di sscharge _ Sum = D i sscharge _ Sum + X [ i ] > t if the planned guideline power X [ i ] < 0.

Determining the equivalent full Charge times according to the temporary total Charge _ Sum and the installed capacity capact i ty of the battery energy storage system: determining the equivalent electricity discharge times according to the total temporary discharge amount D i sCharge _ Sum and the installed capacity of the battery energy storage system capact, wherein the Charge _ Sum/capact is as follows: di sCharge _ Sum/capic item; if the equivalent full charge time is greater than the preset charge time limit value l imitCount or the equivalent discharge time is greater than the preset discharge time limit value l imitCount, the energy storage benefit is obtained by subtracting a preset benefit penalty value penta ty from the current energy storage benefit, namely benefit = benefit-penta lty.

Referring to fig. 6, in another embodiment of the method for determining an optimal planning guidance power provided by the present invention, after the step of obtaining the energy storage benefit corresponding to the planning guidance power for each preset sub-time period, the method further includes:

step S50, determining surplus electric quantity of the battery energy storage system at the starting time of the optimization time period, total discharge quantity and total charge quantity at the ending time of the optimization time period, determining effective total discharge quantity of the battery energy storage system as the difference between the total discharge quantity and the surplus electric quantity, and determining effective total income of the battery energy storage system at the ending time of the optimization time period based on the energy storage income, the total discharge quantity and the effective total discharge quantity;

and S60, determining the average effective income of each degree of electricity according to the effective total income and the total charge amount, and if the average effective income is smaller than a preset peak-valley price difference arbitrage lower limit value, determining that the energy storage income of the optimization time period of the battery energy storage system is obtained by subtracting a preset income penalty value from the current energy storage income.

After the energy storage gain benefit corresponding to each preset sub-time period plan guidance power xi is obtained, the cost of peak clipping, valley filling and charging and discharging needs to be considered. The profitability cannot be too low, the lower profitability limit cannot be too small, the coverage cost and the equipment loss are needed, and the like. In this embodiment, a group intelligent algorithm is used to solve the optimal plan guidance power, and basic parameters of the group intelligent optimization algorithm include the population scale and the optimization times. After the single optimization of 96 sub-time periods of the optimization time period is finished, counting the total discharge amount and the total charge amount corresponding to the optimal planning guidance power X [ i ] in the population scale in each sub-time period, namely calculating the total charge amount sum _ charge _ capacity and the total discharge amount sum _ d i scharge _ capacity. The total Charge amount is a value at which i =96 of the total temporary Charge amount Charge _ Sum = Charge _ Sum + X [ i ]. At, and the total discharge amount is a value at which i =96 of the total temporary discharge amount Di sscharge _ Sum = Di sscharge _ Sum + X [ i ]. At.

The battery energy storage system aims to discharge the electric quantity in the previous day, discharge the electric quantity in the same day and discharge the electric quantity in each day to obtain the maximum energy storage benefit. If the battery energy storage system has residual electricity after 24 points, the profitability of the battery energy storage system is proved not to be used, and after the battery energy storage system is left for the next day, the residual electricity which is not discharged in the previous day needs to be subtracted in the optimizing process of the next day, namely the residual profit of the previous day is subtracted. Therefore, the surplus power of the battery energy storage system at the beginning of the optimization searching time period is the power left by the battery energy storage system and not discharged, namely surplus power = SOC0 × capacity, where SOC0 is the SOC at 0 in the early morning of the day and is the SOC at 24 o' clock in the previous day. And determining the effective total discharge capacity of the battery energy storage system as the difference between the total discharge capacity and the surplus electric quantity, namely the effective total discharge capacity = sum _ di scharge _ capacity-SOC 0 capacity.

Then, an effective total benefit averageProf i t of the battery energy storage system at the end of the optimizing time period is determined based on the energy storage benefit, the total discharge capacity and the effective total discharge capacity, wherein the effective total benefit is also an estimated value of averageProf it = benef it (sum _ di scharge _ capacity-SOC 0 capac it)/sum _ di scharge _ capacity after the previous day of benefits are deducted from today discharge.

And finally, determining the average effective gain everyProf it of each degree of electricity according to the effective total gain averageProf it and the total charge amount sum _ di scharge _ capact, namely, everyProf it = averageProf it/sum _ charge _ capact, and if the average effective gain everyProf it is smaller than the preset peak-valley price difference arbitrage lower limit value costLimit, determining that the energy storage gain of the optimization time period of the battery energy storage system is the current energy storage gain minus the preset gain penalty value penta ty, namely updating the energy storage gain benef = benef it-penta ty.

In another embodiment of the method for determining an optimal planned guide power, after the step of determining that the planned guide power of each preset sub-time period corresponding to the maximum energy storage profit of the optimization time period of the battery energy storage system is the optimal planned guide power of each preset sub-time period, the method further includes:

Besides obtaining the optimal plan guidance power through optimization in the optimization time period, under the condition that the last characteristic time period of the electricity price time curve is the flat valley time period, the battery energy storage system can be charged according to the charging power boundary of each preset sub time period in the flat valley time period as the optimal plan guidance power until the ending time of the flat valley time period or until the battery charge state of the flat valley time period is equal to the preset battery charge state upper limit of the battery energy storage system, and the maximum energy storage profit of the last characteristic time period of the electricity price time curve is obtained. The charging power boundary of each preset sub-time period in the valley leveling period is determined according to the overload boundary of the transformer of the battery energy storage system, the predicted Load I of each preset sub-time period in the valley leveling period and the maximum energy storage charging limit value of the battery energy storage system, namely, the charging power boundary charge _ up _ I of each preset sub-time period is determined to be the smaller value between the difference between the overload boundary and the predicted Load I and the maximum energy storage charging limit value of the battery energy storage system, and charge _ up _ I = MIN (overload boundary-Load I, maximum energy storage charging limit value).

In addition, an embodiment of the present invention further provides an optimal plan guidance power determining device, where the optimal plan guidance power determining device includes: a memory, a processor and a computer program stored on the memory and executable on the processor, the computer program being configured to implement the steps of the method of determining optimal plan directed power as described above.

Furthermore, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of the method for determining an optimal planning guidance power as described above.

It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of another identical element in a process, method, article, or system that comprises the element.

The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.

Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) as described above and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.

The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.

Claims

1. A method for determining an optimal plan guide power, the method comprising:

2. The method for determining optimal planning guidance power according to claim 1, wherein the step of determining the optimization time period for the next day according to the power rate time curve comprises:

3. The method for determining optimal planning guidance power according to claim 1, wherein the step of obtaining the energy storage profit corresponding to the planning guidance power for each preset sub-period further comprises:

4. The method for determining optimal plan directed power of claim 3, wherein the step of determining the charging power boundary and the discharging power boundary for each predetermined sub-period of the battery energy storage system based on the overload boundary, the reverse flow boundary and the predicted load for each predetermined sub-period of the battery energy storage system transformer comprises:

5. The method for determining optimal planning guidance power according to claim 1, wherein the step of obtaining the energy storage profit corresponding to the planning guidance power for each preset sub-period of time comprises:

6. The method for determining the optimal planning guidance power according to claim 5, wherein the step of determining the energy storage profit corresponding to the planning guidance power in the preset sub-time period according to the first comparison result and the second comparison result comprises:

7. The method for determining optimal planning guidance power according to claim 5, wherein the step of determining the energy storage profit corresponding to the planning guidance power for the preset sub-time period according to the first comparison result and the second comparison result further comprises:

when the planned guidance power is discharge power, if the second comparison result is that the second battery state of charge is larger than a preset battery state of charge lower limit, determining the energy storage benefit of the current preset sub-time period 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; and if the second comparison result shows that the second battery SOC is not greater than the lower limit of the preset battery SOC, determining the energy storage profit of the current preset sub-time period according to the SOC difference between the first battery SOC and the lower limit of the preset battery SOC, the installed capacity of the battery energy storage system and the electricity price of the current preset sub-time period.

8. The method for determining optimal planning guidance power according to claim 5, wherein the step of determining the energy storage profit corresponding to the planning guidance power for the preset sub-time period according to the first comparison result and the second comparison result further comprises:

9. The method for determining optimal planning guidance power according to claim 1, wherein the step of obtaining the energy storage profit corresponding to the planning guidance power for each preset sub-period further comprises:

acquiring a temporary charging total amount and a temporary discharging total amount corresponding to the end moment of each preset sub-time period, determining equivalent full charging times according to the temporary charging total amount and the installed capacity of the battery energy storage system, and determining equivalent discharging times according to the temporary discharging total amount and the installed capacity of the battery energy storage system;

10. The method for determining optimal planning guidance power according to claim 1, wherein the step of obtaining the energy storage profit corresponding to the planning guidance power for each preset sub-period further comprises:

11. The method for determining the optimal planned guide power as claimed in claim 1, wherein after the step of determining that the planned guide power corresponding to each preset sub-period of the maximum energy storage profit of the optimization time period of the battery energy storage system is the optimal planned guide power corresponding to each preset sub-period, the method further comprises:

12. An optimal plan guidance power determination device, characterized by comprising: memory, a processor and a computer program stored on the memory and executable on the processor, the computer program being configured to implement the steps of the method of determining optimal plan directed power as claimed in any one of claims 1 to 11.

13. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, which computer program, when being executed by a processor, carries out the steps of the method for optimal planning guided power determination according to any of the claims 1 to 11.