Energy storage strategy generation method and device, electronic equipment, chip, storage medium and computer program product

Abstract

The embodiment of the invention provides an energy storage strategy generation method, an energy storage strategy generation device, electronic equipment, a chip, a storage medium and a computer program product, and the energy storage strategy generation method comprises the steps: determining an energy storage strategy according to first information and a preset rule corresponding to each time interval in n continuous time intervals in the future of an energy storage station; wherein the energy storage strategy is the charging and discharging state of the energy storage station in each time interval in the n continuous time intervals; the charging and discharging state is any one of the following states: charging, discharging and stopping; the first information comprises energy storage related parameters and electricity price related parameters.

Description

Technical Field

[0001] The embodiments of the present application relate to the technical field of energy storage, and in particular, to an energy storage strategy generation method, an energy storage strategy generation device, an electronic device, a chip, a storage medium, and a computer program product. Background Art

[0002] The energy storage strategies of the energy storage system mainly include the following: one charge and one discharge, that is, one charge and one discharge are performed every day; two charges and two discharges, that is, two charges and two discharges are performed every day; peak shaving and valley filling: that is, charging during valley hours and discharging during peak hours, etc. These strategies are all pre-set and executed daily, and there are problems such as poor flexibility and low energy storage utilization rate. Summary of the Invention

[0003] The embodiments of the present application provide an energy storage strategy generation method, an energy storage strategy generation device, an electronic device, a chip, a storage medium, and a computer program product.

[0004] The energy storage strategy generation method provided by the embodiments of the present application includes:

[0005] Determining an energy storage strategy according to the first information corresponding to each time interval in the next n consecutive time intervals of the energy storage station and a preset rule; wherein,

[0006] The energy storage strategy is the charge and discharge state of the energy storage station in each of the n consecutive time intervals; the charge and discharge state is any one of the following: charging, discharging, stopping; the first information includes: the initial battery pack power, the power generation power of the power generation system, the power consumption power of the energy storage station, the feed-in electricity price, the electricity consumption price; the initial battery pack power of the current time interval is the battery pack power at the end of the previous time interval.

[0007] The energy storage strategy generation device provided by the embodiments of the present application includes:

[0008] An energy storage strategy generation module: configured to determine an energy storage strategy according to the first information corresponding to each time interval in the next n consecutive time intervals of the energy storage station and a preset rule; wherein,

[0009] The energy storage strategy is the charge and discharge state of the energy storage station in each of the n consecutive time intervals; the charge and discharge state is any one of the following: charging, discharging, stopping; the first information includes: the initial battery pack power, the power generation power of the power generation system, the power consumption power of the energy storage station, the feed-in electricity price, the electricity consumption price; the initial battery pack power of the current time interval is the battery pack power at the end of the previous time interval.

[0010] The electronic device provided by an embodiment of the present application includes: a processor and a memory. The memory is used to store a computer program, and the processor is used to call and run the computer program stored in the memory to execute any energy storage strategy generation method provided by the embodiment of the present application.

[0011] The chip provided by an embodiment of the present application includes: a processor, which is used to call and run a computer program from a memory, so that a device installed with the chip executes any energy storage strategy generation method provided by the embodiment of the present application.

[0012] The storage medium provided by an embodiment of the present application is used to store a computer program, and the computer program enables a computer to execute any energy storage strategy generation method provided by the embodiment of the present application.

[0013] The computer program product provided by an embodiment of the present application includes a computer program, and the computer program realizes any energy storage strategy generation method provided by the embodiment of the present application when executed by a processor.

[0014] The energy storage strategy generation method provided by the embodiment of the present application determines an energy storage strategy according to the first information corresponding to each time interval in the future n consecutive time intervals and a preset rule; wherein, the energy storage strategy is the charge and discharge state of the energy storage station in each of the n consecutive time intervals; the first information includes: energy storage related parameters and electricity price related parameters. According to the first information of the energy storage station in different time intervals, the state of the energy storage station in different time intervals is flexibly determined, improving the flexibility of the energy storage strategy and the resource utilization rate. Description of the Drawings

[0015] The drawings described herein are used to provide a further understanding of the present application, and constitute a part of the present application. The schematic embodiments of the present application and their descriptions are used to explain the present application, and do not constitute an improper limitation to the present application. In the drawings:

[0016] Figure 1 It is a schematic implementation process of the energy storage strategy generation method provided by the embodiment of the present application Figure 1 ;

[0017] Figure 2 It is a schematic diagram of the energy storage strategy derivation provided by the embodiment of the present application;

[0018] Figure 3 It is a schematic implementation process of the energy storage strategy generation method provided by the embodiment of the present application Figure 2 ;

[0019] Figure 4 It is the overall flowchart of the energy storage strategy generation method provided by the embodiment of the present application;

[0020] Figure 5Schematic structural diagram of the energy storage strategy generation device provided by the embodiment of the present application;

[0021] Figure 6 Schematic diagram of the energy storage strategy scheduling provided by the embodiment of the present application;

[0022] Figure 7 Schematic structural diagram of the electronic device provided by the embodiment of the present application;

[0023] Figure 8 Schematic structural diagram of the chip provided by the embodiment of the present application. Detailed implementation manners

[0024] Next, the technical solutions in the embodiments of the present application will be described with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without creative efforts shall fall within the protection scope of the present application.

[0025] It should be noted that in the embodiments of the present application, the term "and / or" only describes the association relationship of associated objects and indicates that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, in the embodiments of the present application, the character " / " generally represents an "or" relationship between the associated objects before and after.

[0026] In the description of the embodiments of the present application, the term "corresponding" may represent a direct or indirect corresponding relationship between two, may also represent an association relationship between two, or may be a relationship such as indication and being indicated, configuration and being configured, etc.

[0027] To facilitate the understanding of the technical solutions in the embodiments of the present application, the related technologies in the embodiments of the present application are described below. The following related technologies can be arbitrarily combined with the technical solutions in the embodiments of the present application as optional solutions, and they all fall within the protection scope of the embodiments of the present application.

[0028] A complete electrochemical energy storage system mainly consists of a battery pack, a Battery Management System (BMS), an Energy Management System (EMS), a Power Conversion System (PCS), and other electrical equipment. It usually also includes a wind power generation unit, a photovoltaic power generation unit, a grid power supply system, an electricity consumption system, etc. In the energy storage system, the battery pack feeds back status information to the BMS, and the BMS shares it with the EMS and PCS; the EMS issues control information to the PCS and BMS according to optimization and scheduling decisions to control the single cell / battery pack to complete charging and discharging, etc. The PCS can work in the following two states and thus has two important functions: 1. Rectifier working state: When the energy storage system's battery cells are charging, it converts the direct current generated by the wind power generation system and / or photovoltaic power generation system or the alternating current from the grid into direct current; 2. Inverter working state: When discharging the energy storage system's battery cells, it converts the direct current of the battery cells into alternating current and feeds it into the grid.

[0029] In the related art, the adopted charge and discharge strategies, such as one charge and one discharge, two charges and two discharges, peak shaving and valley filling, etc., are all to preset the charge and discharge strategies for the power conversion system in advance and perform charging or discharging operations during the specified time periods, so as to exert the performance of the energy storage battery, reduce the use of grid electric energy, increase the amount of electricity fed into the grid during peak electricity periods, and thus improve the economic benefits of the energy storage station. This mode of setting the strategy is difficult to dynamically adjust the strategy according to different sites and different environmental factors. Therefore, in most cases, it is not the optimal one either.

[0030] Figure 1 Schematic implementation process of the energy storage strategy generation method provided by the embodiments of the present application Figure 1 , such as Figure 1 shown, the embodiments of the present application provide an energy storage strategy generation method, and the method includes the following steps:

[0031] Step 101: Determine an energy storage strategy according to the first information corresponding to each time interval in the next n consecutive time intervals of the energy storage station and a preset rule; where

[0032] the energy storage strategy is the charge and discharge status of the energy storage station in each of the n consecutive time intervals; the charge and discharge status is any one of the following: charging, discharging, stopping; the first information includes: energy storage related parameters and electricity price related parameters.

[0033] In the embodiments of the present application, n is a positive integer, and the total of the n consecutive time intervals can be 24 hours, that is, the next day; it can also be 12 hours, that is, the next half day; it can also be other time totals, and the embodiments of the present application do not limit this.

[0034] Exemplarily, taking the sum of n consecutive time intervals as 24 hours as an example, the value of n can be 24, and the lengths of the 24 time intervals are the same, all being 1 hour; in practical applications, the lengths of different time intervals can be the same or different, and the lengths of the time intervals can be set according to the actual situation, and the embodiments of the present application do not limit this.

[0035] In the embodiments of the present application, the selection of the charge-discharge state of the energy storage station determines the energy storage station's, and the economic benefits of the energy storage station are related to the energy storage-related parameters and electricity price-related parameters of the energy storage station. Among them, the energy storage-related parameters include: the power consumption, the power generation of the power generation system, and the electricity price-related parameters include: the electricity price for power consumption and the feed-in electricity price. Here, the power consumption refers to the unit electricity price for the energy storage station to obtain electric energy from the power grid, and the feed-in electricity price refers to the unit electricity price charged when the energy storage station sends electric energy into the power grid.

[0036] In the embodiments of the present application, the battery pack of the energy storage station cannot be overcharged or over-discharged, and the selection of the charge-discharge state of the energy storage station is also related to the battery pack power. In the embodiments of the present application, the energy storage-related parameters also include: the battery pack power.

[0037] Based on this, in an alternative embodiment of the present application, the energy storage-related parameters include: the initial battery pack power, the power generation of the power generation system, and the power consumption of the energy storage station; among them, the initial battery pack power in the current time interval is the battery pack power at the end of the previous time interval;

[0038] The electricity price-related parameters include: the feed-in electricity price and the electricity price for power consumption.

[0039] In the embodiments of the present application, for n consecutive time intervals, according to the chronological relationship of the time intervals, the charge-discharge state of the energy storage station in each time interval is determined in turn, and the battery pack power at the end of the previous time interval is used as the initial battery pack power in the current time interval. Exemplarily, if the charge-discharge state of the energy storage station corresponding to time interval i is charging, according to the charge-discharge state of time interval i, the power of the battery pack at the end of time interval i is obtained, and this power is used as the initial battery pack power in time interval i + 1.

[0040] In the embodiments of the present application, the power generation system includes a wind power generation system and / or a photovoltaic power generation system. In practical applications, the power generation system can also include other types of power generation systems, such as hydropower generation, etc., and the embodiments of the present application do not limit this.

[0041] If the power generation system includes multiple types of power generation systems, the power generation power of the power generation system is the sum of the power generation powers of each type of power generation system in the multiple types of power generation systems. For example, if the power generation system includes a wind power generation system and a photovoltaic power generation system, then the power generation power of the power generation system is the power generation power of the wind power generation system plus the power generation power of the photovoltaic power generation system.

[0042] In the embodiments of the present application, since the n consecutive time intervals are future times, the power generation power within the time intervals can be predicted based on the historical power generation power. For example, the future power generation power of the power generation system can be predicted based on the historical power generation power of the power generation system under similar weather conditions.

[0043] In the embodiments of the present application, the weather factor parameters of the energy storage station in each time interval can be determined according to the weather forecast information. For example, factors affecting the power generation of the power generation system such as sunny or cloudy weather, wind force, and temperature. The wind condition characteristics affecting the power generation of the wind power generation system and / or the light condition affecting the photovoltaic power generation system are determined according to the weather factor parameters. In the embodiments of the present application, the wind condition characteristics can also be described as wind force factors, and the light conditions can also be described as light factors.

[0044] For example, the power generation system includes a wind power generation system and a photovoltaic power generation system. For any time interval, based on the historical data of the energy storage station, the historical power generation power of the wind power generation system in the case where the wind condition characteristics are similar to those of this time interval and the historical power generation power of the photovoltaic power generation system in the case where the light conditions are similar to those of this time interval are obtained. Based on these historical data, the power generation power of the wind power generation system and the photovoltaic power generation system within this time interval are predicted, and after adding them, the power generation power of the power generation system within this time interval is obtained. It can be understood that if the power generation system only has a wind power generation system, then only the power generation power of the wind power generation system needs to be predicted, and the power generation power of the wind power generation system is used as the power generation power of the power generation system.

[0045] Based on this, in an alternative embodiment of the present application, the power generation system includes: a wind power generation system and / or a photovoltaic power generation system; the method further includes:

[0046] Predict the power generation power of the power generation system in each of the n consecutive time intervals according to the second information; the second information includes:

[0047] The wind condition characteristics corresponding to each of the n consecutive time intervals, the historical power generation power of the wind power generation system in the case where the wind condition characteristics are similar; and / or,

[0048] The light conditions corresponding to each of the n consecutive time intervals, the historical power generation power of the photovoltaic power generation system in the case where the light conditions are similar.

[0049] In the embodiments of the present application, the time-related weighted average method can be used to predict the power generation of the wind power generation system and the power generation of the photovoltaic power generation system. The historical power generation of the wind power generation system under the historical similar wind conditions is taken, and the historical power generation of the photovoltaic power generation system under the historical similar illumination conditions is taken. After weighted averaging according to the time distance from the current moment, the closer to the current time, the greater the weight, so as to improve the accuracy of the predicted value and the effectiveness of the generated strategy.

[0050] The calculation formula for the power generation of the wind power generation system is as follows:

[0051] Pf = (Pf0×k0 + Pf1×k1 +... + Pf i ×k i + Pf m ×k m ) / 2m, k i = m - i / m, 0 ≤ i ≤ m

[0052] Wherein, Pf i is the historical power generation of the wind power generation system under the i-th historical similar wind condition, k i is the weight of the historical power generation of the wind power generation system under the i-th historical similar wind condition, and m is the set historical value range.

[0053] The calculation formula for the power generation of the photovoltaic power generation system is as follows:

[0054] Pg = (Pg0×k0 + Pg1×k1 +... + Pg i ×k i + Pg m ×k m ) / 2m, k i = m - i / m, 0 ≤ i ≤ m

[0055] Wherein, Pg i is the historical power generation of the photovoltaic power generation system under the i-th historical similar illumination condition, k i is the weight of the historical power generation of the photovoltaic power generation system under the i-th historical similar illumination condition, and m is the set historical value range.

[0056] In the embodiments of the present application, since n consecutive time intervals are future times, the power consumption within the time intervals can be predicted based on the historical power consumption. In the embodiments of the present application, two methods are provided to predict the power consumption of the energy storage station within each time interval.

[0057] One way is to calculate separately for each time interval. For any time interval, based on the historical power consumption of the energy storage station in that time interval, predict the power consumption of the energy storage station within that time interval. For example, if the time interval is [0, 1), that is, from 0 o'clock to 1 o'clock, based on the historical power consumption of the energy storage station from 0 o'clock to 1 o'clock, predict the historical power consumption of the energy storage station from 0 o'clock to 1 o'clock in the future. This way has higher accuracy.

[0058] Another way is to calculate the first power consumption based on the historical power consumption of the energy storage station and use it as the power consumption of the energy storage station shared by each time interval. This way has less calculation amount.

[0059] Based on this, in an optional implementation manner of the present application, the method further includes: predicting the power consumption of the energy storage station in each of the n consecutive time intervals according to the third information; the third information includes: the historical power consumption of the energy storage station in each of the n consecutive time intervals; or, predicting the first power consumption according to the fourth information and using the first power consumption as the power consumption of the energy storage station in each of the n consecutive time intervals; the fourth information includes the historical power consumption of the energy storage station.

[0060] In an embodiment of the present application, taking the calculation of the first power consumption based on the historical power consumption of the energy storage station and using it as the power consumption of the energy storage station shared by each time interval as an example, the first power consumption is obtained by using the time-related weighted average method. Take the historical power consumption of the energy storage station, perform weighted average according to the time distance from the current moment to obtain the estimated value. The closer to the current time, the greater the weight, so as to improve the accuracy of the estimated value and the effectiveness of the generated strategy. The calculation formula is as follows:

[0061] Py=(Py0×k0 + Py1×k1+...+Py i ×k i +Py m ×k m ) / 2m, k i =m - i / m, 0≤i≤m

[0062] Where, Py i is the historical power consumption of the i-th energy storage station, k i is the weight of the historical power consumption of the i-th energy storage station, and m is the set historical value range.

[0063] In an embodiment of the present application, during the power generation of the wind power generation system, the power generation of the photovoltaic power generation system, and the power consumption of the energy storage system, the values of m for the three can be the same or different, and can be set according to the actual situation. The embodiments of the present application do not limit this.

[0064] In the embodiments of the present application, the feed-in electricity price and the electricity consumption price corresponding to different time intervals can be determined according to the peak-valley period range and the electricity price information of the area where the energy storage station is located.

[0065] In the embodiments of the present application, if the charge-discharge state of the energy storage station is to be set to charging, it is first necessary that the initial battery pack power is less than or equal to the maximum charging capacity of the battery pack to protect the charging safety of the battery pack. Further, it is necessary that the power generation power of the power generation system is greater than the power consumption power of the energy storage station. In addition to supplying the power consumption needs of the energy storage station, the power generation system has surplus electric energy to charge the battery pack; or on the premise that the initial battery pack power is less than or equal to the maximum charging capacity of the battery pack, the power generation power of the power generation system is equal to the power consumption power of the energy storage station, and the electricity consumption price is less than the first price; the first price is the relative maximum value of the electricity consumption price, because when charging and then using at a price higher than the first price, the energy storage station has no differential income.

[0066] In the embodiments of the present application, if the charge-discharge state of the energy storage station is to be set to discharging, it is first necessary that the initial battery pack power is greater than the minimum discharge capacity of the battery pack to protect the discharging safety of the battery pack. Further, it is necessary that the power generation power of the power generation system is less than the power consumption power of the energy storage station, and the battery pack discharge satisfies the power consumption demand of the energy storage station; or on the premise that the initial battery pack power is greater than the minimum discharge capacity of the battery pack, the power generation power of the power generation system is greater than or equal to the power consumption power of the energy storage station, and the feed-in electricity price is greater than the second price; the second price is the relative minimum value of the electricity consumption price, because when the feed-in electricity price is lower than the second price, the energy storage station has no differential income after charging and then using.

[0067] In the embodiments of the present application, if the charge-discharge state of the energy storage station is to be set to stop, it is necessary to satisfy that the power generation power of the power generation system is less than or equal to the power consumption power of the energy storage station, and the electricity consumption price is equal to the first price. When charging and then using at an electricity consumption price higher than the first price, there will be no differential income.

[0068] It can be expressed by the following formula:

[0069] S = charging, E ≤ E max and (Pf + Pg - Py) > 0

[0070] S = charging, E ≤ E max and (Pf + Pg - Py) = 0 and Yd < Yd max

[0071] S = discharging, E > E min and (Pf + Pg - Py) < 0

[0072] S = discharging, E > E min and (Pf + Pg - Py) ≥ 0 and Kd > Yd min

[0073] S = Stop, (Pf + Pg - Py) ≤ 0, and Yd = Yd max

[0074] Wherein, S represents the charge and discharge state, E represents the initial battery pack power, E max represents the maximum charge capacity of the battery pack, E min represents the minimum discharge capacity of the battery pack, Yd represents the electricity price for power consumption, Kd represents the feed-in tariff, Yd max represents the first price, Yd min represents the second price.

[0075] Based on this, in an alternative embodiment of the present application, the preset rules include one or more of the following:

[0076] When the initial battery pack power is less than or equal to the maximum charge capacity of the battery pack, and the power generation of the power generation system is greater than the power consumption of the energy storage station, determine the charge and discharge state of the energy storage station as charging;

[0077] When the initial battery pack power is less than or equal to the maximum charge capacity of the battery pack, and the power generation of the power generation system is equal to the power consumption of the energy storage station, and the electricity price for power consumption is less than the first price, determine the charge and discharge state of the energy storage station as charging; the first price is the relative maximum value of the electricity price for power consumption;

[0078] When the initial battery pack power is greater than the minimum discharge capacity of the battery pack, and the power generation of the power generation system is less than the power consumption of the energy storage station, determine the charge and discharge state of the energy storage station as discharging;

[0079] When the initial battery pack power is greater than the minimum discharge capacity of the battery pack, and the power generation of the power generation system is greater than or equal to the power consumption of the energy storage station, and the feed-in tariff is greater than the second price, determine the charge and discharge state of the energy storage station as charging; the first price is the relative minimum value of the electricity price for power consumption; and,

[0080] When the power generation of the power generation system is less than or equal to the power consumption of the energy storage station, and the electricity price for power consumption is equal to the first price, determine the charge and discharge state of the energy storage station as stop; the first price is the relative minimum value of the electricity price for power consumption.

[0081] In the embodiments of the present application, the maximum charging capacity and the minimum discharging capacity of the battery pack can be obtained from the initial battery capacity, the battery health, and the battery limiting capacity factor. The relative maximum value of the electricity consumption price and the relative minimum value of the electricity consumption price can be determined based on the peak-valley period range and the electricity price information in the area where the energy storage station is located. Exemplarily, the maximum charging amount of the battery pack does not exceed 90% of the battery capacity, and the battery pack power during discharging is not less than 10% of the battery capacity. The battery limiting capacity factors are taken as 0.9 and 0.1 respectively, where 0.9 is used to calculate the maximum charging capacity of the battery pack, and 0.1 is used to calculate the minimum discharging capacity.

[0082] Reference Figure 2 , Figure 2 is a schematic diagram for deriving the energy storage strategy provided by the embodiments of the present application. As Figure 2 shown, a day is divided into 24 time intervals, namely time interval 0, time interval 1... time interval 23. The power generation system includes a wind power generation system and a photovoltaic power generation system. The first information corresponding to each time interval includes the electricity consumption power of the energy storage system, the power generation power of the wind power generation system, the power generation power of the photovoltaic power generation system, the electricity consumption price, the feed-in electricity price, and the initial battery pack power. According to the order from time interval 0 to time interval 23, the charge-discharge state of each time interval is determined in sequence.

[0083] In the embodiments of the present application, the process of determining the charge-discharge state of the energy storage station in each time interval is as follows: based on the state Si-1 of time interval i-1, the initial battery pack power of time interval i is obtained, and then the state Si of time interval i is determined according to the first information of time interval i, and then the state of time interval i+1 is further derived; if no appropriate state can be selected for time interval i+1, the state of i is adjusted. For example, if the charge-discharge state determined for time interval i+1 according to the preset rule is charging, but the battery pack capacity of the energy storage system is not rechargeable at this time, then time interval i is adjusted to the discharging state; for another example, if the charge-discharge state determined for time interval i+1 according to the preset rule is discharging, but the battery pack capacity of the energy storage system is not dischargeable at this time, then time interval i is adjusted to the charging state. The charge-discharge state of time interval i+1 is derived based on the state of time interval i, so as to ensure the optimality of the charge-discharge state of each time interval and the overall optimality.

[0084] Based on this, in an alternative embodiment of the present application, the method further includes: during the process of determining the energy storage strategy, if the charge-discharge state determined for the current time interval does not meet the preset conditions, then the charge-discharge state of the previous time interval is adjusted so that the charge-discharge state determined for the current time interval meets the preset conditions.

[0085] In the embodiments of the present application, the preset conditions include: if the charge-discharge state within a time interval is charging, the battery pack capacity within that time interval supports charging; if the charge-discharge state within a time interval is discharging, the battery pack capacity within that time interval supports discharging.

[0086] In the embodiments of the present application, for a time interval, after judging according to the first information and the preset rules, multiple different charge-discharge states may be determined. In the embodiments of the present application, different charge-discharge states can be traversed until all possible combinations of charge-discharge states are selected. Exemplarily, if the charge-discharge state determined for the first time interval is charging, the state determined for the second time interval can be either charging or discharging. Then there are two energy storage strategies respectively:

[0087] Energy storage strategy 1: Time interval 1, charging; Time interval 2, discharging;

[0088] Energy storage strategy 2: Time interval 1, charging; Time interval 2, charging;

[0089] Based on energy storage strategy 1 and energy storage strategy 2, the charge-discharge states of time interval 3 are determined respectively. If the state of time interval 3 determined based on energy storage strategy 1 is charging, the state of time interval 3 determined based on energy storage strategy 2 can be either charging or stopping;

[0090] Then there are three energy storage strategies:

[0091] Energy storage strategy 1: Time interval 1, charging; Time interval 2, discharging; Time interval 3, charging;

[0092] Energy storage strategy 2.1: Time interval 1, charging; Time interval 2, charging; Time interval 3, charging;

[0093] Energy storage strategy 2.2: Time interval 1, charging; Time interval 2, charging; Time interval 3, stopping;

[0094] And so on, until all possible combinations of charge-discharge states are selected to obtain multiple energy storage strategies. The multiple different energy storage strategies are simulated and operated in the energy storage station, and the total power fed into the grid and the total power consumed by the user after the operation of each energy storage strategy in the multiple different energy storage strategies are obtained respectively. The first parameter is calculated according to the total power fed into the grid, the total power consumed by the user, the grid feed-in price and the user electricity price of each energy storage strategy. The first parameter characterizes the economic benefit of adopting the energy storage strategy. The energy storage strategy with the largest first parameter value is selected as the energy storage strategy for the future continuous n time intervals.

[0095] Based on this, in an alternative embodiment of the present application, the method further includes: if the determined energy storage strategies are multiple different energy storage strategies, simulating the operation of the multiple energy storage strategies to obtain first parameters of each energy storage strategy among the multiple energy storage strategies; the first parameters are determined based on the total feed-in power, feed-in electricity price, total electricity consumption, and electricity consumption price.

[0096] Determine a first energy storage strategy according to the first parameters of each energy storage strategy among the multiple energy storage strategies, where the first energy storage strategy represents the energy storage strategy with the largest parameter value corresponding to the first parameter among the multiple energy storage strategies.

[0097] In the embodiments of the present application, there are generally two types of feed-in electricity prices in a region, namely peak-period feed-in electricity price and valley-period feed-in electricity price, and there are generally two types of electricity consumption prices in a region, namely peak-period electricity consumption price and valley-period electricity consumption price. The total feed-in power is divided into peak-period total feed-in power and valley-period total feed-in power, and the total electricity consumption is divided into peak-period total electricity consumption and valley-period total electricity consumption, which can be calculated by the following formula:

[0098] First parameter = peak-period total feed-in power × peak-period feed-in electricity price + valley-period total feed-in power × valley-period feed-in electricity price - peak-period total electricity consumption × peak-period electricity consumption price - valley-period total electricity consumption × valley-period electricity consumption price.

[0099] Reference Figure 3 and Figure 4 , Figure 3 is a schematic implementation process of the energy storage strategy generation method provided by the embodiments of the present application Figure 2 , Figure 4 is the overall flowchart of the energy storage strategy generation method provided by the embodiments of the present application. As shown in Figure 3 and Figure 4 , the embodiments of the present application provide an energy storage strategy generation method, and the method includes the following steps:

[0100] Step 301: Obtain the operation data of the energy storage station.

[0101] Obtain the data and parameters of the energy storage station. After data cleaning, obtain the parameter information of the energy storage station and the monitoring data of the energy storage station. The parameter information of the energy storage station includes the geographical location of the energy storage station, the capacity of the battery pack, the power parameters of the wind turbine generator, the power parameters of the photovoltaic generator, etc.; the monitoring data of the energy storage station includes the battery pack power, battery pack health, charge and discharge limits, charging power or discharging power, etc.

[0102] Obtain the weather data of the energy storage station, including historical weather data and weather forecast data. After data extraction and classification, obtain weather parameters, mainly including information related to power generation of the power generation system such as sunny or cloudy weather, wind direction and speed, and temperature.

[0103] Obtain the peak-valley rule data of the electricity price in the area where the energy storage station is located according to the address location of the energy storage station, and obtain the peak-valley parameters after data classification, including: the peak-valley time period range of the power grid and the electricity price information.

[0104] Other data related to the charge and discharge state of the energy storage system can also be obtained, and the embodiments of the present application do not limit this.

[0105] Step 302: Obtain the energy storage strategy generation parameters according to the operation data of the energy storage station.

[0106] The energy storage strategy generation parameters include energy storage-related parameters and electricity price-related parameters.

[0107] Construct energy storage-related parameters according to the operation data of the energy storage station:

[0108] Calculate the power generation parameters of the power generation system according to the parameters of the wind power generation system and the photovoltaic power generation system; for example, battery capacity, charging rated power, wind power generation rated power, and photovoltaic power generation rated power. Among them, the battery capacity = the initial battery capacity × the battery health degree × the battery limit capacity coefficient; the charging rated power P is consistent with the rated charging power of the rectifier; the wind power generation rated power is the total output power of the wind power generation system (the sum of the output powers of each sub-wind turbine system) or the maximum value in the total output power of the historical wind power generation system in the recent period; the rated power of the photovoltaic power generation system is (the sum of the output powers of each sub-photovoltaic power generation unit) or the maximum value in the total output power of the historical photovoltaic power generation system in the recent period;

[0109] Construct state data based on the real-time data and historical data of the energy storage station, that is, obtain the real-time charge and discharge state data from the real-time data of the energy storage station, and obtain the charge and discharge state data corresponding to different time intervals from the historical data. For example: S(i, j) (i > 0, 0 ≤ j < 24) represents the charge and discharge state of the jth battery at the ith moment of the date, and the value is charge, discharge or stop, Pf(i, j) (i > 0, 0 ≤ j < 24) represents the power generation power of the jth wind power generation system at the ith moment of the date, and Pg(i, j) (i > 0, 0 ≤ j < 24) represents the power generation power of the jth photovoltaic power generation system at the ith moment of the date;

[0110] Construct weather factor parameters based on weather forecast information, that is, the predicted values of factors affecting power generation such as sunny or cloudy weather, wind force, and temperature at different time intervals in a day, and predict the power generation power of the power generation system based on these factors; estimate the factors affecting power generation power in a day according to the weather forecast information. For example, fi(0≤i<24) represents the predicted wind force factor at the i-th moment in a day, and gi(0≤i<24) represents the predicted light factor at the i-th moment in a day;, predict the power generation power at different moments in a day. Pfi(0≤i<24) represents the predicted wind power generation power at the i-th moment in a day, and Pgi(0≤i<24) represents the predicted photovoltaic power generation power at the i-th moment in a day. And Pfi and Pgi can be estimated by the time-related weighted average method based on the power generation system parameters and reference historical data.

[0111] The actual charging power of the battery pack is not greater than the rated charging power; if the wind power generation power estimated according to the wind condition characteristics is greater than the rated wind power generation power, the wind power generation power is the rated wind power generation power; if the photovoltaic system power generation power estimated according to the light condition is greater than the rated photovoltaic power generation power, the photovoltaic system power generation power is the rated photovoltaic power generation power;

[0112] Construct peak-valley parameters based on the peak-valley period rule information of the area where the energy storage power station is located, that is, electricity price-related parameters, the feed-in electricity price and the electricity consumption price at different time intervals in a day; for example: Kdi(0≤i<24) represents the feed-in electricity price at the i-th moment in a day, and Ydi(0≤i<24) represents the electricity consumption price at the i-th moment in a day.

[0113] Step 303: Generate parameters according to the energy storage strategy to obtain the energy storage strategy.

[0114] Reference Figure 2 , a day can be divided into 24 time intervals, and according to the first information and preset rules corresponding to each time interval, the charge and discharge states of each time interval are determined in turn to obtain the energy storage strategy; specifically,

[0115] Since the charge-discharge state in the current time interval depends on the battery power at the end of the previous time interval, based on the idea of dynamic programming, the charge-discharge state of the next time interval can be deduced and calculated in sequence until a set of relatively optimal strategies are calculated. Assume that a day is divided into 24 time intervals by hours, with each hour being 1 time interval. Taking the first information at the initial moment of the time interval as the first information of the time interval, the charge-discharge state of the i-th time interval of the energy storage system is Si (i = 1, 2, 3,..., 24). The specific deduction process is as follows: First, set the charge-discharge states of all time intervals to stop, that is, Si = stop, (i = 1, 2, 3,..., 24); Based on the first information and preset rules, adjust the charge-discharge states of each time interval to charge, discharge, or stop in sequence. Based on the state of Si-1, obtain the initial battery power of the i-th time interval, determine Si, and then continue to deduce the state Si+1 of the i+1-th time interval; When no suitable state can be selected for the i+1-th time interval, adjust the state of the i-th time interval. For example: If the i+1-th time interval should be charged according to the preset rules, but the battery pack capacity of the energy storage system is not chargeable at this time, then adjust the i-th time interval to the discharge state. If the i+1-th time interval should be discharged according to the preset rules, but the battery pack capacity of the energy storage system is not dischargeable at this time, then adjust the i-th time interval to the charge state; And so on until all possible combinations of charge-discharge states are selected, that is, multiple charge-discharge strategies, namely multiple energy storage strategies. The charge-discharge state of the i+1-th time interval is deduced based on the charge-discharge state of the i-th time interval, so as to ensure that the charge-discharge state of each time interval is optimal and the overall is optimal.

[0116] Simulate the operation of multiple different energy storage strategies in the energy storage station, and respectively obtain the total feed-in power and total power consumption of each energy storage strategy after the operation of the multiple different energy storage strategies. Calculate the first parameter based on the total feed-in power, total power consumption, feed-in electricity price, and power consumption electricity price of each energy storage strategy. The first parameter characterizes the economic benefit of adopting the energy storage strategy, and select the energy storage strategy with the largest first parameter value as the energy storage strategy for the next day.

[0117] Generally, there are two types of feed-in electricity prices in a region, namely the peak-period feed-in electricity price and the valley-period feed-in electricity price. Generally, there are two types of power consumption electricity prices in a region, namely the peak-period power consumption electricity price and the valley-period power consumption electricity price. Divide the total feed-in power into the peak-period total feed-in power and the valley-period total feed-in power, and divide the total power consumption into the peak-period total power consumption and the valley-period total power consumption. It can be calculated by the following formula:

[0118] First parameter = peak-period total feed-in power × peak-period feed-in electricity price + valley-period total feed-in power × valley-period feed-in electricity price - peak-period total power consumption × peak-period power consumption electricity price - valley-period total power consumption × valley-period power consumption electricity price.

[0119] Step 304: Execute the energy storage strategy and feedback the execution result.

[0120] The obtained energy storage strategy is sent to the energy management system of the energy storage station for execution, and the execution results are recorded regularly. At the same time, the parameters related to weather factors are recalculated to optimize the dynamic programming formula. Specifically, the operation data of the energy storage system after the actual execution of the strategy is used as the basis for determining the first information, and the first information is automatically updated based on the operation data, so as to keep the relevant parameters accurate, continuously improve the accuracy of the strategy generation parameters, and enhance the effectiveness of strategy generation.

[0121] The energy storage strategy generation method provided by the embodiments of the present application processes the parameter data of the energy storage station, real-time and historical charge and discharge states, weather forecast information, and peak-valley period rules, estimates the power generation power of the power generation system and the power consumption power of the energy storage station, generates energy storage strategy parameters, generates predicted values of the charge and discharge states using historical power consumption and power generation data according to energy storage-related parameters and electricity price-related parameters, adjusts the charge and discharge states hourly, derives multiple groups of energy storage strategies, performs dynamic programming and simulation execution on the charge and discharge states in different time periods, determines the best charge and discharge plan to maximize the benefits, sends the generated optimal strategy to the energy storage station for execution, and dynamically optimizes the strategy according to the execution results and changes in weather factors, so as to continuously improve the operation efficiency and benefits of the energy storage system. The energy storage system can adapt to changing power demands and market prices in real time, achieving higher economic benefits and resource utilization rates.

[0122] The embodiments of the present application also provide an energy storage strategy generation device. Refer to Figure 5 , Figure 5 which is the structural schematic diagram of the energy storage strategy generation device provided by the embodiments of the present application. The energy storage strategy generation device in this embodiment includes:

[0123] An energy storage strategy generation module: used to determine the energy storage strategy according to the first information corresponding to each time interval in the next n consecutive time intervals of the energy storage station and the preset rules; wherein, the energy storage strategy is the charge and discharge state of the energy storage station in each of the n consecutive time intervals; the charge and discharge state is any one of the following: charging, discharging, stopping; the first information includes: the initial battery pack power, the power generation power of the power generation system, the power consumption power of the energy storage station, the feed-in electricity price, and the electricity consumption price; the initial battery pack power of the current time interval is the battery pack power at the end of the previous time interval.

[0124] In the embodiments of the present application, the energy storage-related parameters include: the initial battery pack power, the power generation power of the power generation system, and the power consumption power of the energy storage station; wherein, the initial battery pack power of the current time interval is the battery pack power at the end of the previous time interval; the electricity price-related parameters include: the feed-in electricity price and the electricity consumption price.

[0125] In the embodiments of the present application, the preset rules include one or more of the following:

[0126] When the initial battery pack power is less than or equal to the maximum charging capacity of the battery pack, and the power generation power of the power generation system is greater than the power consumption power of the energy storage station, determine that the charge-discharge state of the energy storage station is charging;

[0127] When the initial battery pack power is less than or equal to the maximum charging capacity of the battery pack, the power generation power of the power generation system is equal to the power consumption power of the energy storage station, and the electricity consumption price is less than the first price, determine that the charge-discharge state of the energy storage station is charging; the first price is the relative maximum value of the electricity consumption price;

[0128] When the initial battery pack power is greater than the minimum discharge capacity of the battery pack, and the power generation power of the power generation system is less than the power consumption power of the energy storage station, determine that the charge-discharge state of the energy storage station is discharging;

[0129] When the initial battery pack power is greater than the minimum discharge capacity of the battery pack, the power generation power of the power generation system is greater than or equal to the power consumption power of the energy storage station, and the feed-in tariff is greater than the second price, determine that the charge-discharge state of the energy storage station is charging; the first price is the relative minimum value of the electricity consumption price; and,

[0130] When the power generation power of the power generation system is less than or equal to the power consumption power of the energy storage station, and the electricity consumption price is equal to the first price, determine that the charge-discharge state of the energy storage station is stopped; the first price is the relative minimum value of the electricity consumption price.

[0131] In the embodiments of the present application, the power generation system includes: a wind power generation system and / or a photovoltaic power generation system; the energy storage strategy generation module: is further configured to predict the power generation power of the power generation system in each of the n consecutive time intervals according to the second information; the second information includes:

[0132] The wind condition characteristics corresponding to each of the n consecutive time intervals, and the historical power generation power of the wind power generation system in the case of wind condition characteristics similar thereto; and / or,

[0133] The illumination conditions corresponding to each of the n consecutive time intervals, and the historical power generation power of the photovoltaic power generation system in the case of illumination conditions similar thereto.

[0134] In the embodiments of the present application, the energy storage strategy generation module is further configured to predict the power consumption of the energy storage station in each of the n consecutive time intervals according to the third information; the third information includes the historical power consumption of the energy storage station in each of the n consecutive time intervals; or, predict the first power consumption according to the fourth information, and use the first power consumption as the power consumption of the energy storage station in each of the n consecutive time intervals; the fourth information includes the historical power consumption of the energy storage station.

[0135] In the embodiments of the present application, the energy storage strategy generation module is further configured to, in the process of determining the energy storage strategy, if the charge and discharge state determined in the current time interval does not meet the preset conditions, adjust the charge and discharge state in the previous time interval so that the charge and discharge state determined in the current time interval meets the preset conditions.

[0136] In the embodiments of the present application, the energy storage strategy generation module is further configured to, if the determined energy storage strategies are multiple different energy storage strategies, simulate the operation of the multiple energy storage strategies to obtain the first parameters of each energy storage strategy in the multiple energy storage strategies; the first parameters are determined based on the total feed-in power, feed-in electricity price, total power consumption, and electricity price for power consumption; determine the first energy storage strategy according to the first parameters of each energy storage strategy in the multiple energy storage strategies, where the first energy storage strategy represents the energy storage strategy with the largest parameter value corresponding to the first parameters among the multiple energy storage strategies.

[0137] Those skilled in the art should understand that Figure 5 The implementation functions of the units in the shown energy storage strategy generation device can be understood with reference to the relevant descriptions of the foregoing method. Figure 5 The functions of the units in the shown energy storage strategy generation device can be implemented by a program running on a processor or by specific logic circuits.

[0138] Refer to Figure 6 , Figure 6 which is the schematic diagram of energy storage strategy scheduling provided by the embodiments of the present application. As Figure 6 shown, the energy storage strategy generation module provided by the embodiments of the present application can be deployed on the cloud side, connect to weather prediction data and peak-valley electricity price data, and multiple energy storage stations, obtain various energy storage data from the edge-side energy storage stations, and generate energy storage strategies for each energy storage station respectively. Then, the generated energy storage strategies are sent to the energy management systems of the edge-side energy storage stations for energy storage charge and discharge control, that is, control the charge and discharge state of the energy storage battery pack according to the energy storage strategy, and control the flow direction of electric energy among the energy storage battery, the wind-solar power generation system, and the power grid in different time periods to reduce the power consumption of the power grid, reduce the power consumption during peak periods, and increase the power fed into the power grid during peak periods, so as to achieve the maximum economic benefit.

[0139] Figure 7It is a schematic structural diagram of an electronic device 700 provided by an embodiment of the present application. Figure 7 The illustrated electronic device 700 includes a processor 710. The processor 710 can call and run a computer program from a memory to implement the method in the embodiment of the present application.

[0140] Optionally, as Figure 7 shown, the electronic device 700 may further include a memory 720. Among them, the processor 710 can call and run a computer program from the memory 720 to implement the method in the embodiment of the present application.

[0141] Among them, the memory 720 can be a separate device independent of the processor 710, or can be integrated in the processor 710.

[0142] Optionally, as Figure 7 shown, the electronic device 700 may further include a transceiver 730. The processor 710 can control the transceiver 730 to communicate with other devices. Specifically, it can send information or data to other devices, or receive information or data sent by other devices.

[0143] Among them, the transceiver 730 can include a transmitter and a receiver. The transceiver 730 may further include an antenna, and the number of antennas can be one or more.

[0144] The electronic device 700 can specifically be the energy storage strategy generation device in the embodiment of the present application, and the electronic device 700 can implement the corresponding processes implemented by the energy storage strategy generation device in each method of the embodiment of the present application. For the sake of brevity, it will not be elaborated here.

[0145] Exemplarily, an embodiment of the present application further provides a computer program product, including a computer program, and the computer program can be executed by the processor 710 of the communication device 700 to complete the steps described in any of the foregoing methods.

[0146] Figure 8 It is a schematic structural diagram of a chip in an embodiment of the present application. Figure 8 The illustrated chip 800 includes a processor 810. The processor 810 can call and run a computer program from a memory to implement the method in the embodiment of the present application.

[0147] Optionally, as Figure 8 shown, the chip 800 may further include a memory 820. Among them, the processor 810 can call and run a computer program from the memory 820 to implement the method in the embodiment of the present application.

[0148] Among them, the memory 820 can be a separate device independent of the processor 810, or can be integrated in the processor 810.

[0149] Optionally, the chip 800 may further include an input interface 830. The processor 810 may control the input interface 830 to communicate with other devices or chips. Specifically, it may obtain information or data sent by other devices or chips.

[0150] Optionally, the chip 800 may further include an output interface 840. The processor 810 may control the output interface 840 to communicate with other devices or chips. Specifically, it may output information or data to other devices or chips.

[0151] The chip may be applied to the electronic device 700 in the embodiments of the present application, and the chip may implement the corresponding processes implemented by the electronic device 700 in each method of the embodiments of the present application. For the sake of brevity, details are not described herein again.

[0152] It should be understood that the chip mentioned in the embodiments of the present application may also be referred to as a system-on-chip, system chip, chip system, or system-on-chip.

[0153] It should be understood that the processor in the embodiments of the present application may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method embodiments may be completed by the integrated logic circuit in the hardware of the processor or by instructions in the form of software. The above-mentioned processor may be a general-purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. It may implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present application. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in combination with the embodiments of the present application may be directly embodied as being executed by the hardware decoding processor, or executed by a combination of the hardware and software units in the decoding processor. The software unit may be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory, and the processor reads the information in the memory and combines its hardware to complete the steps of the above method.

[0154] It can be understood that the memory in the embodiments of the present application can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchlink dynamic random access memory (SLDRAM), and direct rambus random access memory (DR RAM). It should be noted that the memory of the systems and methods described herein is intended to include but not be limited to these and any other suitable types of memory.

[0155] It should be understood that the above memory is by way of example but not limitation. For example, the memory in the embodiments of the present application can also be a static random access memory (SRAM), a dynamic random access memory (DRAM), a synchronous dynamic random access memory (SDRAM), a double data rate SDRAM (DDR SDRAM), an enhanced SDRAM (ESDRAM), a synch link DRAM (SLDRAM), and a direct rambus random access memory (DR RAM), etc. That is to say, the memory in the embodiments of the present application is intended to include but not be limited to these and any other suitable types of memory.

[0156] The embodiments of the present application also provide a storage medium for storing a computer program. The storage medium can be applied to the electronic device 700 in the embodiments of the present application, and the computer program enables the computer to execute the corresponding processes implemented by the electronic device 700 in the various methods of the embodiments of the present application. For the sake of brevity, details are not described herein again.

[0157] Those of ordinary skill in the art will appreciate that the units and algorithm steps of the examples described in connection with the embodiments disclosed herein can be implemented in electronic hardware, or in a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. A professional technician can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0158] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments, and details are not described herein again.

[0159] In several embodiments provided by the present application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces, and the indirect coupling or communication connection of the devices or units may be in an electrical, mechanical, or other form.

[0160] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0161] In addition, the functional units in the various embodiments of the present application can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit.

[0162] When the above-mentioned functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art or a part of this technical solution can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or an electronic device 700, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs.

[0163] As described above, the above are only specific implementation manners of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed by this application can easily think of changes or substitutions, which should all be covered within the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

Claims

1. A method for generating an energy storage strategy, characterized in that, Including: Determine an energy storage strategy according to the first information corresponding to each time interval in the next n consecutive time intervals of the energy storage station and a preset rule; wherein, The energy storage strategy is the charge and discharge state of the energy storage station in each of the n consecutive time intervals; the charge and discharge state is any one of the following: charging, discharging, stopping; the first information includes: energy storage related parameters and electricity price related parameters.

2. The method according to claim 1, wherein The energy storage related parameters include: the initial battery pack power, the power generation power of the power generation system, and the power consumption of the energy storage station; wherein, the initial battery pack power in the current time interval is the battery pack power at the end of the previous time interval; The electricity price related parameters include: the feed-in electricity price and the electricity consumption price.

3. The method according to claim 2, wherein The preset rule includes one or more of the following: When the initial battery pack power is less than or equal to the maximum charging capacity of the battery pack, and the power generation power of the power generation system is greater than the power consumption of the energy storage station, determine the charge and discharge state of the energy storage station as charging; When the initial battery pack power is less than or equal to the maximum charging capacity of the battery pack, and the power generation power of the power generation system is equal to the power consumption of the energy storage station, and the electricity consumption price is less than the first price, determine the charge and discharge state of the energy storage station as charging; the first price is the relative maximum value of the electricity consumption price; When the initial battery pack power is greater than the minimum discharge capacity of the battery pack, and the power generation power of the power generation system is less than the power consumption of the energy storage station, determine the charge and discharge state of the energy storage station as discharging; When the initial battery pack power is greater than the minimum discharge capacity of the battery pack, and the power generation power of the power generation system is greater than or equal to the power consumption of the energy storage station, and the feed-in electricity price is greater than the second price, determine the charge and discharge state of the energy storage station as charging; the first price is the relative minimum value of the electricity consumption price; And, When the power generation power of the power generation system is less than or equal to the power consumption of the energy storage station, and the electricity consumption price is equal to the first price, determine the charge and discharge state of the energy storage station as stopping; the first price is the relative minimum value of the electricity consumption price.

4. The method according to claim 3, wherein The power generation system includes: a wind power generation system and / or a photovoltaic power generation system; the method further includes: Predict the power generation power of the power generation system in each of the n consecutive time intervals according to the second information; the second information includes: The wind condition characteristics corresponding to each time interval in the n consecutive time intervals, and the historical power generation power of the wind power generation system in the case of similar wind condition characteristics; and / or, The illumination conditions corresponding to each time interval in the n consecutive time intervals, and the historical power generation power of the photovoltaic power generation system in the case of similar illumination conditions.

5. The method according to claim 4, wherein It further includes: Predict the power consumption of the energy storage station in each of the n consecutive time intervals according to the third information; The third information includes: the historical power consumption of the energy storage station in each of the n consecutive time intervals; or, according to the fourth information, predicting the first power consumption and using the first power consumption as the power consumption of the energy storage station in each of the n consecutive time intervals; the fourth information includes the historical power consumption of the energy storage station.

6. The method according to any one of claims 1 to 5, characterized in that, Further included is: In the process of determining the energy storage strategy, if the charge-discharge state determined for the current time interval does not meet the preset conditions, adjust the charge-discharge state of the previous time interval so that the charge-discharge state determined for the current time interval meets the preset conditions.

7. The method according to claim 6, wherein Further included is: If the determined energy storage strategies are multiple different energy storage strategies, simulate the operation of the multiple energy storage strategies to obtain the first parameters of each energy storage strategy among the multiple energy storage strategies; The first parameter is determined based on the total power of the feed network, the feed network electricity price, the total power consumption, and the electricity price of power consumption; According to the first parameters of each energy storage strategy among the multiple energy storage strategies, determine the first energy storage strategy, where the first energy storage strategy represents the energy storage strategy with the largest parameter value corresponding to the first parameter among the multiple energy storage strategies.

8. An energy storage strategy generation device, characterized in that, Included are: An energy storage strategy generation module: used to determine the energy storage strategy according to the first information corresponding to each of the future n consecutive time intervals of the energy storage station and the preset rules; where, The energy storage strategy is the charge-discharge state of the energy storage station in each of the n consecutive time intervals; the charge-discharge state is any one of the following: charging, discharging, stopping; the first information includes: the initial battery pack power, the power generation of the power generation system, the power consumption of the energy storage station, the feed network electricity price, the electricity price of power consumption; the initial battery pack power of the current time interval is the battery pack power at the end of the previous time interval.

9. An electronic device, characterized in that, Included are: A processor and a memory, where the memory is used to store a computer program, and the processor is used to call and run the computer program stored in the memory to execute the energy storage strategy generation method according to any one of claims 1 to 7.

10. A chip, characterized in that, Included is: A processor, used to call and run a computer program from the memory, so that the device installed with the chip executes the energy storage strategy generation method according to any one of claims 1 to 7.

11. A storage medium, characterized in that, Used to store a computer program, and the computer program enables a computer to execute the energy storage strategy generation method according to any one of claims 1 to 7.

12. A computer program product, comprising a computer program, characterized in that, The computer program, when executed by a processor, implements the energy storage strategy generation method according to any one of claims 1 to 7.

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