Energy scheduling method, energy storage system and storage medium

Abstract

The invention relates to the technical field of energy storage, and provides an energy scheduling method, an energy storage system and a storage medium. The method comprises the following steps: acquiring prediction data of generation power of a photovoltaic power generation assembly, prediction data of electricity utilization power of a load and electricity purchase price data; based on the prediction data of the power generation power and the prediction data of the power utilization power, calculating predicted electricity supplement quantity and predicted electricity utilization quantity; determining a to-be-adjusted electricity purchasing time period based on the electricity purchasing price data and the to-be-adjusted scheduling price when the predicted electricity supplementing quantity is smaller than the predicted electricity consumption; determining the maximum charging electric quantity based on the charging power limiting condition; adjusting the to-be-adjusted scheduling price until the predicted electricity supplement amount, the maximum charging electricity amount and the predicted electricity consumption meet a preset balance condition, and obtaining a target scheduling price; determining a target electricity purchase time period based on the electricity purchase price data and the target scheduling price; and in the target electricity purchasing time period, taking electricity from the power grid to supply power to the energy storage equipment and / or the load. The method can realize reasonable planning of power supply of the power grid.

Description

Technical Field

[0001] The present application relates to the technical field of energy storage, and particularly relates to an energy scheduling method, an energy storage system, and a storage medium. Background Art

[0002] In the field of energy storage, in order to balance the grid load or achieve power market transactions, a household energy storage system can sell the surplus power generated by a power generation device to the grid during high electricity price periods, and draw power from the grid to charge the energy storage device during low electricity price periods.

[0003] However, limited by factors such as the power generation amount of the power generation device, household power consumption, and electricity price fluctuations, existing energy scheduling schemes are difficult to reasonably plan the power purchase time and power purchase quantity from the grid, thereby affecting the achievement of better economic benefits for household electricity use. Summary of the Invention

[0004] The present application provides an energy scheduling method, an energy storage system, and a storage medium to solve the technical problem of being difficult to reasonably plan the power supply situation of the grid.

[0005] In a first aspect of an embodiment of the present application, an energy scheduling method is provided, which is applied to a controller in an energy storage system. The energy storage system includes a photovoltaic power generation component and an energy storage device, and the energy storage system is further configured to be connected to a grid and a load; the method includes: obtaining prediction data of the power generation power of the photovoltaic power generation component, prediction data of the power consumption power of the load, and power purchase price data; calculating a predicted supplementary power amount and a predicted power consumption amount based on the prediction data of the power generation power and the prediction data of the power consumption power; the predicted supplementary power amount is the power amount supplemented by the photovoltaic power generation component to the energy storage device when the power generation power is greater than the power consumption power; the predicted power consumption amount is the power amount provided by the energy storage device and / or the grid to the load when the power consumption power is greater than the power generation power; when the predicted supplementary power amount is less than the predicted power consumption amount, determining a to-be-adjusted power purchase time period based on the power purchase price data and a to-be-adjusted scheduling price; determining the maximum chargeable power amount for charging the energy storage device through the grid within the to-be-adjusted power purchase time period based on the charging power limit condition of the energy storage device; adjusting the to-be-adjusted scheduling price until the predicted supplementary power amount, the maximum chargeable power amount, and the predicted power consumption amount satisfy a preset balance condition to obtain a target scheduling price; determining a target power purchase time period based on the power purchase price data and the target scheduling price; and drawing power from the grid to supply power to the energy storage device and / or the load during the target power purchase time period.

[0006] When the predicted supplementary power in the embodiment of the present application is less than the predicted power consumption, the maximum charging power of the energy storage device by the power grid during the to-be-regulated power purchase time period can be determined through the charging power limit condition of the energy storage device. Furthermore, by adjusting the to-be-regulated scheduling price, the predicted supplementary power, the maximum charging power, and the predicted power consumption meet the preset balance condition, improving the rationality of the target scheduling price and the target power purchase time period. Furthermore, on the basis of meeting the user's power consumption demand, the quantity and price of power purchased from the power grid are reduced, thereby improving the overall economic efficiency.

[0007] The second aspect of the embodiment of the present application provides an energy scheduling device, which runs on a controller in an energy storage system. The energy storage system includes a photovoltaic power generation component and an energy storage device, and the energy storage system is also used to be connected to a power grid and a load; the device includes: an acquisition unit, configured to acquire prediction data of the power generation power of the photovoltaic power generation component, prediction data of the power consumption power of the load, and power purchase price data; a calculation unit, configured to calculate a predicted supplementary power and a predicted power consumption based on the prediction data of the power generation power and the prediction data of the power consumption power; the predicted supplementary power is the power supplemented by the photovoltaic power generation component to the energy storage device when the power generation power is greater than the power consumption power; the predicted power consumption is the power provided by the energy storage device and / or the power grid to the load when the power consumption power is greater than the power generation power; a determination unit, configured to determine a to-be-regulated power purchase time period based on the power purchase price data and the to-be-regulated scheduling price when the predicted supplementary power is less than the predicted power consumption; the determination unit is further configured to determine the maximum charging power of the energy storage device charged by the power grid during the to-be-regulated power purchase time period based on the charging power limit condition of the energy storage device; an adjustment unit, configured to adjust the to-be-regulated scheduling price until the predicted supplementary power, the maximum charging power, and the predicted power consumption meet the preset balance condition to obtain a target scheduling price; the determination unit is further configured to determine a target power purchase time period based on the power purchase price data and the target scheduling price; a control unit, configured to draw power from the power grid to supply power to the energy storage device and / or the load during the target power purchase time period.

[0008] The third aspect of the embodiment of the present application provides an energy storage system, which includes: a photovoltaic power generation component, an energy storage device, a controller, and a memory; the energy storage system is also used to be connected to a power grid and a load; the memory is used to store program instructions; and the controller is configured to read and execute the program instructions stored in the memory. When the program instructions are executed by the controller, the energy storage system executes the energy scheduling method described in the first aspect.

[0009] A fourth aspect of the embodiments of the present application provides a computer-readable storage medium storing program instructions, which, when running on a controller in an energy storage system, cause the energy storage system to execute the energy scheduling method described in the first aspect. Description of the Drawings

[0010] Figure 1 is a schematic structural diagram of an energy storage system provided by an embodiment of the present application.

[0011] Figure 2 is a schematic flowchart of an energy scheduling method provided by an embodiment of the present application.

[0012] Figure 3 is a schematic diagram of a time-price curve and a time-power curve provided by an embodiment of the present application.

[0013] Figure 4 is another schematic diagram of a time-price curve and a time-power curve provided by an embodiment of the present application.

[0014] Figure 5 is a schematic flowchart of another energy scheduling method provided by an embodiment of the present application.

[0015] Figure 6 is another schematic diagram of a time-price curve and a time-power curve provided by an embodiment of the present application.

[0016] Figure 7 is a schematic flowchart of another energy scheduling method provided by an embodiment of the present application.

[0017] Figure 8 is another schematic diagram of a time-price curve and a time-power curve provided by an embodiment of the present application.

[0018] Figure 9 is another schematic diagram of a time-price curve and a time-power curve provided by an embodiment of the present application.

[0019] Figure 10 is a schematic block diagram of an energy scheduling device provided by an embodiment of the present application.

[0020] Figure 11 is another schematic structural diagram of an energy storage system provided by an embodiment of the present application. Detailed Embodiments

[0021] To make the objectives, technical solutions and advantages of this application more clear, the following will, with reference to the accompanying drawings in this application, clearly and completely describe the technical solutions in this application. Apparently, the described embodiments are some, but not all, of the embodiments of this application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in this application without creative efforts shall fall within the scope of protection of this application.

[0022] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor devices and / or microcontroller devices.

[0023] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all the content and operations / steps, nor do they necessarily need to be executed in the described order. For example, some operations / steps can be decomposed, while some operations / steps can be combined or partially combined. Therefore, the actual execution order may change according to the actual situation.

[0024] It should be noted that "at least one" in this application means one or more, and "a plurality" means two or more than two. "And / or" describes the association relationship of associated objects and indicates that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone, where A and B can be singular or plural. The terms "first", "second", "third", "fourth", etc. (if any) in the description, claims and drawings of this application are used to distinguish similar objects and not to describe a specific order or sequence.

[0025] In the embodiments of this application, words such as "exemplary" or "for example" are used to represent examples, illustrations or explanations. Any embodiment or design solution described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Rather, the use of words such as "exemplary" or "for example" is intended to present relevant concepts in a specific manner.

[0026] As Figure 1As shown, it is a schematic structural diagram of an energy storage system provided by an embodiment of the present application. The energy storage system 100 includes a photovoltaic power generation component 110, an energy storage device 120, and a power conversion device 130. Among them, the output end of the energy storage device 120 is connected to the first DC end of the power conversion device 130, and the output end of the photovoltaic power generation component 110 is connected to the second DC end of the power conversion device 130. In some embodiments, both the first DC end and the second DC end of the power conversion device 130 are connected to a DC bus (including a positive DC bus DC_BUS+ and a negative DC bus DC_BUS-). The AC end of the power conversion device 130 is connected to the power grid 200 through an AC bus (including a neutral line N and a live line L), and the AC bus is also connected to a load 300. The energy storage system 100 further includes a controller ( Figure 1 not shown in the figure) and a memory ( Figure 1 not shown in the figure).

[0027] The photovoltaic power generation component 110 may include a plurality of photovoltaic panels. The photovoltaic panels can convert light energy into electrical energy, and thus output direct current to the energy storage device 120, or, after being converted by the power conversion device 130, transmit it to the power grid 200. It can be understood that the present application does not limit the connection manner of the photovoltaic panels in the photovoltaic power generation component 110. For example, in some embodiments, the photovoltaic panels in the photovoltaic power generation component 110 may be connected in series, in parallel, or first in series and then in parallel, etc.

[0028] One or more series-connected and / or parallel-connected battery cells are provided in the energy storage device 120. The energy storage device 120 can have functions of storing electricity and discharging electricity. In some embodiments, the energy storage device 120 may also have a power conversion function, such as a function of converting alternating current and direct current.

[0029] In some embodiments, the power conversion device 130 may include a direct current to alternating current (DC / AC) conversion unit, which can convert the direct current output by the photovoltaic power generation component 110 and / or the energy storage device 120 obtained from the DC bus through the DC end into alternating current, and output it to the AC bus to supply power to the load 300 and / or feed it to the power grid 200. It can be understood that the present application does not limit the specific circuit structure of the DC / AC conversion unit. For example, the DC / AC conversion unit may be a full-bridge topology, a half-bridge topology, etc.

[0030] In some other embodiments, the power conversion device 130 may include an alternating current to direct current (AC / DC) conversion unit, which can convert the alternating current obtained from the power grid into direct current and output it to the DC bus to charge the energy storage device 120. Understandably, the present application does not limit the specific circuit structure of the AC / DC conversion unit. For example, the AC / DC conversion unit may be a full-bridge topology, a half-bridge topology, etc.

[0031] In some other embodiments, the power conversion device 130 may be a bidirectional power conversion device. Thus, when the power conversion device 130 is in the inverter mode, it is used to convert the direct current received at the DC end into alternating current and output it through the AC end to at least supply power to the load 300 and / or feed power to the power grid 200. When the power conversion device 130 is in the rectifier mode, it is used to convert the alternating current received at the AC end into direct current and output it through the DC end to the DC bus to at least charge the energy storage device 120.

[0032] In some embodiments, the power conversion device 130 may include a rectifier circuit and an inverter circuit. By controlling the switching logic and duty cycle of the rectifier circuit and the inverter circuit, the mode switching between the rectifier mode and the inverter mode of the power conversion device 130 and the control of the output voltage are realized. In some other embodiments, the power conversion device 130 may also select an existing bidirectional DC / AC conversion circuit to realize the mode switching between the rectifier mode and the inverter mode of the power conversion device 130 and the control of the output voltage. The specific circuit topology of the power conversion device 130 is not limited here.

[0033] The power grid 200 may be a mains power grid. Understandably, the present application does not limit the type of alternating current of the power grid 200. In other embodiments, the power grid 200 may provide single-phase alternating current, three-phase alternating current or other polyphase alternating currents, etc.

[0034] The load 300 may be various electrical loads in a household or loads in other scenarios. For example, the load 300 may be self-mobile devices such as automotive equipment, lawn mowing equipment, floor cleaning equipment, etc., or household electrical equipment such as refrigerators, washing machines, air conditioners, induction cookers, etc.

[0035] As Figure 2 shown, it is a schematic flow chart of an energy scheduling method provided by an embodiment of the present application. The energy scheduling method can be applied to a controller (such as Figure 11 the controller 140 shown) in the energy storage system 100. As Figure 2As shown, the energy scheduling method may include the following steps S201 - S207. According to different requirements, the order of the steps in this flowchart may be changed, and some steps may be omitted.

[0036] S201, obtain the predicted data of the power generation power of the photovoltaic power generation components, the predicted data of the power consumption power of the load, and the power purchase price data.

[0037] In some embodiments, the controller may obtain the historical data of the power generation power of the photovoltaic power generation components 110 within a certain historical period, process the historical data, and obtain the predicted data of the power generation power of the photovoltaic power generation equipment 110. In some other embodiments, the controller may also directly receive the predicted data of the power generation power of the photovoltaic power generation equipment 110 sent by other devices. In some other embodiments, the controller may also obtain the predicted data of the power generation power of the photovoltaic power generation equipment 110 by other means, and the present application does not limit this.

[0038] Similarly, in some embodiments, the controller may obtain the power consumption situation of the load 300 within a certain historical period, process the historical power consumption situation, and obtain the predicted data of the power consumption power of the load 300. In some other embodiments, the controller may also directly receive the predicted data of the power consumption power of the load 300 sent by other devices. In some other embodiments, the controller may also obtain the predicted data of the power consumption power of the load 300 by other means, and the present application does not limit this.

[0039] The power purchase price data may include the power purchase prices corresponding to different time points / time periods. The power purchase prices corresponding to different time points / time periods may be the same or different. For example, referring to Figure 3 the time - price curve graph shown, curve A1 may represent the change curve of the power purchase price data. Selecting four time points t1, t2, t3, and t4 from Figure 3 it can be seen that the power purchase price at time point t1 is different from the power purchase price at time point t2, the power purchase price at time point t3 is different from the power purchase price at time point t4, and the power purchase price at time point t2 is the same as the power purchase price at time point t3.

[0040] S202, based on the predicted data of the power generation power and the predicted data of the power consumption power, calculate the predicted supplementary power quantity and the predicted power consumption quantity.

[0041] In some embodiments, the predicted supplementary power quantity may be the power quantity supplemented by the photovoltaic power generation components to the energy storage device when the power generation power is greater than the power consumption power within a preset scheduling period.

[0042] The above preset scheduling period can be set according to actual requirements. For example, usually, the variation period of the electricity purchase price data is 1 day. Therefore, the preset scheduling period can also be set to 1 day. In other scenarios, the preset scheduling period can also be set to 2 days, 5 days, 1 week, 2 weeks, etc., and the present application does not limit this.

[0043] In some embodiments, the controller calculates a predicted charge-up amount based on the predicted power generation data and the predicted power consumption data, including: The controller determines a charge-up time period based on the predicted power generation data and the predicted power consumption data, and the charge-up time period is the time period when the power generation is greater than the power consumption. The controller calculates the difference power between the power generation and the power consumption within the charge-up time period, performs a clipping process on the difference power based on the charging power limit condition of the energy storage device, and obtains the charge-up power. The controller integrates the charge-up power within the charge-up time period to obtain the predicted charge-up amount.

[0044] Among them, the charging power limit condition may include a charging power limit value, and the charging power limit value can be set according to the circuit structures of devices / components such as the energy storage device and the DC bus. Different circuit structures correspond to different charging power limit values, and the charging power limit values corresponding to the same circuit structure at different times can also be different. The above charging power limit value can be set based on one or more of factors such as the upper limit of the charging power of the energy storage device, the upper limit of the load-bearing power of the DC bus, and the upper limit of the load-bearing power of the AC bus.

[0045] In some embodiments, when performing the clipping process on the difference power based on the charging power limit condition of the energy storage device, if the difference power is less than or equal to the charging power limit value, the difference power is determined as the charge-up power; if the difference power is greater than the charging power limit value, the charging power limit value is determined as the charge-up power.

[0046] In some other embodiments, when limiting the differential power based on the charging power limit condition of the energy storage device, it can also be to limit the power generation based on the charging power limit value. If the power generation is less than or equal to the charging power limit value, the power generation is maintained; if the power generation is greater than the charging power limit value, the power generation is limited to the charging power limit value. Since the power generation after the limiting process is less than or equal to the charging power limit value, the differential power between the power generation and the power consumption is necessarily less than or equal to the charging power limit value. For example, assuming that the above charging power limit value is determined according to the transmission capacity of the DC bus, it is possible that the power generation is greater than the charging power limit value, but the differential power is less than the charging power limit value; in this case, if the power generation is output according to the power generation, although the differential power is less than the charging power limit value, the power transmitted on the DC bus exceeds the transmission capacity of the DC bus, which may cause damage to the DC bus; therefore, in this case, the power generation can be limited based on the charging power limit value to avoid the power transmitted on the DC bus exceeding the transmission capacity of the DC bus and ensure the safe operation of the system.

[0047] For example, referring to Figure 3 the time-power curve shown, assume that curve C1 represents the change curve of the predicted data of the power generation of the photovoltaic power generation module, curve D1 represents the change curve of the predicted data of the power consumption of the load, and curve E1 represents the change curve of the charging power limit value MAX_CHG_PWR.

[0048] As Figure 3 shown, the charging period is the period when the power generation is greater than the power consumption, so the charging period can be the period [t1, t4]. During the charging period [t1, t4], since the power generation is less than the charging power limit value MAX_CHG_PWR, therefore, during the charging period [t1, t4], the differential power P_diff1 = P_pv - P_use is also less than the charging power limit value MAX_CHG_PWR, then during the charging period [t1, t4], the charging power can be the differential power P_diff1, P_diff1 = P_pv - P_use. The controller integrates the differential power P_diff1 during the charging period [t1, t4], and the predicted charging amount obtained can correspond to Figure 3 the area represented by the E_CHG region shown.

[0049] Another example, referring to Figure 4The time-power curve shown. Assume that curve C2 represents the change curve of the predicted data of the power generation power of the photovoltaic power generation module, curve D2 represents the change curve of the predicted data of the power consumption power of the load, and curve E2 represents the change curve of the charging power limit MAX_CHG_PWR. The supplementary charging time period is the time period when the power generation power is greater than the power consumption power. Then, the supplementary charging time period can be the time period [t6, t11]. The supplementary charging time period [t6, t11] can include: the time period [t6, t8], the time period [t8, t9], and the time period [t9, t11]. During the time periods [t6, t8] and [t9, t11], the differential power P_diff1 is less than the charging power limit MAX_CHG_PWR. During the time period [t8, t9], the power generation power P_pv is greater than the charging power limit MAX_CHG_PWR. At this time, the power generation power P_pv can be limited to the charging power limit MAX_CHG_PWR to make P_diff1 less than the charging power limit MAX_CHG_PWR. Therefore, during the time periods [t6, t8] and [t9, t11], the supplementary charging power can be the differential power P_diff1. During the time period [t8, t9], the supplementary charging power can be the difference P_limit between the charging power limit MAX_CHG_PWR and the power consumption power, P_limit = MAX_CHG_PWR - P_use. The controller integrates the differential power P_diff1 during the time periods [t6, t8] and [t9, t11], and integrates P_limit during the time period [t8, t9]. The predicted supplementary charge obtained can correspond to Figure 4 the area represented by the E_CHG region shown.

[0050] In this embodiment, by comparing the predicted data of the power generation power with the predicted data of the power consumption power, the supplementary charging time period when the power generation power is greater than the user power can be determined. By performing amplitude limiting processing on the calculated differential power according to the charging power limit condition of the energy storage device, it is possible to avoid the determined supplementary charging power being greater than the charging power limit of the energy storage device, thereby ensuring the service life of the energy storage device and reasonably determining the predicted supplementary charge.

[0051] In some embodiments, by performing amplitude limiting processing on the calculated differential power according to the charging power limit condition of the energy storage device, it is also possible to avoid the power generation power being greater than the transmission capacity of the DC bus or other circuits, thereby ensuring the safe operation of the energy storage system.

[0052] In some embodiments, the predicted power consumption is the power provided by the energy storage device and / or the power grid to the load when the power consumption power is greater than the power generation power within a preset scheduling period.

[0053] In some embodiments, the controller calculates the predicted power consumption based on the predicted data of the power generation power and the predicted data of the power consumption power, including: The controller determines the power consumption time period based on the predicted data of the power generation power and the predicted data of the power consumption power, and the power consumption time period is the time period when the power consumption power is greater than the power generation power. The controller calculates the difference power between the power consumption power and the power generation power within the power consumption time period, and integrates the difference power within the power consumption time period to obtain the predicted power consumption.

[0054] For example, referring to Figure 3 the time-power curve shown in the figure, assume that curve C1 represents the change curve of the predicted data of the power generation power of the photovoltaic power generation module, and curve D1 represents the change curve of the predicted data of the power consumption power of the load. The power consumption time period is the time period when the power consumption power is greater than the power generation power. Taking 0 o'clock as the starting time, the power consumption time period may include the time period (0 o'clock, t1] and the time period [t4, 24 o'clock). The power consumption power may be the difference power P_diff2 between the power consumption power and the power generation power, P_diff2 = P_use - P_pv. The controller integrates the difference power P_diff2 within the time period (0 o'clock, t1] and the time period [t4, 24 o'clock), and the predicted power consumption obtained can correspond to Figure 3 the area represented by the E_GAP region shown in the figure.

[0055] Another example, referring to Figure 4 the time-power curve shown in the figure, assume that curve C2 may represent the change curve of the predicted data of the power generation power of the photovoltaic power generation module, and curve D2 may represent the change curve of the predicted data of the power consumption power of the load. The power consumption time period is the time period when the power consumption power is greater than the power generation power, then the power consumption time period may include the time period (0 o'clock, t6] and the time period [t11, 24 o'clock). The controller integrates the difference power P_diff2 within the time period (0 o'clock, t6] and the time period [t11, 24 o'clock), and the predicted power consumption obtained can correspond to Figure 4 the area represented by the E_GAP region shown in the figure.

[0056] In this embodiment, by comparing the predicted data of the power consumption power with the predicted data of the power generation power, the time period when the power consumption power is greater than the power generation power can be determined. Furthermore, by integrating the difference power between the power consumption power and the power generation power within the power consumption time period, the predicted power consumption can be accurately determined.

[0057] In some embodiments, the controller may use an integrator to integrate the power replenishment power within the power replenishment time period to obtain the predicted power replenishment amount. The controller may also use an integrator to integrate the power consumption power within the power consumption time period to obtain the predicted power consumption amount.

[0058] S203. When the predicted supplementary power is less than the predicted power consumption, determine the power purchase time period to be adjusted based on the power purchase price data and the dispatch price to be adjusted.

[0059] In some embodiments, the dispatch price to be adjusted can be adjusted between the highest price and the lowest price provided by the power purchase price data. The initial value of the dispatch price to be adjusted can be the lowest price in the power purchase price data.

[0060] Generally speaking, it is beneficial to obtain power from the power grid during low electricity price periods to achieve the best economic benefits. Therefore, the power purchase time period to be adjusted can represent the time period corresponding to when the power purchase price is less than the dispatch price to be adjusted.

[0061] For example, referring to Figure 3 the time-price curve graph shown, curve A1 can represent the change curve of the power purchase price data, and curve B1 can represent the change curve of the dispatch price to be adjusted. Since the power purchase price is less than the dispatch price to be adjusted during the time period [t2, t3], the power purchase time period to be adjusted can be determined as the time period [t2, t3].

[0062] In some embodiments, there can be multiple power purchase time periods to be adjusted. For example, referring to Figure 4 the time-price curve graph shown, curve A2 can represent the change curve of the power purchase price data, and curve B2 can represent the change curve of the dispatch price to be adjusted. Since the power purchase price is less than the dispatch price to be adjusted during the time period (0 o'clock, t5], the time period [t7, t10], and the time period [t12, 24 o'clock), the power purchase time period to be adjusted can include the time period (0 o'clock, t5], the time period [t7, t10], and the time period [t12, 24 o'clock).

[0063] S204. Based on the charging power limit condition of the energy storage device, determine the maximum charging power of the energy storage device charged by the power grid during the power purchase time period to be adjusted.

[0064] In some embodiments, the charging power of the energy storage device can include the power charged by the photovoltaic power generation module for the energy storage device and / or the power charged by the power grid for the energy storage device.

[0065] Affected by the charging power limit condition of the energy storage device and the fact that the photovoltaic power generation module charges the energy storage device simultaneously in some time periods, the maximum charging power of the power grid for the energy storage device will be limited. The maximum charging power can be understood as the maximum power that the power grid can charge the energy storage device during the time period when the power purchase price is less than the dispatch price to be adjusted.

[0066] When the power generation power is greater than the power consumption power, the photovoltaic power generation components charge the energy storage device. If the charging power limit value in the charging power limit condition is greater than the power generation power, the power grid can charge the energy storage device; if the charging power limit value is less than the power generation power, the power grid will not charge the energy storage device.

[0067] When the power generation power is less than the power consumption power, the power grid can charge the energy storage device on the premise of meeting the power consumption demand of the load.

[0068] In some embodiments, a time period in which the power generation power is greater than the power consumption power and the charging power limit value is greater than the power generation power is determined from the to-be-adjusted power purchase time period as the first charging time period, and a time period in which the power generation power is less than the power consumption power is determined from the to-be-adjusted power purchase time period as the second charging time period. The maximum charging power can be determined based on the following formula: E_AC_CHG = ∫ TA (MAX_CHG_PWR - P_pv)*dt + ∫ TB (MAX_CHG_PWR - P_use)*dt. Wherein, E_AC_CHG can represent the maximum charging power, MAX_CHG_PWR can represent the charging power limit value in the charging power limit condition, P_pv can represent the predicted data of the power generation power, P_use can represent the predicted data of the power consumption power, TA can represent the first charging time period, and TB can represent the second charging time period.

[0069] For example, please refer to Figure 3 , curve A1 can represent the change curve of the power purchase price data, curve B1 can represent the change curve of the to-be-adjusted dispatching price, curve C1 can represent the change curve of the predicted data of the power generation power of the photovoltaic power generation components, and curve D1 can represent the change curve of the predicted data of the power consumption power of the load. Figure 3 Curve E1 is also shown, and curve E1 represents the change curve of the charging power limit value MAX_CHG_PWR in the charging power limit condition. The to-be-adjusted power purchase time period can include the time period [t2, t3]. During the time period [t2, t3], the power generation power is greater than the power consumption power, and the charging power limit value MAX_CHG_PWR is greater than the power generation power P_pv, then the first charging time period can be the time period [t2, t3]. The controller calculates the difference between the charging power limit value and the power generation power to obtain the maximum charging power (MAX_CHG_PWR - P_pv) for charging the energy storage device through the power grid, and integrates the maximum charging power (MAX_CHG_PWR - P_pv) during the charging time period [t2, t3]. The obtained maximum charging power can correspond to Figure 3 the area represented by the E_AC_CHG region shown.

[0070] Another example, please refer to Figure 4, curve A2 can represent the variation curve of the electricity purchase price data, curve B2 can represent the variation curve of the adjustable scheduling price to be adjusted, curve C2 can represent the variation curve of the predicted data of the power generation power of the photovoltaic power generation module, and curve D2 can represent the variation curve of the predicted data of the power consumption power of the load. Figure 4 Curve E2 is also shown, and curve E2 represents the variation curve of the charging power limit value MAX_CHG_PWR in the charging power limit condition.

[0071] The electricity purchase time period to be adjusted may include the time period (0 o'clock, t5], the time period [t7, t10], and the time period [t12, 24 o'clock).

[0072] Determine the time period in the electricity purchase time period to be adjusted where the power generation power is greater than the power consumption power and the charging power limit value is greater than the power generation power as the first charging time period. The first charging time period may include the time period [t7, t8] and the time period [t9, t10].

[0073] Determine the time period in the electricity purchase time period to be adjusted where the power generation power is less than the power consumption power as the second charging time period. The second charging time period may include the time period (0 o'clock, t5] and the time period [t12, 24 o'clock).

[0074] Based on the determination formula of the maximum charging amount, the integral processing of (MAX_CHG_PWR - P_pv) within the first charging time period and the integral processing of (MAX_CHG_PWR - P_use) within the second charging time period can be performed to obtain the maximum charging amount, which corresponds to the sum of the areas represented by the E_AC_CHG region shown. Figure 4 The area represented by the E_AC_CHG region shown corresponds to the sum.

[0075] In this embodiment, through the charging power limit condition of the energy storage device, the maximum charging amount of the power grid charging the energy storage device can be controlled, avoiding affecting the life of the energy storage device due to too high charging power, and also avoiding the power transmitted on the line exceeding the carrying capacity of the corresponding line, thereby improving the stability of the energy storage system.

[0076] S205. Adjust the adjustable scheduling price until the predicted supplementary power amount, the maximum charging amount, and the predicted power consumption amount meet the preset balance condition to obtain the target scheduling price.

[0077] In some embodiments, the preset balance condition may indicate that the sum of the predicted recharge amount and the maximum charging amount is equal to the predicted power consumption. To reduce the oscillatory adjustment of the target scheduling price, the preset balance condition may also indicate that the absolute value of the difference between the sum of the predicted recharge amount and the maximum charging amount and the predicted power consumption is less than a preset power difference, that is, when the deviation between the sum of the predicted recharge amount and the maximum charging amount and the predicted power consumption is within a certain range, it can be regarded as the sum of the predicted recharge amount and the maximum charging amount being equal to the predicted power consumption. The preset power difference can be determined according to the product of a preset ratio and the predicted power consumption, and the preset power difference can also be determined according to the product of the preset ratio and the total power amount. The preset ratio can be adjusted according to requirements. For example, the preset ratio can be set to 5%.

[0078] In some embodiments, the controller adjusts the scheduling price to be adjusted, including: the controller determines the adjustment direction of the scheduling price to be adjusted based on the predicted recharge amount, the maximum charging amount, and the predicted power consumption. Among them, the adjustment direction may include, but is not limited to: increasing the scheduling price to be adjusted, decreasing the scheduling price to be adjusted, etc.

[0079] In some embodiments, the controller determines the adjustment direction of the scheduling price to be adjusted based on the predicted recharge amount, the maximum charging amount, and the predicted power consumption, including: when the sum of the predicted recharge amount and the maximum charging amount is less than the predicted power consumption, the controller determines that the adjustment direction is to increase the scheduling price to be adjusted. When the sum of the predicted recharge amount and the maximum charging amount is greater than the predicted power consumption, the controller determines that the adjustment direction is to decrease the scheduling price to be adjusted.

[0080] In this embodiment, by the predicted recharge amount, the maximum charging amount, and the predicted power consumption, the adjustment direction of the scheduling price to be adjusted can be determined, thereby improving the adjustment efficiency of the scheduling price to be adjusted.

[0081] In some embodiments, when it is determined to increase the scheduling price to be adjusted, the controller updates the lower boundary price based on the scheduling price to be adjusted, and updates the scheduling price to be adjusted based on the average value of the scheduling price to be adjusted and the upper boundary price.

[0082] Among them, the initial value of the lower boundary price can be the lowest price in the power purchase price data, and the initial value of the upper boundary price can be the highest price in the power purchase price data. There are no restrictions on this setting in practical applications.

[0083] For example, assume that the highest price R_MAX in the electricity purchase price data = 5 EUR (EUR, euro, and the specific price unit can be set according to the corresponding country / region in practice), and the lowest price R_MIN in the electricity purchase price data = 1 EUR. Initially, the lowest price R_MIN in the electricity purchase price data (e.g., 1 EUR) is used as the initial value of the lower boundary price, and the highest price R_MAX in the electricity purchase price data (e.g., 5 EUR) is used as the initial value of the upper boundary price. If the scheduling price to be adjusted R_BORD_old = 2 EUR and the adjustment direction is to increase the scheduling price to be adjusted, the updated lower boundary price is the scheduling price to be adjusted 2 EUR, and the updated scheduling price to be adjusted R_BORD_new = (R_BORD_old + R_MAX) / 2 = (2 EUR + 5 EUR) / 2 = 3.5 EUR.

[0084] In some other embodiments, when determining to decrease the scheduling price to be adjusted, the upper boundary price is updated based on the scheduling price to be adjusted, and the scheduling price to be adjusted is updated based on the average value of the scheduling price to be adjusted and the lower boundary price. For example, assume that the highest price R_MAX in the electricity purchase price data = 5 EUR and the lowest price R_MIN in the electricity purchase price data = 1 EUR. Initially, the lowest price R_MIN (1 EUR) in the electricity purchase price data is used as the initial value of the lower boundary price, and the highest price R_MAX (5 EUR) in the electricity purchase price data is used as the initial value of the upper boundary price. If the scheduling price to be adjusted R_BORD_old = 2 EUR and the adjustment direction is to decrease the scheduling price to be adjusted, the updated upper boundary price is the scheduling price to be adjusted 2 EUR, and the updated scheduling price to be adjusted R_BORD_new = (R_BORD_old + R_MIN) / 2 = (2 EUR + 1 EUR) / 2 = 1.5 EUR.

[0085] In this embodiment, by updating the scheduling price to be adjusted through the upper boundary price or the lower boundary price in the electricity purchase price data, the update efficiency of the scheduling price to be adjusted can be improved.

[0086] In some other embodiments, the controller adjusts the scheduling price to be adjusted, including: the controller calculates the deviation value between the total charging power and the predicted power consumption, and the total charging power is the sum of the predicted supplementary power and the maximum charging power. The controller calculates the ratio of the deviation value to the reference power, and calculates the price adjustment value based on the ratio, the price deviation value, and a preset coefficient. The reference power can be the larger value of the total charging power and the predicted power consumption, and the price deviation value can be the difference between the highest price and the lowest price in the electricity purchase price data. The controller updates the scheduling price to be adjusted based on the price adjustment value.

[0087] Among them, the preset coefficient is used to prevent the oscillation overshoot of the scheduling price to be adjusted. Calculate the sum of the price adjustment value and the scheduling price to be adjusted to obtain the updated scheduling price to be adjusted.

[0088] For example, assume that the sum of the predicted supplementary power and the maximum charging power is: E_chg+E_AC_CHG = 2 kwh, the predicted power consumption is: E_gap = 10 kwh, the highest price in the power purchase price data is: R_MAX = 5 EUR, the lowest price in the power purchase price data is: R_MIN = 1 EUR, and the scheduling price to be adjusted is: R_BORD_old = 2 EUR. Then the total charging power is: E_chg+E_AC_CHG = 2 kwh, the deviation value between the total charging power of 2 kwh and the predicted power consumption E_gap is: -8 kwh, the reference power is: 10 kwh (the reference power is the larger value of the total charging power and the predicted power consumption), the ratio of the deviation value to the reference power is -4 / 5, the price deviation value is: R_MAX–R_MIN = 4 EUR, the preset coefficient is k, the price adjustment value is -4 / 5*4*k = -16k / 5, and if the updated scheduling price to be adjusted is: R_BORD_new = R_BORD_old+(-16k / 5).

[0089] In this embodiment, by combining the predicted supplementary power, the predicted power consumption, the maximum charging power, and the highest price and the lowest price in the power purchase price data to update the scheduling price to be adjusted, it can ensure that the updated scheduling price to be adjusted conforms to the optimal scheduling result, thereby improving the rationality of the update of the scheduling price to be adjusted.

[0090] S206. Based on the power purchase price data and the target scheduling price, determine the target power purchase time period.

[0091] In some embodiments, the target power purchase time period may represent the time period when the power purchase price is less than the target scheduling price. For example Figure 3 As shown in the time-price curve graph, curve A1 represents the change curve of the power purchase price data. If curve B1 represents the change curve of the target scheduling price, then the target power purchase time period can be determined as the time period [t2, t3]. Another example Figure 4 As shown in the time-price curve graph, curve A2 may represent the change curve of the power purchase price data. If curve B2 represents the change curve of the target scheduling price, then the target power purchase time period may include: the time period (0 o'clock, t5], the time period [t7, t10], and the time period [t12, 24 o'clock).

[0092] S207. During the target power purchase time period, draw power from the power grid to supply power to the energy storage device and / or the load.

[0093] Using the above energy scheduling method, when the predicted supplementary power is less than the predicted power consumption in the embodiments of the present application, the maximum charging power of the energy storage device can be determined by the charging power limit condition of the energy storage device during the to-be-adjusted power purchase time period. Furthermore, by adjusting the to-be-adjusted scheduling price, the predicted supplementary power, the maximum charging power, and the predicted power consumption meet the preset balance condition, improving the rationality of the target scheduling price and the target power purchase time period. Furthermore, on the basis of meeting the user's power consumption demand, the quantity and price of power purchased from the power grid are reduced, thereby improving the overall economic benefit.

[0094] As Figure 5 shown, it is a schematic flowchart of another energy scheduling method provided by the embodiments of the present application. The energy scheduling method is applied to the controller of the energy storage system 100 (such as Figure 11 the controller 140 shown). As Figure 5 shown, the energy scheduling method may include the following steps S501-S507. According to different requirements, the order of the steps in this flowchart can be changed, and some can be omitted.

[0095] S501, Obtain the predicted data of the power generation power of the photovoltaic power generation component, the predicted data of the power consumption power of the load, and the power purchase price data.

[0096] S502, Based on the predicted data of the power generation power and the predicted data of the power consumption power, calculate the predicted supplementary power and the predicted power consumption.

[0097] For the detailed content of steps S501-S502, reference can be made to the detailed description of steps S201-S202 above Figure 2 and will not be repeated here.

[0098] S503, When the predicted supplementary power is less than the predicted power consumption and the battery capacity of the energy storage device is less than the predicted power consumption, determine the first to-be-adjusted power purchase time period based on the power purchase price data and the first to-be-adjusted scheduling price, and determine the second to-be-adjusted power purchase time period based on the power purchase price data and the second to-be-adjusted scheduling price.

[0099] In some embodiments, when the battery capacity of the energy storage device is less than the predicted power consumption, the energy storage device cannot store enough energy through one energy scheduling. For this reason, multiple to-be-adjusted scheduling prices can be set in the above Figure 2 to balance the consumption of the predicted power consumption through multiple energy schedulings. This embodiment takes the to-be-adjusted scheduling price including the first to-be-adjusted scheduling price and the second to-be-adjusted scheduling price as an example for illustration, and the actual solution is not limited to this.

[0100] In some embodiments, the first electricity purchase time period to be adjusted may represent a time period during which the electricity purchase price is less than the first adjusted dispatching price, and the second electricity purchase time period to be adjusted may represent a time period during which the electricity purchase price is less than the second adjusted dispatching price. For example, please refer to Figure 6 the time-price curve graph shown. Assume that curve A3 may represent the change curve of the electricity purchase price data, curve B3 may represent the change curve of the first adjusted dispatching price, and curve B4 may represent the change curve of the second adjusted dispatching price. During time period T1, the electricity purchase price is less than the first adjusted dispatching price. Therefore, the first electricity purchase time period to be adjusted includes: time period T1; during time period T3, the electricity purchase price is less than the second adjusted dispatching price. Therefore, the second electricity purchase time period to be adjusted includes: time period T3.

[0101] In some embodiments, the predicted electricity consumption includes the first electricity consumption corresponding to the first electricity consumption time period and the second electricity consumption corresponding to the second electricity consumption time period. In some embodiments, the first electricity consumption time period may represent the time from the first time point to the second time point when the power generation power is balanced with the power consumption power, and the second electricity consumption time period may represent the time from the third time point when the power generation power is balanced with the power consumption power to the fourth time point, where the first time point and the fourth time point can be set according to actual needs. For example, the first time point can be set to 0 o'clock, and the fourth time point can be set to 24 o'clock. The balance between the power generation power and the power consumption power may mean that the power generation power is equal to the power consumption power, and the balance between the power generation power and the power consumption power may also mean that the difference between the power generation power and the power consumption power is less than a preset threshold. In some other embodiments, the first electricity consumption time period and the second electricity consumption time period can also be fixedly set. For example, the first electricity consumption time period can be set to [0 o'clock, 12 o'clock), and the second electricity consumption time period can be set to [12 o'clock, 24 o'clock).

[0102] S504. Based on the charging power limit condition of the energy storage device, determine the first maximum charging amount for charging the energy storage device through the power grid during the first electricity purchase time period to be adjusted, and determine the second maximum charging amount for charging the energy storage device through the power grid during the second electricity purchase time period to be adjusted.

[0103] In some embodiments, the determination method of the first maximum charging amount and the determination method of the second maximum charging amount are similar to the determination method of the maximum charging amount described above Figure 2 and will not be described repeatedly here.

[0104] For example, please refer to Figure 6 . Curve C3 may represent the change curve of the predicted data of the power generation power of the photovoltaic power generation module, curve D3 may represent the change curve of the predicted data of the power consumption power of the load, and curve E3 may represent the change curve of the charging power limit value MAX_CHG_PWR in the charging power limit condition.

[0105] As shown Figure 6 in the figure, the first power purchase time period to be adjusted includes the time period T1, and the time period T1 may include the time period T11, the time period T12, and the time period T13. Determine the time periods T11 and T13 in the first power purchase time period to be adjusted, where the power generation power is greater than the power consumption power and the charging power limit is greater than the power generation power. Based on the maximum charging power determination formula described above Figure 2 , the controller can perform integral calculation on (MAX_CHG_PWR - P_pv) within the time periods T11 and T13 to obtain the first maximum charging power. The first maximum charging power can correspond to the sum of the areas represented by the E_AC_CHG1 region shown Figure 6 in the figure.

[0106] The second power purchase time period to be adjusted includes the time period T3, within which the power generation power is less than the power consumption power. Based on the maximum charging power determination formula described above Figure 2 , integral processing can be performed on (MAX_CHG_PWR - P_use) within the time period T3 to obtain the second maximum charging power. The second maximum charging power can correspond to the area represented by the E_AC_CHG2 region shown Figure 6 in the figure.

[0107] S505, adjust the first power purchase scheduling price to be adjusted until the predicted supplementary power, the first maximum charging power, and the first power consumption meet the preset balance condition, and obtain the first target scheduling price.

[0108] In some embodiments, the adjustment method of the first power purchase scheduling price to be adjusted is similar to the adjustment method of the power purchase scheduling price to be adjusted described above Figure 2 , and will not be described in detail here.

[0109] S506, adjust the second power purchase scheduling price to be adjusted until the second maximum charging power and the second power consumption meet the preset balance condition, and obtain the second target scheduling price.

[0110] In some embodiments, the second maximum charging power and the second power consumption meeting the preset balance condition may mean that the second maximum charging power is equal to the second power consumption, or may also mean that the difference between the second maximum charging power and the second power consumption is less than the preset power, and the preset power can be set according to requirements. The adjustment method of the second power purchase scheduling price to be adjusted is similar to the adjustment method of the power purchase scheduling price to be adjusted described above Figure 2 , and will not be described in detail here.

[0111] S507, determine the first target power purchase time period based on the power purchase price data and the first target scheduling price, and determine the second target power purchase time period based on the power purchase price data and the second target scheduling price.

[0112] In some embodiments, the method for determining the first target power purchase time period and the method for determining the second target power purchase time period are similar to the method for determining the target power purchase time period described above Figure 2 and will not be described again here.

[0113] Using the above energy scheduling method, in the embodiments of the present application, when the battery capacity of the energy storage device is less than the predicted power consumption, by controlling the balance of the predicted supplementary power, the first maximum charging power and the first power consumption, and the balance of the second maximum charging power and the second power consumption, the first target scheduling price and the second target scheduling price can be reasonably determined, thereby improving the rationality of the first target power purchase time period and the second target power purchase time period.

[0114] As Figure 7 shown, it is a schematic flowchart of another energy scheduling method provided by the embodiments of the present application. The energy scheduling method is applied to the controller of the energy storage system 100 (such as Figure 11 the controller 140 shown). As Figure 7 shown, the energy scheduling method may include the following steps S701 - S708. According to different requirements, the order of the steps in this flowchart may be changed, and some may be omitted.

[0115] S701, Obtain the predicted data of the power generation power of the photovoltaic power generation module, the predicted data of the power consumption power of the load, and the power purchase price data.

[0116] S702, Based on the predicted data of the power generation power and the predicted data of the power consumption power, calculate the predicted supplementary power and the predicted power consumption.

[0117] S703, When the predicted supplementary power is less than the predicted power consumption, determine the to - be - adjusted power purchase time period based on the power purchase price data and the to - be - adjusted scheduling price.

[0118] S704, Based on the charging power limit condition of the energy storage device, determine the maximum charging power for charging the energy storage device through the power grid during the to - be - adjusted power purchase time period.

[0119] For the detailed content of steps S701 - S704, reference can be made to the detailed description of steps S201 - S204 above Figure 2 and will not be described again here.

[0120] S705, Obtain the power selling price data.

[0121] In some embodiments, the power selling price data may include the power selling prices corresponding to different time points. The power selling prices corresponding to different time points may be the same or different. For example Figure 8 as shown in the time - price curve graph, curve A5 can represent the change curve of the power selling price data.

[0122] S706. Determine the electricity selling time period to be adjusted based on the electricity selling price data and the dispatching price to be adjusted.

[0123] In some embodiments, the electricity selling time period to be adjusted may represent the time period corresponding to when the electricity selling price is greater than the dispatching price to be adjusted. For example, referring to Figure 8 the time-price curve graph shown, curve A4 may represent the change curve of the electricity purchase price data, curve A5 may represent the change curve of the electricity selling price data, and curve B5 may represent the change curve of the dispatching price to be adjusted. During time period T5 and time period T6, the electricity selling price is greater than the dispatching price to be adjusted, so the electricity selling time period to be adjusted may include: time period T5 and time period T6.

[0124] S707. Determine the maximum discharge power of the energy storage device feeding power to the power grid during the electricity selling time period to be adjusted based on the discharge power limit condition of the energy storage device.

[0125] In some embodiments, the discharge power of the energy storage device may include: the power fed to the load and / or the power fed to the power grid. Affected by the discharge power limit condition of the energy storage device and / or the power consumption of the load, the maximum discharge power is limited. The maximum discharge power may be the maximum power fed back by the energy storage device to the power grid during the time period when the electricity selling price is greater than the dispatching price to be adjusted.

[0126] The above discharge power limit condition may include a discharge power limit value. The discharge power limit value may be set based on one or more of factors such as the upper limit of the discharge power of the energy storage device, the upper limit of the bearing power of the DC bus, and the upper limit of the bearing power of the AC bus.

[0127] In some embodiments, the maximum discharge power can be determined based on the following formula: E_AC_SOLD = ∫ TC (MAX_DSG_PWR - P_use) * dt, where E_AC_SOLD can represent the maximum discharge power, MAX_DSG_PWR can represent the discharge power limit value in the discharge power limit condition, P_use can represent the power consumption, and TC can represent the electricity selling time period to be adjusted.

[0128] For example, in combination with Figure 8 to illustrate the determination of the maximum discharge power, referring to Figure 8 shown, curve B5 may represent the change curve of the dispatching price to be adjusted, curve A5 may represent the change curve of the electricity selling price data, curve C4 may represent the change curve of the predicted power generation data, curve D4 may represent the change curve of the predicted power consumption data, curve E4 may represent the change curve of the charging power limit value MAX_CHG_PWR, and curve F1 may represent the change curve of the discharge power limit value MAX_DSG_PWR.

[0129] The adjustable power selling time period may include time period T5 and time period T6. Based on the determination formula of the maximum discharge power, the integral result of the difference power (MAX_DSG_PWR - P_use) between the discharge power limit and the power consumption on time period T5 and time period T6 can be calculated, and the obtained maximum discharge power can correspond to Figure 8 the sum of the areas represented by the E_AC_SOLD region shown.

[0130] For another example, referring to Figure 9 as shown, curve A6 may represent the change curve of the power purchase price data, curve A7 may represent the change curve of the power selling price data, curve B6 may represent the change curve of the first adjustable scheduling price, and curve B7 may represent the change curve of the second adjustable scheduling price; curve C5 may represent the change curve of the predicted data of the power generation power, curve D5 may represent the change curve of the predicted data of the power consumption power, curve E5 may represent the change curve of the charging power limit MAX_CHG_PWR, and curve F2 may represent the change curve of the discharge power limit MAX_DSG_PWR.

[0131] The adjustable power selling time period may include time period T7 and time period T8. Based on the determination formula of the maximum discharge power, the integral result of the difference power (MAX_DSG_PWR - P_use) between the discharge power limit and the power consumption on time period T7 and time period T8 can be calculated, and the obtained maximum discharge power can correspond to Figure 9 the sum of the areas represented by the E_AC_SOLD_1 and E_AC_SOLD_2 regions shown.

[0132] S708, adjust the adjustable scheduling price until the predicted power replenishment amount, the maximum charging power, the maximum discharge power, and the predicted power consumption amount meet the preset balance condition, and obtain the target scheduling price.

[0133] In some embodiments, the preset balance condition may indicate that the first power sum of the predicted power replenishment amount and the maximum charging power is equal to the second power sum of the maximum discharge power and the predicted power consumption amount. The preset balance condition may also indicate that the difference between the first power sum and the second power sum is less than a set value, and the set value can be set according to requirements. The adjustment method of the adjustable scheduling price may refer to the relevant description of step S205 above Figure 2 and will not be repeated here.

[0134] In some embodiments, the controller determines a target power purchase time period based on the power purchase price data and the target scheduling price, and during the target power purchase time period, draws power from the power grid to supply power to the energy storage device and / or the load. Among them, the target power purchase time period may be the time period corresponding to when the power purchase price is less than the target scheduling price. In this embodiment, when the power purchase price is less than the target scheduling price, power is drawn from the power grid to supply power to the energy storage device and / or the load, which can draw power from the power grid during low electricity price time periods to achieve the best economic benefits.

[0135] In some embodiments, the controller determines a target power sale time period based on the power sale price data and the target scheduling price, and during the target power sale time period, feeds power back to the power grid. Among them, the target power purchase time period may be the time period corresponding to when the power sale price is greater than the target scheduling price. For example Figure 8 As shown, if curve B5 can represent the change curve of the target scheduling price, then the target power sale time period may be the time periods T5 and T6 as shown in Figure 8 shown, and the maximum discharge power can correspond to the sum of the areas represented by the Figure 8 E_AC_SOLD region as shown. Another example is Figure 9 as shown, if curve B6 and curve B7 can respectively represent the change curves of the first target scheduling price and the second target scheduling price, then the target power sale time period may be the time periods T7 and T8 as shown in Figure 9 shown, and the power sale volume can correspond to the sum of the areas represented by the Figure 9 E_AC_SOLD_1 and E_AC_SOLD_2 regions as shown. In this embodiment, when the power sale price is greater than the target scheduling price, power is fed back to the power grid, which can feed power back to the power grid during high electricity price time periods to achieve the best economic benefits.

[0136] Through the charging power limit condition and the discharging power limit condition of the energy storage device in the embodiments of the present application, the maximum charging power of the power grid to charge the energy storage device during the to-be-adjusted power purchase time period and the maximum discharging power to feed power back to the power grid during the to-be-adjusted power sale time period can be determined. Furthermore, by adjusting the to-be-adjusted scheduling price through the maximum charging power and the maximum discharging power, the rationality of the target scheduling price is improved. Then, based on the target scheduling price, the power purchase price data and the power sale price data corresponding to different time periods, the reasonable planning of the target power purchase time period and the target power sale time period can be realized, thereby improving the overall economic benefits.

[0137] As Figure 10 shown, it is a module schematic diagram of an energy scheduling device provided by an embodiment of the present application. The energy scheduling device 101 runs on a controller in the energy storage system 100 (such as Figure 11 the controller 140 shown). The energy scheduling device 101 includes an acquisition unit 1010, a calculation unit 1011, a determination unit 1012, an adjustment unit 1013, and a control unit 1014.

[0138] An acquisition unit 1010 is configured to acquire prediction data of the power generation power of a photovoltaic power generation component, prediction data of the power consumption power of a load, and power purchase price data; a calculation unit 1011 is configured to calculate a predicted supplementary power quantity and a predicted power consumption quantity based on the prediction data of the power generation power and the prediction data of the power consumption power; the predicted supplementary power quantity is the power quantity supplemented by the photovoltaic power generation component to an energy storage device when the power generation power is greater than the power consumption power; the predicted power consumption quantity is the power quantity provided by the energy storage device and / or the power grid to the load when the power consumption power is greater than the power generation power; a determination unit 1012 is configured to determine a to-be-adjusted power purchase time period based on the power purchase price data and a to-be-adjusted scheduling price when the predicted supplementary power quantity is less than the predicted power consumption quantity; the determination unit 1012 is further configured to determine the maximum charge quantity for charging the energy storage device through the power grid during the to-be-adjusted power purchase time period based on the charging power limit condition of the energy storage device; an adjustment unit 1013 is configured to adjust the to-be-adjusted scheduling price until the predicted supplementary power quantity, the maximum charge quantity, and the predicted power consumption quantity meet a preset balance condition to obtain a target scheduling price; the determination unit 1012 is further configured to determine a target power purchase time period based on the power purchase price data and the target scheduling price; a control unit 1014 is configured to draw power from the power grid to supply power to the energy storage device and / or the load during the target power purchase time period.

[0139] In some embodiments, the adjustment unit 1013 is specifically configured to: determine the adjustment direction of the to-be-adjusted scheduling price based on the predicted supplementary power quantity, the maximum charge quantity, and the predicted power consumption quantity; when it is determined to increase the to-be-adjusted scheduling price, update the lower boundary price based on the to-be-adjusted scheduling price, and update the to-be-adjusted scheduling price based on the average value of the to-be-adjusted scheduling price and the upper boundary price; the initial value of the lower boundary price is the lowest price in the power purchase price data, and the initial value of the upper boundary price is the highest price in the power purchase price data; when it is determined to decrease the to-be-adjusted scheduling price, update the upper boundary price based on the to-be-adjusted scheduling price, and update the to-be-adjusted scheduling price based on the average value of the to-be-adjusted scheduling price and the lower boundary price.

[0140] In some embodiments, the adjustment unit 1013 is specifically configured to: calculate the deviation value between the total charge quantity and the predicted power consumption quantity; the total charge quantity is the sum of the predicted supplementary power quantity and the maximum charge quantity; calculate the ratio of the deviation value to the reference power quantity, and calculate the price adjustment value based on the ratio, the price deviation value, and a preset coefficient; the reference power quantity is the larger value of the total charge quantity and the predicted power consumption quantity, and the price deviation value is the difference between the highest price and the lowest price in the power purchase price data; update the to-be-adjusted scheduling price based on the price adjustment value.

[0141] In some embodiments, the obtaining unit 1010 is further configured to obtain electricity selling price data; determine an electricity selling time period to be adjusted based on the electricity selling price data and the scheduling price to be adjusted; the determining unit 1012 is further configured to determine the maximum discharge power of the energy storage device based on the discharge power limit condition of the energy storage device during the electricity selling time period to be adjusted. The adjusting unit 1013 is further configured to adjust the scheduling price to be adjusted until the predicted supplementary power, the maximum charge power, the maximum discharge power, and the predicted power consumption meet a preset balance condition, and obtain a target scheduling price.

[0142] In some embodiments, the determining unit 1012 is further configured to determine a target electricity selling time period based on the electricity selling price data and the target scheduling price; the control unit 1014 is further configured to feed power to the power grid during the target electricity selling time period.

[0143] In some embodiments, the battery capacity of the energy storage device is less than the predicted power consumption, and the scheduling price to be adjusted includes a first scheduling price to be adjusted and a second scheduling price to be adjusted; the predicted power consumption includes a first power consumption corresponding to a first power consumption time period and a second power consumption corresponding to a second power consumption time period; the determining unit 1012 is further configured to, when the predicted supplementary power is less than the predicted power consumption, determine a first electricity purchase time period to be adjusted based on the electricity purchase price data and the first scheduling price to be adjusted, and determine a second electricity purchase time period to be adjusted based on the electricity purchase price data and the second scheduling price to be adjusted; the determining unit 1012 is further configured to determine a first maximum charge power for charging the energy storage device through the power grid during the first electricity purchase time period to be adjusted based on the charge power limit condition of the energy storage device, and determine a second maximum charge power for charging the energy storage device through the power grid during the second electricity purchase time period to be adjusted; the adjusting unit 1013 is further configured to adjust the first scheduling price to be adjusted until the predicted supplementary power, the first maximum charge power, and the first power consumption meet a preset balance condition, and obtain a first target scheduling price; the adjusting unit 1013 is further configured to adjust the second scheduling price to be adjusted until the second maximum charge power and the second power consumption meet a preset balance condition, and obtain a second target scheduling price; the determining unit 1012 is further configured to determine a first target electricity purchase time period based on the electricity purchase price data and the first target scheduling price, and determine a second target electricity purchase time period based on the electricity purchase price data and the second target scheduling price.

[0144] In some embodiments, the calculating unit 1011 is specifically configured to: determine a supplementary power time period based on the predicted data of the power generation power and the predicted data of the power consumption power; the supplementary power time period is a time period when the power generation power is greater than the power consumption power; calculate the difference power between the power generation power and the power consumption power during the supplementary power time period; perform a clipping process on the difference power based on the charge power limit condition of the energy storage device to obtain a supplementary power; integrate the supplementary power during the supplementary power time period to obtain the predicted supplementary power.

[0145] In some embodiments, the adjustment unit 1013 is specifically configured to: when the sum of the predicted supplementary power and the maximum charging power is less than the predicted power consumption, determine that the adjustment direction is to increase the adjustable scheduling price to be adjusted; when the sum of the predicted supplementary power and the maximum charging power is greater than the predicted power consumption, determine that the adjustment direction is to decrease the adjustable scheduling price to be adjusted.

[0146] For the detailed content of the functions of each module / unit, reference may be made to the above Figure 2 、 Figure 5 and Figure 7 The detailed description will not be repeated here.

[0147] When the predicted supplementary power is less than the predicted power consumption in the embodiments of the present application, through the charging power limit condition of the energy storage device, the maximum charging power of the grid to charge the energy storage device during the adjustable power purchase time period can be determined. Furthermore, by adjusting the adjustable scheduling price with the maximum charging power, the rationality of the target scheduling price can be improved. Then, according to the target scheduling price and the power purchase price data corresponding to different time periods, a reasonable plan for the target power purchase time period can be realized, thereby improving the overall economic benefit.

[0148] As Figure 11 shown, it is another structural schematic diagram of an energy storage system provided by the embodiments of the present application.

[0149] In some embodiments, the energy storage system 100 includes, but is not limited to, a controller 140, a memory 150, and program instructions stored in the memory 150 and executable on the controller 140, such as an energy scheduling program.

[0150] Those skilled in the art can understand that the schematic diagram is only an example of the energy storage system 100, and does not constitute a limitation on the energy storage system 100. It may include more or fewer components than shown, or combine some components, or different components. For example, the energy storage system 100 may further include input / output devices, network access devices, buses, etc.

[0151] The controller 140 can be a Central Processing Unit (CPU), or it can also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc. The controller 140 is the operation core and control center of the energy storage system 100, connecting all parts of the entire energy storage system 100 through various interfaces and lines, and executing the operating system of the energy storage system 100 and various installed application programs, program codes, etc.

[0152] Exemplarily, the program instructions can be divided into one or more modules / units, and one or more modules / units are stored in the memory 150 and executed by the controller 140 to complete this application. One or more modules / units can be a series of program instruction segments capable of completing specific functions, and this program instruction segment is used to describe the execution process of the program instructions in the controller 140. For example, the program instructions can be divided into an acquisition unit 1010, a calculation unit 1011, a determination unit 1012, an adjustment unit 1013, and a control unit 1014.

[0153] The memory 150 can be used to store program instructions and / or modules. The controller 140 realizes various functions of the controller 140 by running or executing the program instructions and / or modules stored in the memory 150 and calling the data stored in the memory 150. The memory 150 mainly includes a program storage area and a data storage area. Among them, the program storage area can store the operating system, application programs required for at least one function, etc.; the data storage area can store the data created according to the use of the energy storage system. The memory 150 can include non-volatile and volatile memories, such as: hard disks, memory, plug-in hard disks, Smart Media Cards (SMCs), Secure Digital (SD) cards, FlashCards, at least one magnetic disk storage device, flash device, or other storage devices.

[0154] The memory 150 can be an external memory and / or an internal memory of the controller 140. Further, the memory 150 can be a memory in physical form, such as a memory stick, a TF card (Trans-flash Card), etc.

[0155] When the above integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, to implement all or part of the processes in the above-described embodiment methods of this application, it can also be completed by instructing relevant hardware through program instructions. The program instructions can be stored in a computer-readable storage medium. When the program instructions are executed by a processor, the steps of the above various method embodiments can be implemented.

[0156] Among them, the program instructions include program instruction codes, and the program instruction codes can be in the form of source code, object code, executable files, or some intermediate forms, etc. The computer-readable medium can include: any entity or device capable of carrying program instruction codes, recording media, USB flash drives, mobile hard disks, magnetic disks, optical disks, computer memories, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory).

[0157] Combined Figure 2 、 Figure 5 and Figure 7 , the memory 150 in the energy storage system 100 stores program instructions, and the controller 140 can execute the program instructions stored in the memory 150 to implement the energy scheduling method as shown in any of the above method embodiments.

[0158] Specifically, for the specific implementation method of the controller 140 for the above program instructions, reference can be made to the description of the relevant steps in the above method embodiments, which will not be elaborated here.

[0159] In several embodiments provided in this 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 modules is only a logical function division, and there can be other division methods in actual implementation.

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

[0161] In addition, in each functional module in the various embodiments of this application, it can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated unit can be implemented in the form of hardware, or in the form of hardware plus software functional modules.

[0162] Therefore, from any perspective, the embodiments should be regarded as exemplary and non-restrictive. The scope of this application is defined by the appended claims rather than the above description. Accordingly, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be embraced by this application. Any reference signs in the claims should not be construed as limiting the claims concerned.

[0163] In addition, it is obvious that the term "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of elements or devices may also be implemented by one element or device through software or hardware. The terms first, second, etc. are used to denote names and do not denote any particular order.

[0164] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application and not to limit them. Although this application has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of this application can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of this application.

Claims

1. An energy scheduling method, characterized in that, A controller applied to an energy storage system, the energy storage system including a photovoltaic power generation component and an energy storage device, and the energy storage system is also used to connect to a power grid and a load; the method includes: Obtain the predicted data of the power generation power of the photovoltaic power generation component, the predicted data of the power consumption power of the load, and the power purchase price data; Based on the predicted data of the power generation power and the predicted data of the power consumption power, calculate the predicted supplementary power and the predicted power consumption; the predicted supplementary power is the power supplemented by the photovoltaic power generation component to the energy storage device when the power generation power is greater than the power consumption power; the predicted power consumption is the power provided by the energy storage device and / or the power grid to the load when the power consumption power is greater than the power generation power; When the predicted supplementary power is less than the predicted power consumption, determine the to-be-adjusted power purchase time period based on the power purchase price data and the to-be-adjusted scheduling price; Based on the charging power limit condition of the energy storage device, determine the maximum charging power of charging the energy storage device through the power grid during the to-be-adjusted power purchase time period; Adjust the to-be-adjusted scheduling price until the predicted supplementary power, the maximum charging power, and the predicted power consumption meet the preset balance condition, and obtain the target scheduling price; Based on the power purchase price data and the target scheduling price, determine the target power purchase time period; During the target power purchase time period, draw power from the power grid to supply power to the energy storage device and / or the load.

2. The method according to claim 1, wherein The adjusting the to-be-adjusted scheduling price includes: Determine the adjustment direction of the to-be-adjusted scheduling price based on the predicted supplementary power, the maximum charging power, and the predicted power consumption; When it is determined to increase the to-be-adjusted scheduling price, update the lower boundary price based on the to-be-adjusted scheduling price, and update the to-be-adjusted scheduling price based on the average value of the to-be-adjusted scheduling price and the upper boundary price; the initial value of the lower boundary price is the lowest price in the power purchase price data, and the initial value of the upper boundary price is the highest price in the power purchase price data; When it is determined to decrease the to-be-adjusted scheduling price, update the upper boundary price based on the to-be-adjusted scheduling price, and update the to-be-adjusted scheduling price based on the average value of the to-be-adjusted scheduling price and the lower boundary price.

3. The method according to claim 1, wherein The adjusting the to-be-adjusted scheduling price includes: Calculate the deviation value between the total charging power and the predicted power consumption; the total charging power is the sum of the predicted supplementary power and the maximum charging power; Calculate the ratio of the deviation value to the reference power, and calculate the price adjustment value based on the ratio, the price deviation value, and a preset coefficient; the reference power is the larger value of the total charging power and the predicted power consumption, and the price deviation value is the difference between the highest price and the lowest price in the power purchase price data; Update the to-be-adjusted scheduling price based on the price adjustment value.

4. The method according to claim 1, wherein The method further includes: Obtain the power selling price data; Based on the power selling price data and the to-be-adjusted scheduling price, determine the to-be-adjusted power selling time period; Determine the maximum discharge power of the energy storage device during the to-be-regulated power selling period based on the discharge power limit condition of the energy storage device; Correspondingly, adjusting the to-be-regulated scheduling price until the predicted supplementary power, the maximum charging power, and the predicted power consumption satisfy a preset balance condition to obtain the target scheduling price includes: Adjust the to-be-regulated scheduling price until the predicted supplementary power, the maximum charging power, the maximum discharge power, and the predicted power consumption satisfy a preset balance condition to obtain the target scheduling price.

5. The method according to claim 4, wherein The method further includes: Determine the target power selling period based on the power selling price data and the target scheduling price; During the target power selling period, feed power to the power grid.

6. The method according to claim 1, wherein The battery capacity of the energy storage device is less than the predicted power consumption. The to-be-regulated scheduling price includes a first to-be-regulated scheduling price and a second to-be-regulated scheduling price; the predicted power consumption includes a first power consumption corresponding to a first power consumption period and a second power consumption corresponding to a second power consumption period; When the predicted supplementary power is less than the predicted power consumption, determine the to-be-regulated power purchase period based on the power purchase price data and the to-be-regulated scheduling price; Determine the maximum charging power of the energy storage device charged by the power grid during the to-be-regulated power purchase period based on the charging power limit condition of the energy storage device; adjust the to-be-regulated scheduling price until the predicted supplementary power, the maximum charging power, and the predicted power consumption satisfy a preset balance condition to obtain the target scheduling price; Determine the target power purchase period based on the power purchase price data and the target scheduling price, including: When the predicted supplementary power is less than the predicted power consumption, determine a first to-be-regulated power purchase period based on the power purchase price data and the first to-be-regulated scheduling price, and determine a second to-be-regulated power purchase period based on the power purchase price data and the second to-be-regulated scheduling price; Determine the first maximum charging power of the energy storage device charged by the power grid during the first to-be-regulated power purchase period and the second maximum charging power of the energy storage device charged by the power grid during the second to-be-regulated power purchase period based on the charging power limit condition of the energy storage device; Adjust the first to-be-regulated scheduling price until the predicted supplementary power, the first maximum charging power, and the first power consumption satisfy the preset balance condition to obtain the first target scheduling price; Adjust the second to-be-regulated scheduling price until the second maximum charging power and the second power consumption satisfy the preset balance condition to obtain the second target scheduling price; Determine a first target power purchase period based on the power purchase price data and the first target scheduling price, and determine a second target power purchase period based on the power purchase price data and the second target scheduling price.

7. The method according to claim 1, wherein Calculating the predicted supplementary power based on the predicted power generation data and the predicted power consumption data includes: Based on the predicted data of the power generation power and the predicted data of the power consumption power, determine the charging period; the charging period is the period when the power generation power is greater than the power consumption power; Calculate the difference power between the power generation power and the power consumption power during the charging period; Perform amplitude limiting processing on the difference power based on the charging power limit condition of the energy storage device to obtain the charging power; Integrate the charging power during the charging period to obtain the predicted charging amount; 8. The method according to claim 2, wherein The determining the adjustment direction of the to-be-adjusted scheduling price based on the predicted charging amount, the maximum charging amount, and the predicted power consumption includes: When the sum of the predicted charging amount and the maximum charging amount is less than the predicted power consumption, determine the adjustment direction as increasing the to-be-adjusted scheduling price; When the sum of the predicted charging amount and the maximum charging amount is greater than the predicted power consumption, determine the adjustment direction as decreasing the to-be-adjusted scheduling price.

9. An energy storage system, characterized in that, Includes: Photovoltaic power generation components, an energy storage device, a controller, and a memory; the energy storage system is further configured to be connected to a power grid and a load; The memory is used to store program instructions; And The controller is configured to read and execute the program instructions stored in the memory. When the program instructions are executed by the controller, the energy storage system executes the energy scheduling method according to any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores program instructions. When the program instructions run on the controller in the energy storage system, the energy storage system executes the energy scheduling method according to any one of claims 1 to 8.

Images