Power consumption control method, device and equipment based on optical storage system and storage medium

Abstract

The invention provides a power consumption control method, device and equipment based on a light storage system and a storage medium, and relates to the technical field of electric energy management. The method comprises the following steps: acquiring historical electricity consumption related data, including historical electricity consumption of a plurality of flexible loads corresponding to different time periods in a day, output power of a photovoltaic unit, charging power and discharging power of energy storage equipment, related information participating in demand response and electricity price; based on historical power consumption related data, a target function is constructed with the maximum sum of income participating in demand response and electric charge saved by peak-valley arbitrage as a target, and constraint conditions of the target function include a power consumption balance constraint, an energy storage device work constraint, a demand response constraint and a response time constraint of the energy storage device; solving the objective function under constraint conditions to obtain optimized power consumption corresponding to the plurality of flexible loads in each time period within one day; and controlling the power consumption of the plurality of flexible loads according to the optimized power consumption. According to the invention, power utilization control can be carried out more flexibly.

Description

Technical Field

[0001] The present application relates to the technical field of power management, and particularly to a power consumption control method, device, equipment and storage medium based on a photovoltaic energy storage system. Background Art

[0002] High-energy-consuming enterprises are the main group of energy consumption, and their electricity consumption costs account for a relatively large proportion of production costs. With the gradual opening of the power market and the transformation of the energy structure, how to optimize the electricity consumption strategy and reduce the electricity consumption cost has become the focus of attention of high-energy-consuming enterprises.

[0003] Currently, when high-energy-consuming enterprises consume electricity, usually the electricity consumption of some equipment is directly reduced, or, on this basis, an energy storage device is configured, and the energy storage is charged and discharged by using the peak-valley difference of the electricity price to achieve power consumption control, so as to consume electricity more reasonably and reduce the electricity consumption cost. However, there is a problem of single and fixed form in the above way of power consumption control. Summary of the Invention

[0004] The present application provides a power consumption control method, device, equipment and storage medium based on a photovoltaic energy storage system to solve the problem of single and fixed form existing in the current way of power consumption control.

[0005] In a first aspect, the present application provides a power consumption control method based on a photovoltaic energy storage system, including:

[0006] Obtain historical power consumption-related data, where the historical power consumption-related data includes the historical power consumption of multiple flexible loads corresponding to different time periods within a day, the output power of a photovoltaic unit, the charging power and discharging power of an energy storage device, relevant information participating in demand response, and the electricity price;

[0007] Based on the historical power consumption-related data, construct an objective function with the maximum sum of the benefits of participating in demand response and the electricity bill saved by peak-valley arbitrage as the goal, and the constraint conditions of the objective function include power consumption balance constraint, energy storage device working constraint, demand response constraint, and energy storage device response time constraint;

[0008] Solve the objective function under the constraint conditions to obtain the optimized power consumption of multiple flexible loads corresponding to each time period within a day;

[0009] Control the power consumption of multiple flexible loads according to the optimized power consumption.

[0010] Optionally, solve the objective function under constraints to obtain the optimized electricity consumption corresponding to multiple flexible loads at each time period within a day, including: obtaining the first optimized electricity consumption corresponding to multiple flexible loads during the charging period of the energy storage device according to historical electricity consumption, output power, and charging power; obtaining the second optimized electricity consumption corresponding to multiple flexible loads during the discharging period of the energy storage device according to historical electricity consumption, output power, and discharging power; determining multiple target time periods of the electricity consumption to be optimized corresponding to multiple flexible loads within a day according to the charging period and the discharging period; solving the objective function under constraints based on the target time periods to obtain the third optimized electricity consumption corresponding to multiple flexible loads at each target time period within a day; and obtaining the optimized electricity consumption corresponding to multiple flexible loads at each time period within a day according to the first optimized electricity consumption, the second optimized electricity consumption, and the third optimized electricity consumption.

[0011] Optionally, solve the objective function under constraints based on the target time periods to obtain the third optimized electricity consumption corresponding to multiple flexible loads at each target time period within a day, including: adjusting the electricity consumption corresponding to multiple flexible loads at each target time period under constraints to obtain the adjusted electricity consumption; and solving the objective function based on the electricity price corresponding to each target time period and the adjusted electricity consumption to obtain the third optimized electricity consumption corresponding to multiple flexible loads at each target time period within a day.

[0012] Optionally, the objective function satisfies the following formula:

[0013]

[0014] where t represents the time period number; n 1 represents the total number of time periods participating in demand response; T represents the total number of time periods participating in obtaining peak-valley arbitrage to save electricity charges; S(t) represents whether to participate in demand response; N represents the response revenue adjustment coefficient; C 1 (t) represents the clearing price of demand response in the relevant information; C 2 (t) represents the electricity price at time period t; P old (t) represents the historical electricity consumption of the flexible load at time period t; P real (t) is the decision variable of the objective function, used to represent the optimized electricity consumption of the flexible load at time period t; P valid (t) represents the effective response electricity quantity participating in demand response, which is determined based on P old (t), P real (t), and the winning bid electricity quantity in the relevant information.

[0015] Optionally, the output power of the photovoltaic unit, the charging power and the discharging power of the energy storage device corresponding to different time periods within a day are determined based on a preset photovoltaic-storage collaborative working rule, and the preset photovoltaic-storage collaborative working rule is used to instruct the photovoltaic unit and the energy storage device to cooperate with each other according to the time-of-use electricity price to complete the charging and discharging work of the energy storage device and the power supply work of the photovoltaic unit.

[0016] Optionally, the power consumption balance constraint is determined according to the historical power consumption, the charging power, the discharging power, the output power, and the optimized power consumption; the energy storage device working constraint is determined according to the energy storage upper limit, the energy storage lower limit, the charging power upper limit, the charging power lower limit, the discharging power upper limit, and the discharging power lower limit of the energy storage device; the demand response constraint is determined according to the historical power consumption, the optimized power consumption, and the winning bid power in the relevant information; the response time constraint of the energy storage device is determined according to the energy storage response time upper limit of the energy storage device.

[0017] In a second aspect, the present application provides a power consumption control device based on a photovoltaic-storage system, including:

[0018] An acquisition module, configured to acquire historical power consumption-related data, where the historical power consumption-related data includes the historical power consumption of a plurality of flexible loads corresponding to different time periods within a day, the output power of the photovoltaic unit, the charging power and the discharging power of the energy storage device, the relevant information participating in demand response, and the electricity price;

[0019] A construction module, configured to construct an objective function with the maximum sum of the benefits of participating in demand response and the electricity fee saved by peak-valley arbitrage as the goal based on the historical power consumption-related data, and the constraint conditions of the objective function include a power consumption balance constraint, an energy storage device working constraint, a demand response constraint, and a response time constraint of the energy storage device;

[0020] A processing module, configured to solve the objective function under the constraint conditions to obtain the optimized power consumption corresponding to each time period of a plurality of flexible loads within a day;

[0021] A control module, configured to control the power consumption of a plurality of flexible loads according to the optimized power consumption.

[0022] Optionally, the processing module is specifically configured to: obtain the first optimized power consumption corresponding to multiple flexible loads during the charging period of the energy storage device according to the historical power consumption, output power, and charging power; obtain the second optimized power consumption corresponding to multiple flexible loads during the discharging period of the energy storage device according to the historical power consumption, output power, and discharging power; determine multiple target periods of the power consumption to be optimized corresponding to multiple flexible loads within a day according to the charging period and the discharging period; solve the objective function under the constraint conditions based on the target periods to obtain the third optimized power consumption corresponding to multiple flexible loads at each target period within a day; and obtain the optimized power consumption corresponding to multiple flexible loads at each period within a day according to the first optimized power consumption, the second optimized power consumption, and the third optimized power consumption.

[0023] Optionally, when the processing module is configured to solve the objective function under the constraint conditions based on the target periods to obtain the third optimized power consumption corresponding to multiple flexible loads at each target period within a day, it is specifically configured to: adjust the power consumption corresponding to multiple flexible loads at each target period under the constraint conditions to obtain the adjusted power consumption; and solve the objective function based on the electricity price corresponding to each target period and the adjusted power consumption to obtain the third optimized power consumption corresponding to multiple flexible loads at each target period within a day.

[0024] Optionally, the objective function satisfies the following formula:

[0025]

[0026] where t represents the period number; n 1 represents the total number of periods participating in demand response; T represents the total number of periods participating in obtaining the electricity cost savings from peak-valley arbitrage; S(t) represents whether to participate in demand response; N represents the response revenue adjustment coefficient; C 1 (t) represents the clearing price of demand response in the relevant information; C 2 (t) represents the electricity price at time t; P old (t) represents the historical power consumption of the flexible load at time t; P real (t) is the decision variable of the objective function and is used to represent the optimized power consumption of the flexible load at time t; P valid (t) represents the effective response power consumption participating in demand response, which is determined based on P old (t), P real (t), and the winning bid power consumption in the relevant information.

[0027] Optionally, the output power of the photovoltaic unit, the charging power and the discharging power of the energy storage device corresponding to different time periods within a day are determined based on a preset photovoltaic-storage collaborative working rule, which is used to instruct the photovoltaic unit and the energy storage device to cooperate with each other according to the time-of-use electricity price to complete the charging and discharging work of the energy storage device and the power supply work of the photovoltaic unit.

[0028] Optionally, the power consumption balance constraint is determined according to historical power consumption, charging power, discharging power, output power, and optimized power consumption; the energy storage device working constraint is determined according to the upper energy storage limit, lower energy storage limit, upper charging power limit, lower charging power limit, upper discharging power limit, and lower discharging power limit of the energy storage device; the demand response constraint is determined according to historical power consumption, optimized power consumption, and the winning bid power in the relevant information; the response time constraint of the energy storage device is determined according to the upper energy storage response time limit of the energy storage device.

[0029] In a third aspect, the present application provides an electronic device, including: a processor, and a memory communicatively connected to the processor;

[0030] The memory stores computer-executable instructions;

[0031] The processor executes the computer-executable instructions stored in the memory to implement the power consumption control method based on the photovoltaic-storage system as described in the first aspect of the present application.

[0032] In a fourth aspect, the present application provides a computer-readable storage medium, in which computer program instructions are stored. When the computer program instructions are executed, the power consumption control method based on the photovoltaic-storage system as described in the first aspect of the present application is implemented.

[0033] In a fifth aspect, the present application provides a computer program product, including a computer program, which when executed implements the power consumption control method based on the photovoltaic-storage system as described in the first aspect of the present application.

[0034] A power consumption control method, device, equipment and storage medium based on a photovoltaic-storage system provided by the present application obtain historical power consumption-related data, where the historical power consumption-related data includes the historical power consumption of multiple flexible loads corresponding to different time periods within a day, the output power of a photovoltaic unit, the charging power and discharging power of a energy storage device, relevant information participating in demand response, and electricity prices. Based on the historical power consumption-related data, a target function is constructed with the goal of maximizing the sum of the benefits of participating in demand response and the electricity charges saved by peak-valley arbitrage. The constraint conditions of the target function include power consumption balance constraint, energy storage device operation constraint, demand response constraint, and response time constraint of the energy storage device. The target function is solved under the constraint conditions to obtain the optimized power consumption of multiple flexible loads corresponding to each time period within a day. According to the optimized power consumption, the power consumption of multiple flexible loads is controlled. In the present application, considering the operating characteristics of the photovoltaic unit and the energy storage device comprehensively, fully exploring the collaborative operation mode between the photovoltaic unit and the energy storage device, and realizing more flexible power consumption control by reasonably adjusting the power consumption of flexible loads, having the ability to participate in demand response while saving electricity charges, thereby helping to improve the stability and efficiency of the power grid. Description of the Drawings

[0035] The drawings here are incorporated into the specification and form a part of this specification, showing embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application.

[0036] Figure 1 It is a flowchart of a power consumption control method based on a photovoltaic-storage system provided by an embodiment of the present application;

[0037] Figure 2 It is a working schematic diagram of a photovoltaic unit provided by an embodiment of the present application;

[0038] Figure 3 It is a working schematic diagram of an energy storage device provided by an embodiment of the present application;

[0039] Figure 4 It is a flowchart of a power consumption control method based on a photovoltaic-storage system provided by another embodiment of the present application;

[0040] Figure 5 It is a structural schematic diagram of a power consumption control device based on a photovoltaic-storage system provided by an embodiment of the present application;

[0041] Figure 6 It is a structural schematic diagram of an electronic device provided by an embodiment of the present application.

[0042] Through the above drawings, specific embodiments of the present application have been shown, and there will be more detailed descriptions hereinafter. These drawings and text descriptions are not intended to limit the scope of the concept of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. Specific Embodiments

[0043] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without creative efforts shall fall within the protection scope of the present application.

[0044] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or fully authorized by all parties. And the collection, use, and processing of relevant data need to comply with relevant laws, regulations, and standards, and corresponding operation entrances are provided for users to choose to authorize or refuse.

[0045] First, some technical terms involved in the present application are explained as follows:

[0046] Demand response is a power management strategy that encourages electricity users to adjust their electricity consumption behavior during peak electricity demand periods or when electricity supply is tight to help balance the grid load.

[0047] Flexible load refers to an electricity load that can be dynamically adjusted according to the needs of the power system.

[0048] Peak-valley arbitrage refers to a strategy of using the difference in electricity prices at different times to purchase or store electricity during valley periods with lower electricity prices and use or sell electricity during peak periods with higher electricity prices to achieve benefits.

[0049] Currently, when high-energy-consuming enterprises use electricity, they usually directly cut the electricity consumption of some equipment, or, on this basis, configure energy storage equipment to perform energy storage charging and discharging operations using the peak-valley difference in electricity prices to achieve electricity consumption control, so as to use electricity more reasonably and reduce electricity costs. However, using the above methods to control electricity consumption ignores the ability of the energy storage equipped by high-energy-consuming enterprises themselves to participate in the power market demand response. Therefore, there is a problem of single and fixed form, and the benefits brought by the way of cutting electricity consumption are not enough to support the corresponding transformation costs. In addition, compared with other user-side resources, although high-energy-consuming enterprises have a large proportion of electricity consumption, due to the restrictions of the operation constraints of various production equipment, there are certain limitations in adjusting the electricity consumption of their production equipment. At the same time, there are differences in the production process technologies of different high-energy-consuming enterprises, and it is difficult to obtain a unified standard.

[0050] Based on the above problems, the present application provides a power consumption control method, device, equipment and storage medium based on a photovoltaic energy storage system. By fully analyzing the working characteristics of photovoltaic units and energy storage devices, exploring the collaborative operation mode between photovoltaic units and energy storage devices, and reasonably adjusting the power consumption of flexible loads, power consumption control can be carried out more flexibly, enabling high-energy-consuming enterprises to save electricity bills while having the ability to participate in demand response, being able to develop the flexibility resources of user-side loads to a greater extent, helping to improve the stability and efficiency of the power grid, and laying a foundation for high-energy-consuming enterprises to use energy storage to participate in power grid regulation.

[0051] It should be noted that the power consumption control method based on the photovoltaic energy storage system provided by the present application can be applied in a server, and the server can be an independent server, or a service cluster, etc.

[0052] Figure 1 This is a flowchart of the power consumption control method based on the photovoltaic energy storage system provided by an embodiment of the present application. As Figure 1 shown, the power consumption control method based on the photovoltaic energy storage system in the embodiment of the present application includes:

[0053] S101. Obtain historical power consumption-related data, where the historical power consumption-related data includes the historical power consumption of multiple flexible loads corresponding to different time periods within a day, the output power of the photovoltaic unit, the charging power and discharging power of the energy storage device, the relevant information for participating in demand response, and the electricity price.

[0054] In the embodiment of the present application, the historical power consumption-related data can be the historical power consumption-related data of any past day. Exemplarily, for example, a day can be divided into 24 time periods, then the historical power consumption-related data includes the historical power consumption of multiple flexible loads corresponding to 24 time periods within a day, the output power of the photovoltaic unit, the charging power and discharging power of the energy storage device, the relevant information for participating in demand response, and the electricity price. Among them, the relevant information for participating in demand response can include, for example, the clearing price of demand response and the winning bid quantity.

[0055] It can be understood that for the energy storage device, the state of charge (SOC) of the energy storage device includes two situations: charging and discharging. The mathematical models of the energy storage amounts of the energy storage device under different states of charge satisfy the following formula one and formula two:

[0056]

[0057] Among them, SOC chr (t) represents the state of charge of the energy storage device at time t during the charging process; SOC disc (t) represents the state of charge of the energy storage device at time t during the discharging process; η chrIndicates the charging efficiency of the energy storage device; η disc Indicates the discharging efficiency of the energy storage device; P chr (t) represents the charging power of the energy storage device at time t; P disc (t) represents the discharging power of the energy storage device at time t; E n Indicates the rated power of the energy storage device; Δt represents the duration of time period t.

[0058] For a photovoltaic unit, the power generation power of the photovoltaic unit mainly depends on the intensity of light, and is also affected by the ambient temperature to a certain extent. Therefore, the mathematical model of the power generation power of the photovoltaic unit satisfies the following formula three:

[0059]

[0060] Among them, P PV (t) represents the output power of the photovoltaic unit at time t, with the unit of watt (W); k T Represents the temperature coefficient, with the unit of % / °C; P SET Represents the rated output power of the photovoltaic unit, with the unit of watt; S SET Represents the standard light intensity of the photovoltaic unit, with the unit of kilowatt per square meter (kW / m 2 ); S(t) represents the light intensity of the photovoltaic unit at time t, with the unit of kW / m 2 ; T(t) represents the ambient temperature (°C) at time t; T SET Represents the standard ambient temperature (°C).

[0061] Optionally, the output power of the photovoltaic unit, the charging power and the discharging power of the energy storage device corresponding to different time periods within a day are determined based on a preset photovoltaic-storage collaborative working rule, and the preset photovoltaic-storage collaborative working rule is used to instruct the photovoltaic unit and the energy storage device to cooperate with each other according to the time-of-use electricity price to complete the charging and discharging work of the energy storage device and the power supply work of the photovoltaic unit.

[0062] It can be understood that the photovoltaic unit and the energy storage device applied in the production process optimization are not independent of each other, but cooperate with each other according to the electricity price and working status to complete the charging and discharging work. For the photovoltaic unit, the working time is concentrated during the day when the light is sufficient. The photovoltaic unit needs to supply power to the flexible load, and in addition, it also needs to supply power to the energy storage device during high electricity price periods. Figure 2 Is a working schematic diagram of the photovoltaic unit provided by an embodiment of the present application, as Figure 2As shown, the abscissa represents the time period, with the unit of hour (h), and the ordinate represents the power, with the unit of kilowatt (kW). At different time periods of a day, the working states of the photovoltaic unit include not supplying power 201, supplying power to the flexible load 202, and supplying power to the energy storage device 203. For the energy storage device, the working states include the charging state and the discharging state. The discharging state is to supply power to other devices, and the charging state is to charge from the photovoltaic unit even during high electricity price periods. Figure 3 The working schematic diagram of the energy storage device provided by an embodiment of the present application is as Figure 3 shown. The abscissa represents the time period, with the unit of hour (h), and the ordinate represents the electricity price, with the unit of yuan. At different time periods of a day, the working states of the energy storage device include the charging state 301 and the discharging state 302, and may also include the state of not charging and not discharging 303. The above-mentioned photovoltaic unit and energy storage device cooperate with each other according to the time-of-use electricity price to complete the charging and discharging work, and complete the charging and discharging work of the energy storage device and the power supply work of the photovoltaic unit, which is the preset photovoltaic-storage collaborative working rule, and can also be understood as the photovoltaic-storage collaborative working model. The specific preset photovoltaic-storage collaborative working rule is shown in Table 1 below.

[0063] Table 1

[0064] Time Photovoltaic unit Energy storage device 0 - 5 o'clock No light, not working Purchase electricity from the grid for charging 6 - 7 o'clock Output power is too low, not supplying power Purchase electricity from the grid for charging 8 - 11 o'clock Supply power to flexible load Supply power to other devices 12 - 13 o'clock Supply power to energy storage device Charge from photovoltaic unit 14 - 19 o'clock Supply power to flexible load until sunset Supply power to other devices until the lower limit of energy storage

[0065] Optionally, the historical electricity consumption of multiple flexible loads corresponding to different time periods within a day can also be used to obtain the flexible load electricity consumption curve, which is used to represent the change trend of the electricity consumption of the flexible load reserve within a day. The photovoltaic-storage collaborative working electricity consumption curve can also be obtained according to the output power of the photovoltaic unit, the charging power and discharging power of the energy storage device corresponding to different time periods within a day.

[0066] S102. Based on the historical electricity consumption-related data, a target function is constructed with the goal of maximizing the sum of the benefits of participating in demand response and the electricity charges saved by peak-valley arbitrage. The constraint conditions of the target function include power balance constraint, energy storage device working constraint, demand response constraint, and energy storage device response time constraint.

[0067] In this step, after obtaining the historical electricity consumption-related data, a target function can be constructed based on the historical electricity consumption-related data with the goal of maximizing the sum of the benefits of participating in demand response and the electricity charges saved by peak-valley arbitrage. Among them, the electricity consumption of the flexible load is used as the decision variable of the target function. By adjusting the electricity consumption of the flexible load within a day and introducing the photovoltaic-storage collaborative power supply and the benefits of participating in demand response, the goal of the target function is achieved: maxF = F 1 +F 2 where F 1 represents the benefit of participating in demand response after the production process optimization; F 2It represents the electricity cost saved through peak-valley arbitrage after the production process optimization. For the specific objective function, reference can be made to the subsequent embodiments.

[0068] The constraint conditions of the objective function include power balance constraint, energy storage device operation constraint, demand response constraint, and response time constraint of the energy storage device. It can be understood that the power balance constraint is used to ensure that the normal production work of high-energy-consuming enterprises is not affected before and after optimization, that is, the total power consumption before and after optimization should remain unchanged; the energy storage device operation constraint is used to ensure that the power consumption in each period after power optimization cannot be higher or lower than a certain proportion of the rated working power of the energy storage device, so as to ensure the normal and safe operation of the energy storage device; the demand response constraint is used to determine the effective response power; the response time constraint of the energy storage device is used to consider the influence of the energy storage action delay of the energy storage device, that is, the response time should be less than the upper limit of the response time. For the specific constraint conditions, reference can be made to the subsequent embodiments.

[0069] S103. Solve the objective function under the constraint conditions to obtain the optimized power consumption corresponding to multiple flexible loads in each period within a day.

[0070] Exemplarily, based on the historical power consumption-related data and the power consumption corresponding to multiple flexible loads during the charging period and discharging period of the energy storage device respectively, the objective function can be solved under the constraint conditions of the objective function to obtain the optimized power consumption corresponding to multiple flexible loads in each period within a day. The embodiments of the present application do not limit the solution method.

[0071] S104. Control the power consumption of multiple flexible loads according to the optimized power consumption.

[0072] In this step, after obtaining the optimized power consumption corresponding to multiple flexible loads in each period within a day, the power consumption of multiple flexible loads at different times within a day can be controlled according to the optimized power consumption. Optionally, the optimized flexible load power consumption curve can also be obtained according to the optimized power consumption corresponding to multiple flexible loads in each period within a day, so as to facilitate viewing the change trend of the optimized power consumption of the flexible load within a day; the income from participating in demand response and the electricity cost saved through peak-valley arbitrage can also be output.

[0073] The power consumption control method based on a photovoltaic-storage system provided by an embodiment of the present application obtains historical power consumption-related data, which includes the historical power consumption of multiple flexible loads corresponding to different time periods within a day, the output power of a photovoltaic unit, the charging power and discharging power of an energy storage device, relevant information participating in demand response, and electricity prices. Based on the historical power consumption-related data, a target function is constructed with the goal of maximizing the sum of the benefits from participating in demand response and the electricity charges saved through peak-valley arbitrage. The constraint conditions of the target function include power consumption balance constraints, energy storage device operation constraints, demand response constraints, and response time constraints of the energy storage device. The target function is solved under the constraint conditions to obtain the optimized power consumption of multiple flexible loads corresponding to each time period within a day. According to the optimized power consumption, the power consumption of multiple flexible loads is controlled. In the embodiment of the present application, by comprehensively considering the operating characteristics of the photovoltaic unit and the energy storage device, fully exploring the collaborative operation mode between the photovoltaic unit and the energy storage device, and reasonably adjusting the power consumption of flexible loads, more flexible power consumption control is achieved. While saving electricity charges, the ability to participate in demand response is also possessed, thereby helping to improve the stability and efficiency of the power grid.

[0074] Based on the above embodiment, it can be understood that a photovoltaic-storage collaborative work model is introduced into the production process facing demand response, and then a complete operation method for high-energy-consuming enterprises participating in demand response considering photovoltaic-storage collaborative work is established. The main steps may include: Step 1, analyze the power consumption characteristics in the production process of high-energy-consuming enterprises and analyze their daily power load curves; Step 2, select appropriate photovoltaic units and energy storage devices, and the output of the photovoltaic units and energy storage devices should match the electrical equipment, and further study the photovoltaic-storage collaborative work; Step 3, participate in demand response transactions; Step 4, through optimization processing, obtain the daily power consumption of the optimized flexible load and the available benefits.

[0075] Figure 4 The flowchart of the power consumption control method based on a photovoltaic-storage system provided by another embodiment of the present application. Based on the above embodiment, the embodiment of the present application further describes the power consumption control method based on a photovoltaic-storage system. As Figure 4 shown, the power consumption control method based on a photovoltaic-storage system of the embodiment of the present application may include:

[0076] S401. Obtain historical power consumption-related data, which includes the historical power consumption of multiple flexible loads corresponding to different time periods within a day, the output power of a photovoltaic unit, the charging power and discharging power of an energy storage device, relevant information participating in demand response, and electricity prices.

[0077] For the specific description of this step, reference can be made to the relevant description of S101 in the embodiment Figure 1 shown, and details are not described herein again.

[0078] S402. Based on the historical electricity consumption - related data, construct an objective function with the goal of maximizing the sum of the benefits from participating in demand response and the electricity charges saved through peak - valley arbitrage. The constraint conditions of the objective function include power balance constraint, energy storage device operation constraint, demand response constraint, and energy storage device response time constraint.

[0079] For the specific description of this step, reference can be made to Figure 1 the relevant description of S102 in the illustrated embodiment. Optionally, the objective function satisfies the following formula four:

[0080]

[0081] where t represents the time period number; n 1 represents the total number of time periods participating in demand response; T represents the total number of time periods participating in obtaining the electricity charges saved through peak - valley arbitrage; S(t) represents whether to participate in demand response. For example, when the value of S(t) is 0, it means not participating in demand response, and when the value of S(t) is 1, it means participating in demand response; N represents the response benefit adjustment coefficient; C 1 (t) represents the clearing price of demand response in the relevant information, with the unit of yuan per kilowatt - hour; C 2 (t) represents the electricity price at time period t, with the unit of yuan per kilowatt - hour; P old (t) represents the historical electricity consumption of the flexible load at time period t; P real (t) is a decision variable of the objective function, used to represent the optimized electricity consumption of the flexible load at time period t; P valid (t) represents the effective response electricity quantity participating in demand response, which is determined based on P old (t), P real (t) and the winning bid electricity quantity in the relevant information. Specifically, reference can be made to formula ten in the subsequent embodiment.

[0082] It can be understood that in the above - mentioned embodiment of S102

[0083] Optionally, the power balance constraint is determined based on historical electricity consumption, charging power, discharging power, output power, and optimized electricity consumption; the energy storage device operation constraint is determined based on the energy storage upper limit, energy storage lower limit, charging power upper limit, charging power lower limit, discharging power upper limit, and discharging power lower limit of the energy storage device; the demand response constraint is determined based on historical electricity consumption, optimized electricity consumption, and the winning bid electricity quantity in the relevant information; the energy storage device response time constraint is determined based on the energy storage response time upper limit of the energy storage device.

[0084] Exemplarily, the power balance constraint is used to ensure that the normal production work of high - energy - consuming enterprises is not affected before and after optimization, that is, the total electricity consumption before and after optimization should remain unchanged. The power balance constraint satisfies the following formula five:

[0085]

[0086] Among them, Equation 5 indicates that the sum of the optimized electricity consumption corresponding to the flexible load, the power generation (output power) of the photovoltaic unit, and the charge and discharge amount (charging power and discharging power) of the energy storage device within one day should be the same as the total electricity before optimization, so as to ensure that the normal production work of high-energy-consuming enterprises is not affected after they participate in demand response.

[0087] The working constraints of the energy storage device are used to ensure that the electricity consumption in each period after electricity optimization cannot be higher or lower than a certain proportion of the rated working electricity of the energy storage device, so as to ensure the normal and safe operation of the energy storage device. The working constraints of the energy storage device are as follows in Equations 6 to 9:

[0088] SOC min ≤SOC chr (t)≤SOC max Equation 6

[0089] SOC min ≤SOC disc (t)≤SOC max Equation 7

[0090]

[0091] Among them, SOC max represents the upper limit of the energy storage of the energy storage device; SOC min represents the lower limit of the energy storage of the energy storage device; represents the upper limit of the charging power of the energy storage device; represents the lower limit of the charging power of the energy storage device; represents the upper limit of the discharging power of the energy storage device; represents the lower limit of the discharging power of the energy storage device.

[0092] For the demand response constraint, it can be understood that when participating in demand response, it is necessary to participate in bidding. After determining the winning bid electricity, the electricity consumption curve is adjusted on the day of the demand response transaction, and the effective response electricity is determined according to the actual response electricity. Finally, the revenue settlement is carried out based on the effective response electricity. Therefore, the effective response electricity can be determined by the following Equation 10:

[0093]

[0094] Among them, P bid (t) represents the winning bid electricity; P valid (t) represents the effective response electricity.

[0095] For Equation 10 above, (P old (t)-Preal (t) represents the actual responsive power consumption, and P(t) can be obtained according to different conditions. valid (t). For example, if (P old (t) - P real (t)) < P bid (t) × 50%, then P valid (t) is 0.

[0096] The response time constraint of the energy storage device is used to consider the influence of the energy storage action time delay of the energy storage device, that is, the energy storage response time should be less than the upper limit of the energy storage response time. The response time constraint of the energy storage device satisfies the following formula XI:

[0097] t ≤ t max Formula XI

[0098] Among them, t max is a preset value; t corresponds to the function related to the time period in the above embodiment, and numerically (that is, the length of the time period is how many minutes or how many hours) is equal to this t.

[0099] In the embodiment of the present application, Figure 1 step S103 in can further include the following four steps of S403 to S406:

[0100] S403. According to the historical power consumption, output power, and charging power, obtain the first optimized power consumption corresponding to multiple flexible loads during the charging period of the energy storage device respectively; according to the historical power consumption, output power, and discharge power, obtain the second optimized power consumption corresponding to multiple flexible loads during the discharge period of the energy storage device respectively.

[0101] Exemplarily, for the charging period of the energy storage device, the first optimized power consumption can be obtained through the following formula XII:

[0102] P real (t) = P old (t) + P chr (t) - P PV (t) Formula XII

[0103] For the discharge period of the energy storage device, the second optimized power consumption can be obtained through the following formula XIII:

[0104] P real (t) = P old (t) - P disc (t) - P PV (t) Formula XIII

[0105] S404. According to the charging period and the discharge period, determine multiple target periods of the power consumption to be optimized corresponding to multiple flexible loads within a day.

[0106] Exemplarily, referring to Figure 3 , the charging state of the energy storage device corresponds to the charging period, and the discharging state corresponds to the discharging period. Therefore, according to the charging period and the discharging period, it is possible to determine that the multiple target periods of the electricity consumption to be optimized corresponding to multiple flexible loads within a day are the periods corresponding to the state of neither charging nor discharging. It can be understood that during the charging period and the discharging period of the energy storage device, whether it is to save electricity costs or participate in demand response, the corresponding effects are achieved through the collaborative work of the photovoltaic and energy storage systems. For the target periods, the electricity consumption of the flexible loads can be adjusted to reduce the electricity cost.

[0107] S405. Based on the target periods, solve the objective function under the constraint conditions to obtain the third optimized electricity consumption corresponding to multiple flexible loads within a day at each target period respectively.

[0108] In this step, after determining the target periods, the objective function can be solved under the constraint conditions to obtain the third optimized electricity consumption corresponding to multiple flexible loads within a day at each target period respectively.

[0109] Optionally, based on the target periods, solving the objective function under the constraint conditions to obtain the third optimized electricity consumption corresponding to multiple flexible loads within a day at each target period respectively may include: under the constraint conditions, adjust the electricity consumption corresponding to multiple flexible loads at each target period respectively to obtain the adjusted electricity consumption; based on the electricity price corresponding to each target period and the adjusted electricity consumption, solve the objective function to obtain the third optimized electricity consumption corresponding to multiple flexible loads within a day at each target period respectively.

[0110] It can be understood that under the constraint conditions, adjusting the electricity consumption corresponding to multiple flexible loads at each target period respectively can achieve iterative solution of the objective function, so as to obtain the third optimized electricity consumption corresponding to multiple flexible loads within a day at each target period respectively.

[0111] S406. According to the first optimized electricity consumption, the second optimized electricity consumption, and the third optimized electricity consumption, obtain the optimized electricity consumption corresponding to multiple flexible loads within a day at each period respectively.

[0112] In this step, after obtaining the first optimized electricity consumption, the second optimized electricity consumption, and the third optimized electricity consumption corresponding to different periods within a day, that is, the optimized electricity consumption corresponding to multiple flexible loads within a day at each period respectively is obtained.

[0113] S407. Control the electricity consumption of multiple flexible loads according to the optimized electricity consumption.

[0114] For the specific description of this step, reference can be made to the relevant description of S104 in the Figure 1 illustrated embodiment, which will not be elaborated here.

[0115] The power consumption control method based on a photovoltaic and energy storage system provided by an embodiment of the present application obtains historical power consumption-related data, where the historical power consumption-related data includes the historical power consumption of multiple flexible loads corresponding to different time periods within a day, the output power of a photovoltaic unit, the charging power and discharging power of an energy storage device, relevant information participating in demand response, and electricity prices. Based on the historical power consumption-related data, a target function is constructed with the goal of maximizing the sum of the benefits of participating in demand response and the electricity charges saved through peak-valley arbitrage. The constraint conditions of the target function include power consumption balance constraints, energy storage device operation constraints, demand response constraints, and response time constraints of the energy storage device. According to the historical power consumption, output power, and charging power, the first optimized power consumption corresponding to each of the multiple flexible loads during the charging period of the energy storage device is obtained. According to the historical power consumption, output power, and discharging power, the second optimized power consumption corresponding to each of the multiple flexible loads during the discharging period of the energy storage device is obtained. According to the charging period and the discharging period, multiple target time periods of the power consumption to be optimized corresponding to the multiple flexible loads within a day are determined. Based on the target time periods, the target function is solved under the constraint conditions to obtain the third optimized power consumption corresponding to each of the multiple flexible loads at each target time period within a day. According to the first optimized power consumption, the second optimized power consumption, and the third optimized power consumption, the optimized power consumption corresponding to each of the multiple flexible loads at each time period within a day is obtained. According to the optimized power consumption, the power consumption of the multiple flexible loads is controlled. In the embodiment of the present application, considering the working characteristics of the photovoltaic unit and the energy storage device comprehensively, fully exploring the collaborative operation mode between the photovoltaic unit and the energy storage device, during the charging period and the discharging period of the energy storage device, the photovoltaic and energy storage work together to achieve corresponding effects. For the target time periods, the power consumption of the flexible loads is adjusted to reduce the power consumption cost, which can more reasonably adjust the power consumption of the flexible loads, realize more flexible power consumption control, have the ability to participate in demand response while saving electricity charges, and thus help improve the stability and efficiency of the power grid.

[0116] The following is an embodiment of the device of the present application, which can be used to execute the method embodiment of the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the method embodiment of the present application.

[0117] Figure 5 This is a schematic structural diagram of a power consumption control device based on a photovoltaic and energy storage system provided by an embodiment of the present application. As Figure 5 shown, the power consumption control device 500 based on a photovoltaic and energy storage system according to an embodiment of the present application includes: an acquisition module 501, a construction module 502, a processing module 503, and a control module 504. Among them:

[0118] An acquisition module 501 is configured to acquire historical power consumption-related data, where the historical power consumption-related data includes the historical power consumption of multiple flexible loads corresponding to different time periods within a day, the output power of a photovoltaic unit, the charging power and discharging power of an energy storage device, relevant information participating in demand response, and electricity prices.

[0119] A construction module 502 is configured to construct an objective function based on the historical power consumption-related data with the goal of maximizing the sum of the benefits of participating in demand response and the electricity charges saved through peak-valley arbitrage. The constraint conditions of the objective function include power balance constraint, energy storage device operation constraint, demand response constraint, and response time constraint of the energy storage device.

[0120] A processing module 503 is configured to solve the objective function under the constraint conditions to obtain the optimized power consumption of multiple flexible loads corresponding to each time period within a day.

[0121] A control module 504 is configured to control the power consumption of multiple flexible loads according to the optimized power consumption.

[0122] In some embodiments, the processing module 503 may specifically be configured to: obtain the first optimized power consumption of multiple flexible loads corresponding to the charging time period of the energy storage device according to the historical power consumption, output power, and charging power; obtain the second optimized power consumption of multiple flexible loads corresponding to the discharging time period of the energy storage device according to the historical power consumption, output power, and discharging power; determine multiple target time periods of the power consumption to be optimized corresponding to multiple flexible loads within a day according to the charging time period and the discharging time period; solve the objective function under the constraint conditions based on the target time periods to obtain the third optimized power consumption of multiple flexible loads corresponding to each target time period within a day; and obtain the optimized power consumption of multiple flexible loads corresponding to each time period within a day according to the first optimized power consumption, the second optimized power consumption, and the third optimized power consumption.

[0123] Optionally, when the processing module 503 is configured to solve the objective function under the constraint conditions based on the target time periods to obtain the third optimized power consumption of multiple flexible loads corresponding to each target time period within a day, it may specifically be configured to: adjust the power consumption of multiple flexible loads corresponding to each target time period under the constraint conditions to obtain the adjusted power consumption; and solve the objective function based on the electricity prices corresponding to each target time period and the adjusted power consumption to obtain the third optimized power consumption of multiple flexible loads corresponding to each target time period within a day.

[0124] Optionally, the objective function satisfies the following formula:

[0125]

[0126] where t represents the time period number; n 1represents the total number of time periods participating in demand response; T represents the total number of time periods participating in obtaining the electricity cost savings from peak-valley arbitrage; S(t) represents whether to participate in demand response; N represents the response revenue adjustment coefficient; C 1 C(t) represents the clearing price of demand response in the relevant information; C 2 C(t) represents the electricity price at time period t; P old P(t) represents the historical electricity consumption of the flexible load at time period t; P real P(t) is the decision variable of the objective function, used to represent the optimized electricity consumption of the flexible load at time period t; P valid P(t) represents the effective response electricity quantity participating in demand response, which is determined based on P old P(t), P real P(t) and the winning bid electricity quantity in the relevant information.

[0127] Optionally, the output power of the photovoltaic unit, the charging power and the discharging power of the energy storage device corresponding to different time periods within a day are determined based on a preset photovoltaic-energy storage collaborative working rule, and the preset photovoltaic-energy storage collaborative working rule is used to instruct the photovoltaic unit and the energy storage device to cooperate with each other according to the time-of-use electricity price to complete the charging and discharging work of the energy storage device and the power supply work of the photovoltaic unit.

[0128] Optionally, the power balance constraint is determined based on the historical electricity consumption, the charging power, the discharging power, the output power and the optimized electricity consumption; the energy storage device working constraint is determined based on the energy storage upper limit, the energy storage lower limit, the charging power upper limit, the charging power lower limit, the discharging power upper limit and the discharging power lower limit of the energy storage device; the demand response constraint is determined based on the historical electricity consumption, the optimized electricity consumption and the winning bid electricity quantity in the relevant information; the response time constraint of the energy storage device is determined based on the energy storage response time upper limit of the energy storage device.

[0129] The device of the embodiment of the present application can be used to execute the technical solutions of any of the above-mentioned method embodiments, and its implementation principle and technical effects are similar, which will not be elaborated here.

[0130] Figure 6 This is a schematic structural diagram of an electronic device provided by an embodiment of the present application. As Figure 6 shown, the electronic device 600 may include: at least one processor 601 and a memory 602.

[0131] The memory 602 is used to store a program. Specifically, the program may include program code, and the program code includes computer execution instructions.

[0132] The memory 602 may include high-speed random access memory (RAM), and may also include non-volatile memory, such as at least one disk memory.

[0133] The processor 601 is used to execute the computer-executable instructions stored in the memory 602 to implement the power consumption control method based on the optical storage system described in the foregoing method embodiments. Among them, the processor 601 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application. Specifically, when implementing the power consumption control method based on the optical storage system described in the foregoing method embodiments, the electronic device may be an electronic device with processing functions such as a server.

[0134] Optionally, the electronic device 600 may further include a communication interface 603. In specific implementation, if the communication interface 603, the memory 602, and the processor 601 are independently implemented, the communication interface 603, the memory 602, and the processor 601 may be interconnected through a bus and communicate with each other. The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc., but it does not mean that there is only one bus or one type of bus.

[0135] Optionally, in specific implementation, if the communication interface 603, the memory 602, and the processor 601 are integrated on a chip, the communication interface 603, the memory 602, and the processor 601 may communicate through an internal interface.

[0136] The present application also provides a computer-readable storage medium, in which computer program instructions are stored. When the processor executes the computer program instructions, the solution of the power consumption control method based on the optical storage system as described above is implemented.

[0137] The present application also provides a computer program product, including a computer program, which implements the solution of the power consumption control method based on the optical storage system as described above when executed.

[0138] The above computer-readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Read Only Memory (PROM), Read Only Memory (ROM), magnetic memory, flash memory, a magnetic disk, or an optical disk. The readable storage medium can be any available medium accessible by a general-purpose or special-purpose computer.

[0139] An exemplary readable storage medium is coupled to the processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit. Of course, the processor and the readable storage medium can also exist as discrete components in an electrical control device based on an optical storage system.

[0140] Those of ordinary skill in the art can understand that all or part of the steps for implementing the above method embodiments can be completed by hardware related to program instructions. The foregoing program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps including those of the above method embodiments; and the foregoing storage medium includes various media that can store program codes, such as ROM, RAM, magnetic disks, or optical disks.

[0141] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application and are not intended to limit them. Although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for controlling power consumption based on a photovoltaic storage system, characterized in that: include: Obtaining historical electricity consumption related data, the historical electricity consumption related data including historical electricity consumption of multiple flexible loads corresponding to different time periods in a day, output power of photovoltaic units, charging power and discharging power of energy storage equipment, relevant information on participating in demand response, and electricity prices; Based on the historical electricity consumption related data, an objective function is constructed with the goal of maximizing the sum of the benefits of participating in demand response and the electricity cost saved by peak-valley arbitrage, and the constraints of the objective function include power balance constraints, energy storage equipment working constraints, demand response constraints, and energy storage equipment response time constraints; Solving the objective function under the constraint conditions to obtain the optimized power consumption corresponding to the multiple flexible loads in each time period in a day; The power consumption of the plurality of flexible loads is controlled according to the optimized power consumption.

2. The power consumption control method according to claim 1, characterized in that: The objective function is solved under the constraint conditions to obtain the optimized power consumption corresponding to the multiple flexible loads in each time period in a day, including: According to the historical power consumption, the output power and the charging power, obtaining first optimized power consumptions corresponding to the plurality of flexible loads during the charging period of the energy storage device; According to the historical power consumption, the output power and the discharge power, obtaining the second optimized power consumption corresponding to each of the plurality of flexible loads during the discharge period of the energy storage device; Determine, according to the charging period and the discharging period, a plurality of target periods of power consumption to be optimized corresponding to the plurality of flexible loads in one day; Based on the target time period, the objective function is solved under the constraint condition to obtain the third optimized power consumption corresponding to each of the target time periods of the multiple flexible loads in one day; According to the first optimized power consumption, the second optimized power consumption and the third optimized power consumption, the optimized power consumption corresponding to the multiple flexible loads in each time period in one day is obtained.

3. The power consumption control method according to claim 2, characterized in that: The objective function is solved based on the target time period under the constraint condition to obtain the third optimized power consumption corresponding to each of the target time periods of the multiple flexible loads in one day, including: Under the constraint conditions, adjusting the power consumption corresponding to each of the target time periods of the plurality of flexible loads to obtain adjusted power consumption; Based on the electricity price corresponding to each target time period and the adjusted power consumption, the objective function is solved to obtain the third optimized power consumption corresponding to each target time period of the plurality of flexible loads in one day.

4. The power consumption control method according to claim 1, characterized in that: The objective function satisfies the following formula: Wherein, t represents the time period number; n1 represents the total number of time periods participating in demand response; T represents the total number of time periods participating in peak-valley arbitrage to save electricity costs; S(t) represents whether to participate in demand response; N represents the response benefit adjustment coefficient; C1(t) represents the clearing price of demand response in the relevant information; C2(t) represents the electricity price in time period t; P old (t) represents the historical power consumption of the flexible load in period t; P real (t) is the decision variable of the objective function, which is used to represent the optimized power consumption of the flexible load in the period t; valid (t) represents the effective response power participating in demand response, which is based on P old (t), P real (t) and the winning bid quantity in the relevant information.

5. The power consumption control method according to any one of claims 1 to 4, characterized in that: The output power of the photovoltaic group, the charging power and the discharging power of the energy storage device corresponding to different time periods in a day are determined based on the preset photovoltaic and storage collaborative working rules. The preset photovoltaic and storage collaborative working rules are used to instruct the photovoltaic group and the energy storage device to cooperate with each other according to the time-of-use electricity price to complete the charging and discharging of the energy storage device and the power supply of the photovoltaic group.

6. The power consumption control method according to any one of claims 1 to 4, characterized in that: The power balance constraint is determined based on the historical power consumption, the charging power, the discharging power, the output power and the optimized power consumption; the energy storage device working constraint is determined based on the energy storage upper limit, energy storage lower limit, charging power upper limit, charging power lower limit, discharging power upper limit and discharging power lower limit of the energy storage device; the demand response constraint is determined based on the historical power consumption, the optimized power consumption and the winning bid power in the relevant information; the response time constraint of the energy storage device is determined based on the energy storage response time upper limit of the energy storage device.

7. A power consumption control device based on a photovoltaic storage system, characterized in that: include: An acquisition module is used to acquire historical electricity consumption related data, wherein the historical electricity consumption related data includes historical electricity consumption of multiple flexible loads corresponding to different time periods in a day, output power of photovoltaic units, charging power and discharging power of energy storage equipment, relevant information on participating in demand response, and electricity price; A construction module is used to construct an objective function based on the historical electricity consumption related data with the goal of maximizing the sum of the benefits of participating in demand response and the electricity cost saved by peak-valley arbitrage, wherein the constraints of the objective function include power balance constraints, energy storage equipment working constraints, demand response constraints, and energy storage equipment response time constraints; A processing module, used for solving the objective function under the constraint conditions to obtain the optimized power consumption corresponding to the multiple flexible loads in each time period in a day; A control module is used to control the power consumption of the multiple flexible loads according to the optimized power consumption.

8. An electronic device, characterized in that: include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the power consumption control method based on the photovoltaic storage system according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer program instructions, and when the computer program instructions are executed, the power consumption control method based on the photovoltaic storage system according to any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed, the power consumption control method based on the photovoltaic storage system according to any one of claims 1 to 6 is implemented.

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