Household distributed photovoltaic output optimization and control method

Abstract

The invention relates to a household distributed photovoltaic output optimization and control method, and belongs to the photovoltaic field. From the perspective of alternative energy consumption and multi-energy complementation, traditional time-of-use electricity price is taken as an excitation signal, a household and park micro-energy grid comprehensive demand response model based on optimized operation is constructed, and a micro-energy grid comprehensive demand response strategy is formulated based on coordinated optimization of various energy conversion and energy storage equipment and loads. While diversified energy requirements of users are met, the operation scheduling cost of the power grid is reduced, and accurate and scientific control of household photovoltaic is realized.

Description

Technical Field

[0001] The present invention belongs to the field of photovoltaics, and in particular relates to a household distributed photovoltaic output optimization and control method. Background Art

[0002] The output of household distributed photovoltaic power generation is highly random, affected by the user's energy consumption behavior. If it is not guided and controlled, its uncertainty will penetrate into the distribution network, seriously affecting the safe and stable operation of the distribution network.

[0003] Residential energy consumers have great potential for demand response. With the promotion and popularization of wall-mounted boilers, household electric energy storage and household photovoltaic power generation devices, the demand response resources on the residential side will become increasingly abundant, including not only traditional household appliances, but also facilities such as household electric energy storage, photovoltaic power generation and wall-mounted boilers. The role of residential electricity users will also undergo major changes, from traditional electricity demand response participants to comprehensive demand response participants. Summary of the invention

[0004] The purpose of the present invention is to provide a household distributed photovoltaic output optimization and control method, from the perspective of alternative energy and multi-energy complementarity, to construct a comprehensive demand response model for household and campus micro-energy networks based on optimized operation, based on the coordinated optimization of various energy conversion and energy storage equipment and loads, to formulate a comprehensive demand response strategy for the micro-energy network, while meeting the diverse energy needs of users, reducing the grid operation and dispatching costs, and realizing accurate and scientific control of household photovoltaics.

[0005] To achieve the above purpose, the technical solution of the present invention is: a household distributed photovoltaic output optimization and control method, comprising:

[0006] From the perspective of alternative energy use and multi-energy complementarity, a comprehensive demand response model for household micro-energy grid based on optimized operation is constructed;

[0007] Based on the coordinated optimization of various energy conversion and storage equipment and loads, a comprehensive demand response strategy for micro-energy networks is formulated.

[0008] In one embodiment of the present invention, a comprehensive demand response model of a household micro-energy network based on optimized operation includes:

[0009] Load model construction;

[0010] Construction of comprehensive demand response model.

[0011] In one embodiment of the present invention, the load model is constructed, including:

[0012] (1) Power load

[0013] (1.1)Transferable and non-interruptible load

[0014] The working time of the shiftable and non-interruptible load can be shifted within the time window scheduled by the user, but once the work starts, it is not allowed to be interrupted; for the shiftable and non-interruptible load, its load model is as follows:

[0015]

[0016] Where: m represents the electrical appliance that can be moved horizontally and cannot be interrupted. is the actual operating power of electrical appliance m at time t; is the rated power of electrical appliance m; is a binary variable, indicating the working state of appliance m at time t. Indicates the start state, otherwise it indicates the shutdown state; The working time necessary for appliance m to complete its task; and They represent the earliest start time and the latest end time of the operation of the appliance m set by the user; v is the start time of the appliance m; the second term in the above formula indicates that the operation of the appliance cannot be interrupted, and the third term in the above formula indicates that the appliance must work within the working time interval set by the user;

[0017] (1.2)Transferable and interruptible load

[0018] The loads that can be shifted and interrupted include electric vehicles and household energy storage batteries, whose operation can be interrupted and the working hours can be shifted;

[0019] For electric vehicles, the load model is as follows:

[0020]

[0021] Where: is the movable and interruptible load, i.e., the charging power of the electric vehicle at time t; is the maximum charging power of the charging vehicle; It is the time for the electric car to arrive home; It’s time for electric cars to go out; SOC t The state of charge of the electric vehicle at time t; W EV is the electric vehicle capacity; η ch is the electric vehicle charging efficiency; EV is the energy loss rate of the electric vehicle battery; SOC min and SOC max They are the minimum and maximum state of charge levels of electric vehicle batteries; SOC dis the expected value of the state of charge of the electric vehicle when the user goes out; the first two items in the above formula respectively indicate that the electric vehicle can be charged only when the user arrives home, and the charging power is not greater than its maximum power constraint; the third and fourth items in the above formula indicate the state of charge of the electric vehicle battery; the last item in the above formula indicates that the state of charge of the electric vehicle when the user goes out is not less than the expected value;

[0022] For household energy storage batteries, the load model is as follows:

[0023]

[0024] Where: η stg(+) is the charging efficiency; S SOC (t) is the state of charge at time t; E stg,rate is the rated capacity of the energy storage battery; S SOC,ini is the initial state of charge; S SOC,min and S SOC,max are the minimum and maximum values ​​of the state of charge, P stg(+) / (-) Charging power / discharging power for energy storage batteries.

[0025] In one embodiment of the present invention, the power load further includes:

[0026] (1.3) Baseline load

[0027] The baseline load is a fixed-power, mandatory load.

[0028] In one embodiment of the present invention, the load model construction further includes:

[0029] (2) Alternative energy load

[0030] Alternative energy loads include wall-mounted boilers, which produce hot water by burning natural gas for household bathing and heating. The wall-mounted boiler load model is expressed as:

[0031]

[0032] Where: and are the natural gas input power and thermal output power of the wall-mounted boiler at time t, is the maximum input power of the wall-mounted boiler; η whs It is the heating efficiency of the wall-mounted boiler.

[0033] In one embodiment of the present invention, the load model construction further includes:

[0034] (3) Heat load

[0035] The heat load is modeled as the required hot water load. It is assumed that the water in the water tank can be heated by electric heating or heat generated by gas boilers and gas turbines. It is also assumed that the amount of hot water consumed in the water tank will be supplemented with an equal amount of cold water. The hot water temperature is expressed as:

[0036]

[0037] Where: Indicates the hot water temperature at time t, T1 ws Indicates the hot water temperature at the initial moment; is the volume of cold water added, i.e. the hot water load at time t; is the hot water load at the initial moment; V is the volume of the water tank; ρ w is the density of water; T cw is the cold water temperature; C w is the specific heat capacity of water; is the required heating power;

[0038] If you want to maintain the hot water at the desired temperature The required heating power Use the following formula to calculate:

[0039]

[0040] In one embodiment of the present invention, the comprehensive demand response model is constructed, including:

[0041] 1) Objective function:

[0042] The goal of household comprehensive demand response is to minimize its daily operating costs. The objective function expression is as follows:

[0043]

[0044] The objective function includes five items, namely, electricity purchase cost, gas purchase cost, battery operation cost, electricity sales revenue and electricity sales penalty cost. is the power purchased by the user from the grid at time t, P t is the electricity price at time t, G t is the gas purchase volume at time t, p g is the natural gas price, k1 and k2 are the battery penalty coefficient and the electricity sales penalty coefficient respectively, P sell,t is the electricity sold at time t, p sell,t is the electricity price at time t, The amount of electricity expected to be purchased by the power grid.

[0045] In one embodiment of the present invention, the comprehensive demand response model is constructed, further comprising:

[0046] 2) Constraints

[0047] The constraint is the power balance constraint, which is expressed as:

[0048]

[0049] Where: is the photovoltaic output power, is the discharge power of the energy storage battery, Charging power for energy storage battery, P sell For selling electricity, is the power of the electric boiler, is the electrical cooling power, The charging power of the charging pile, Aggregate power for other electrical loads; is the thermal power of the wall-mounted boiler, η whs The heating efficiency of the wall-mounted boiler is is the electric power of the electric water heater, η eh is the thermal efficiency of the electric water heater, is the heat load, and They are respectively the charging power of electric vehicles, the power of washing machines, dishwashers and rice cookers among the movable and non-interruptible loads, is the baseline load power.

[0050] The present invention also provides an electronic device, comprising a memory, a processor, and computer program instructions stored in the memory and capable of being executed by the processor. When the processor executes the computer program instructions, the method steps described above can be implemented.

[0051] The present invention also provides a computer-readable storage medium, on which computer program instructions that can be executed by a processor are stored. When the processor executes the computer program instructions, the method steps described above can be implemented.

[0052] Compared with the prior art, the present invention has the following beneficial effects: starting from the perspective of alternative energy and multi-energy complementarity, taking time-of-use electricity prices as incentive signals, constructing a comprehensive demand response model for household and campus micro-energy networks based on optimized operation, and formulating a comprehensive demand response strategy for micro-energy networks based on the coordinated optimization of various energy conversion and energy storage equipment and loads. While meeting the diverse energy needs of users, it reduces the cost of grid operation and dispatching, and realizes precise and scientific control of household photovoltaics. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 For household micro energy network.

[0054] Figure 2 It is a household micro energy network based on energy bus architecture.

[0055] Figure 3 It is the time-of-use electricity price curve.

[0056] Figure 4 Providing power for household photovoltaics.

[0057] Figure 5 Hot water load.

[0058] Figure 6 A comprehensive control strategy for household micro-energy grid considering demand response.

[0059] Figure 7 This is a comprehensive control strategy for household micro-energy networks without considering demand response. DETAILED DESCRIPTION

[0060] The technical solution of the present invention is described in detail below in conjunction with the accompanying drawings.

[0061] The present invention provides a household distributed photovoltaic output optimization and control method, comprising:

[0062] From the perspective of alternative energy use and multi-energy complementarity, a comprehensive demand response model for household micro-energy grid based on optimized operation is constructed;

[0063] Based on the coordinated optimization of various energy conversion and storage equipment and loads, a comprehensive demand response strategy for the micro-energy network is formulated (specifically, the minimum value of the objective function is solved according to the objective function and constraints constructed based on the comprehensive demand response model of the household micro-energy network based on optimized operation).

[0064] The following is the specific implementation process of the present invention.

[0065] Figure 1 The main equipment of a typical household micro-energy network is given, mainly including baseline loads such as lighting and entertainment; loads that can be shifted but not interrupted, such as washing machines, dishwashers, and rice cookers; loads that can be shifted and interrupted, such as electric vehicles; and household energy storage, photovoltaic power generation equipment, and wall-mounted boilers, etc. Based on electricity prices and natural gas prices, the energy management system of the household micro-energy network formulates an optimized household energy management strategy with the goal of minimizing energy costs. Photovoltaic power generation, household energy storage, and wall-mounted boilers can achieve multi-energy complementarity and alternative energy use with power grid power supply, and realize peak load shaving and valley filling by optimizing the power consumption strategy of shiftable loads. The following is a detailed comprehensive demand response model of a household micro-energy network based on optimized operation.

[0066] 1. Load model:

[0067] (1) Power load

[0068] (1.1)Transferable and non-interruptible load

[0069] For loads that can be shifted and cannot be interrupted, such as washing machines, dishwashers, and rice cookers, their working time can be shifted within the time window scheduled by the user, but once the work starts, it is not allowed to be interrupted; for loads that can be shifted and cannot be interrupted, their load model is as follows:

[0070]

[0071] Where: m represents the electrical appliance that can be moved horizontally and cannot be interrupted. is the actual operating power of electrical appliance m at time t; is the rated power of electrical appliance m; is a binary variable, indicating the working state of appliance m at time t. Indicates the start state, otherwise it indicates the shutdown state; The working time necessary for appliance m to complete its task; and They represent the earliest start time and the latest end time of the operation of the appliance m set by the user; v is the start time of the appliance m; the second term in the above formula indicates that the operation of the appliance cannot be interrupted, and the third term in the above formula indicates that the appliance must work within the working time interval set by the user;

[0072] (1.2)Transferable and interruptible load

[0073] The shiftable and interruptible loads include electric vehicles and household energy storage batteries, whose operation can be interrupted and the working hours can be shifted;

[0074] For electric vehicles, the load model is as follows:

[0075]

[0076] Where: is the movable and interruptible load, i.e., the charging power of the electric vehicle at time t; is the maximum charging power of the charging vehicle; It is the time when the electric car arrives home; It’s time for electric cars to go out; SOC t The state of charge of the electric vehicle at time t; W EV is the electric vehicle capacity; η ch is the electric vehicle charging efficiency; EV is the energy loss rate of electric vehicle batteries; SOC min and SOC max They are the minimum and maximum state of charge levels of electric vehicle batteries; SOC dis the expected value of the state of charge of the electric vehicle when the user goes out; the first two items in the above formula respectively indicate that the electric vehicle can be charged only when the user arrives home, and the charging power is not greater than its maximum power constraint; the third and fourth items in the above formula indicate the state of charge of the electric vehicle battery; the last item in the above formula indicates that the state of charge of the electric vehicle when the user goes out is not less than the expected value;

[0077] For household energy storage batteries, the load model is as follows:

[0078]

[0079] Where: η stg(+) is the charging efficiency; S SOC (t) is the state of charge at time t; E stg,rate is the rated capacity of the energy storage battery; S SOC,ini is the initial state of charge; S SOC,min and S SOC,max are the minimum and maximum state of charge, respectively.

[0080] (1.4) Baseline load

[0081] The baseline load mainly includes entertainment equipment such as color TVs, lighting equipment, etc. Its power is fixed, non-adjustable and mandatory.

[0082] (2) Alternative energy load

[0083] Alternative energy loads include wall-mounted boilers, which generate hot water by burning natural gas for family bathing and heating. Wall-mounted boilers can be used in conjunction with electric water heaters. When electricity prices are high, natural gas can be consumed by wall-mounted boilers for heating, thereby reducing electricity consumption. At the same time, it also meets the user's heat load demand and ensures user energy satisfaction. It is one of the effective measures for household users to achieve comprehensive demand response. The wall-mounted boiler load model is expressed as:

[0084]

[0085] Where: and are the natural gas input power and thermal output power of the wall-mounted boiler at time t, is the maximum input power of the wall-mounted boiler; η whs is the heating efficiency of the wall-mounted boiler; in this example, it is taken as 0.9;

[0086] (3) Heat load

[0087] The heat load is modeled as the required hot water load. It is assumed that the water in the water tank can be heated by electric heating or heat generated by gas boilers and gas turbines. It is also assumed that the amount of hot water consumed in the water tank will be supplemented with an equal amount of cold water. The hot water temperature is expressed as:

[0088]

[0089] Where: Indicates the hot water temperature at time t; is the volume of cold water added, i.e. the hot water load at time t; is the hot water load at the initial moment; V is the volume of the water tank; ρ w is the density of water; T cw is the cold water temperature; C w is the specific heat capacity of water; is the required heating power;

[0090] If you want to maintain the hot water at the desired temperature The required heating power Use the following formula to calculate:

[0091]

[0092] 2. Comprehensive demand response model:

[0093] When consuming energy, residential users pay more attention to the energy experience. Comprehensive demand response can optimize and convert multiple energy sources on the demand side, aiming to improve energy efficiency, reduce supply and demand costs, and enhance system flexibility and reliability. Figure 2 As shown in the figure, the household micro-energy grid can be represented by an energy bus architecture, in which the photovoltaic output and the power purchase from the upper power grid are the input ends of the electric bus, the electric load and the water heater are the output ends, and the electric energy storage can interact with the electric bus; the input end of the thermal bus is the water heater and the wall-mounted boiler, and the output end is the thermal load.

[0094] The goal of household comprehensive demand response is to minimize its daily operating costs. The objective function expression is as follows:

[0095]

[0096] The objective function includes five items, namely, electricity purchase cost, gas purchase cost, battery operation cost, electricity sales revenue and electricity sales penalty cost. is the power purchased by the user from the grid at time t, P t is the electricity price at time t, G t is the gas purchase volume at time t, p g is the natural gas price, k1 and k2 are the battery penalty coefficient and the electricity sales penalty coefficient respectively, P sell,t is the electricity sold at time t, p sell,t is the electricity price at time t, The amount of electricity expected to be purchased from the power grid;

[0097] The constraint is the power balance constraint, which is expressed as:

[0098]

[0099] Where: is the photovoltaic output power, is the battery discharge power, is the battery charging power, P sell For selling electricity, is the power of the electric boiler, is the electrical cooling power, The charging power of the charging pile, Aggregate power for other electrical loads; is the thermal power of the wall-mounted boiler, η whs The heating efficiency of the wall-mounted boiler is is the electric power of the electric water heater, η eh is the thermal efficiency of the electric water heater, For heat load. and They are respectively the charging power of electric vehicles, the power of washing machines, dishwashers and rice cookers among the movable and non-interruptible loads, is the baseline load power.

[0100] 3. Example Analysis

[0101] (1) Basic parameters

[0102] Through two types of household micro-energy networks, one with a wall-mounted boiler and one without, the strategy and effect of household users with household distributed photovoltaics participating in comprehensive demand response are discussed and analyzed. The power grid company implements a time-of-use electricity price strategy, such as Figure 3 As shown in , the natural gas price of the natural gas company is a fixed price of 0.31 yuan / kWh. Users participate in comprehensive demand response based on time-of-use electricity prices to minimize their daily operating costs. The energy storage parameters, electric vehicle parameters and shiftable load parameters are shown in Table 1, Table 2 and Table 3 respectively.

[0103] Table 1 Energy storage parameters

[0104]

[0105] Table 2 Electric vehicle parameters

[0106]

[0107] Table 3 Translatable and non-interruptible loads

[0108]

[0109] In addition, the user installed a photovoltaic power generation system with a rated capacity of 2kW. The photovoltaic output and outdoor temperature are shown in Figure 4 . Figure 5The user's daily hot water demand is given.

[0110] (2) Results Analysis

[0111] Figure 6 A comprehensive strategy for household micro-energy grid considering demand response is given. Figure 6 It can be seen that in order to reduce electricity costs, the dishwasher considering the demand response strategy is scheduled to work at 23:00-24:00, the washing machine and rice cooker are scheduled to work at 10:00-11:00, and the electric vehicle charging time is scheduled at 6:00-7:00. The batteries are charged at low or flat times and discharged at peak times to reduce electricity costs.

[0112] Figure 7 The comprehensive strategies of household micro-energy grid without considering demand response are given respectively. Figure 7 It can be seen that without considering the demand response strategy, the working hours of the dishwasher are scheduled at 19:00-20:00, the washing machine is scheduled at 17:00-18:00, the rice cooker is scheduled at 11:00-12:00, and the electric vehicle charging time is scheduled at 6:00-7:00.

[0113] Compared with those that consider demand response, dishwashers and rice cookers that do not consider demand response work during periods of higher electricity prices, resulting in higher electricity costs. In addition, the cost per day for household users who consider demand response is 256.9 yuan, while the cost per day for household users who do not consider demand response is 290.8 yuan. By considering demand response, better economic benefits can be achieved.

[0114] The present invention also provides an electronic device, comprising a memory, a processor, and computer program instructions stored in the memory and capable of being executed by the processor. When the processor executes the computer program instructions, the method steps described above can be implemented.

[0115] The present invention also provides a computer-readable storage medium, on which computer program instructions that can be executed by a processor are stored. When the processor executes the computer program instructions, the method steps described above can be implemented.

[0116] The above are preferred embodiments of the present invention. Any changes made according to the technical solution of the present invention, as long as the resulting functions do not exceed the scope of the technical solution of the present invention, belong to the protection scope of the present invention.

Claims

1. A household distributed photovoltaic output optimization and control method, characterized in that: include: From the perspective of alternative energy use and multi-energy complementarity, a comprehensive demand response model for household micro-energy grid based on optimized operation is constructed; Based on the coordinated optimization of various energy conversion and storage equipment and loads, a comprehensive demand response strategy for micro-energy networks is formulated.

2. The household distributed photovoltaic output optimization and control method according to claim 1 is characterized in that: The comprehensive demand response model of household micro-energy grid based on optimized operation includes: Load model construction; Construction of comprehensive demand response model.

3. The household distributed photovoltaic output optimization and control method according to claim 2 is characterized in that: Load model construction, including: (1) Power load (1.1)Transferable and non-interruptible load The working time of the shiftable and non-interruptible load can be shifted within the time window scheduled by the user, but once the work starts, it is not allowed to be interrupted; for the shiftable and non-interruptible load, its load model is as follows: Where: m represents the electrical appliance that can be moved horizontally and cannot be interrupted. is the actual operating power of electrical appliance m at time t; is the rated power of electrical appliance m; is a binary variable, indicating the working state of appliance m at time t. Indicates the start state, otherwise it indicates the shutdown state; The working time necessary for appliance m to complete its task; and They represent the earliest start time and the latest end time of the operation of the appliance m set by the user; v is the start time of the appliance m; the second term in the above formula indicates that the operation of the appliance cannot be interrupted, and the third term in the above formula indicates that the appliance must work within the working time interval set by the user; (1.2)Transferable and interruptible load The shiftable and interruptible loads include electric vehicles and household energy storage batteries, whose operation can be interrupted and the working hours can be shifted; For electric vehicles, the load model is as follows: Where: is the movable and interruptible load, i.e., the charging power of the electric vehicle at time t; is the maximum charging power of the charging vehicle; It is the time when the electric car arrives home; It’s time for electric cars to go out; SOC t The state of charge of the electric vehicle at time t; W EV is the electric vehicle capacity; η ch is the electric vehicle charging efficiency; EV is the energy loss rate of electric vehicle batteries; SOC min and SOC max They are the minimum and maximum state of charge levels of electric vehicle batteries; SOC d is the expected value of the state of charge of the electric vehicle when the user goes out; the first two items in the above formula respectively indicate that the electric vehicle can be charged only when the user arrives home, and the charging power is not greater than its maximum power constraint; the third and fourth items in the above formula indicate the state of charge of the electric vehicle battery; the last item in the above formula indicates that the state of charge of the electric vehicle when the user goes out is not less than the expected value; For household energy storage batteries, the load model is as follows: Where: η stg(+) is the charging efficiency; S SOC (t) is the state of charge at time t; E stg,rate is the rated capacity of the energy storage battery; S SOC,ini is the initial state of charge; S SOC,min and S SOC,max are the minimum and maximum values ​​of the state of charge, P stg(+) / (-) Charging power / discharging power for energy storage batteries.

4. The household distributed photovoltaic output optimization and control method according to claim 3 is characterized in that: Electrical loads also include: (1.3) Baseline load The baseline load is a fixed-power, mandatory load.

5. The household distributed photovoltaic output optimization and control method according to claim 3 is characterized in that: Load model construction also includes: (2) Alternative energy load Alternative energy loads include wall-mounted boilers, which burn natural gas to produce hot water for household bathing and heating. The wall-mounted boiler load model is expressed as: Where: and are the natural gas input power and thermal output power of the wall-mounted boiler at time t, is the maximum input power of the wall-mounted boiler; η whs It is the heating efficiency of the wall-mounted boiler.

6. The household distributed photovoltaic output optimization and control method according to claim 5, characterized in that: Load model construction also includes: (3) Heat load The heat load is modeled as the required hot water load. It is assumed that the water in the water tank can be heated by electric heating or heat generated by gas boilers and gas turbines. It is also assumed that the amount of hot water consumed in the water tank will be supplemented with an equal amount of cold water. The hot water temperature is expressed as: Where: represents the hot water temperature at time t, Indicates the hot water temperature at the initial moment; is the volume of cold water added, i.e. the hot water load at time t; is the hot water load at the initial moment; V is the volume of the water tank; ρ w is the density of water; T cw is the cold water temperature; C w is the specific heat capacity of water; is the required heating power; If you want to maintain the hot water at the desired temperature The required heating power Use the following formula to calculate:

7. The household distributed photovoltaic output optimization and control method according to claim 6, characterized in that: Comprehensive demand response model construction, including: 1) Objective function: The goal of household comprehensive demand response is to minimize its daily operating costs. The objective function expression is as follows: The objective function includes five items, namely, electricity purchase cost, gas purchase cost, battery operation cost, electricity sales revenue and electricity sales penalty cost. is the power purchased by the user from the grid at time t, P t is the electricity price at time t, G t is the gas purchase volume at time t, p g is the natural gas price, k1 and k2 are the battery penalty coefficient and the electricity sales penalty coefficient respectively, P sell,t is the electricity sold at time t, p sell,t is the electricity price at time t, The amount of electricity expected to be purchased by the power grid.

8. The household distributed photovoltaic output optimization and control method according to claim 7, characterized in that: Comprehensive demand response model building also includes: 2) Constraints The constraint is the power balance constraint, which is expressed as: Where: is the photovoltaic output power, is the discharge power of the energy storage battery, Charging power for energy storage battery, P sell For selling electricity, is the power of the electric boiler, is the electrical cooling power, The charging power of the charging pile, Aggregate power for other electrical loads; is the thermal power of the wall-mounted boiler, η whs The heating efficiency of the wall-mounted boiler is is the electric power of the electric water heater, η eh is the thermal efficiency of the electric water heater, is the heat load, and They are the charging power of electric vehicles, the power of washing machines, dishwashers and rice cookers among the movable and non-interruptible loads, is the baseline load power.

9. An electronic device, characterized in that: The method comprises a memory, a processor and computer program instructions stored in the memory and capable of being executed by the processor. When the processor executes the computer program instructions, the method steps as claimed in any one of claims 1 to 8 can be implemented.

10. A computer-readable storage medium having stored thereon computer program instructions that can be executed by a processor, and when the processor executes the computer program instructions, the method steps according to any one of claims 1 to 8 can be implemented.

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