Control method and device of household photovoltaic system, electronic equipment and storage medium

Abstract

The invention provides a control method and device for a household photovoltaic system, electronic equipment and a storage medium, and the control method comprises the following steps: optimizing # imgabs1 # and # imgabs2 # through employing an optimization model for the total household electricity cost # imgabs0 #, enabling the value of the total household electricity cost # imgabs0 # to be minimum, carrying out the adjustment of the total electricity consumption of electricity consumption equipment in all time periods, and enabling the adjustment of the total electricity consumption of the electricity consumption equipment # imgabs1 # and # imgabs2 # of the electricity consumption equipment # imgabs0 #. And adjusting charging and discharging of the energy storage battery in all time periods. According to the control method, the total cost of the household photovoltaic system can be minimized.

Description

Technical Field

[0001] The present invention relates to the field of photovoltaic technology, and in particular to a control method, device, electronic equipment and storage medium for a household photovoltaic system. Background Art

[0002] With the development of technology, household photovoltaic systems have become popular. Generally, household photovoltaic systems include: photovoltaic panels, power-consuming equipment, energy storage batteries and grid connection equipment. The grid connection equipment is used to connect to the grid. The electric energy generated by the photovoltaic panels can be provided to the power-consuming equipment and the energy storage batteries, and can also be sold to the grid through the grid connection equipment. The electric energy in the energy storage batteries can be provided to the power-consuming equipment, and can also be sold to the grid through the grid connection equipment. The grid connection equipment can obtain electric energy from the grid and provide it to the power-consuming equipment and the energy storage batteries.

[0003] Here, the power generation of photovoltaic panels is volatile, random and intermittent at different times, and there are certain limitations in directly calling the current power to provide power to the load. The reason is that: on the one hand, when the photovoltaic panel is fully powered, a large amount of excess power cannot be fully utilized; on the other hand, when the photovoltaic panel is insufficiently powered, it is necessary to use the power of the grid to enable the electrical equipment to work normally. Controlling the energy storage battery and performing reasonable charging and discharging can, on the one hand, store the excess distributed power and transfer it to the time when the power is insufficient or the electricity price is high; on the other hand, the energy storage battery can use its own characteristic of storing power to achieve the effect of low storage and high generation, that is, charging when the electricity price is low and discharging when the electricity price is high, thereby reducing the user's electricity bill.

[0004] Therefore, how to regulate the charging and discharging of energy storage batteries to minimize the total cost of household photovoltaic systems has become an urgent problem to be solved. Summary of the invention

[0005] The object of the present invention is to provide a control method, device, electronic equipment and storage medium for a household photovoltaic system.

[0006] In order to achieve one of the above-mentioned invention purposes, an embodiment of the present invention provides a control method for a household photovoltaic system, wherein the household photovoltaic system comprises: a photovoltaic panel, a power-consuming device, an energy storage battery and a grid connection device, wherein the grid connection device is used to connect to the grid; the electric energy generated by the photovoltaic panel can be provided to the power-consuming device and the energy storage battery, and can also be sold to the grid through the grid connection device; the electric energy in the energy storage battery can be provided to the power-consuming device, and can also be sold to the grid through the grid connection device; the grid connection device can obtain electric energy from the grid and provide it to the power-consuming device and the energy storage battery; comprising the following steps: the total cost of household electricity consumption Where n is a natural number, f t is the electricity price in the tth period, f PV is the unit price of photovoltaic panel power generation subsidy, and the duration of each period is is the amount of electricity purchased by the household from the grid during the tth period; When the household purchases electricity from the grid, When the household sells electricity to the grid; is the total power consumption of power-consuming devices in the tth period, is the power output of the photovoltaic panel in the tth period, is the discharge amount of the energy storage battery in the tth period. When When the energy storage battery receives and stores electrical energy, the constraints are: SOC min ≤SOC t ≤SOC max , where P b,max , SOC min and SOC max are constants, P b,max >0,0 <SOC min <SOC max ; The dynamic update of the energy storage battery state of charge SOC is: η is the charging efficiency, η ch is the discharge efficiency, E b,max is the total capacity of the energy storage battery; and Optimize to minimize the total household electricity cost C, and based on The total power consumption of the power-consuming equipment in all periods is adjusted, and based on The charging and discharging of the energy storage battery is regulated in all time periods.

[0007] As a further improvement of an implementation manner of the present invention, the optimization model is linear programming.

[0008] As a further improvement of an implementation manner of the present invention, the optimization model is dynamic programming.

[0009] As a further improvement of an embodiment of the present invention, the optimization model is a genetic algorithm.

[0010] The embodiment of the present invention also provides a control device for a household photovoltaic system, wherein the household photovoltaic system comprises: a photovoltaic panel, a power-consuming device, an energy storage battery and a grid connection device, wherein the grid connection device is used to connect to the grid; the electric energy generated by the photovoltaic panel can be provided to the power-consuming device and the energy storage battery, and can also be sold to the grid through the grid connection device; the electric energy in the energy storage battery can be provided to the power-consuming device, and can also be sold to the grid through the grid connection device; the grid connection device can obtain electric energy from the grid and provide it to the power-consuming device and the energy storage battery; and comprises the following modules: a model creation module for calculating the total cost of household electricity consumption Where n is a natural number, f t is the electricity price in the tth period, f PV is the unit price of photovoltaic panel power generation subsidy, and the duration of each period is is the amount of electricity purchased by the household from the grid during the tth period; t G >0, the household purchases electricity from the grid. When the household sells electricity to the grid; is the total power consumption of power-consuming devices in the tth period, is the power output of the photovoltaic panel in the tth period, is the discharge amount of the energy storage battery in the tth period. When When the energy storage battery receives and stores electrical energy, the constraints are: SOC min ≤SOC t ≤SOC max , where P b,max , SOC min and SOC max are constants, P b,max >0,0 <SOC min <SOC max ; The dynamic update of the energy storage battery state of charge SOC is: η is the charging efficiency, η ch is the discharge efficiency, E b,max is the total capacity of the energy storage battery; the optimization module is used to use the optimization model to and Optimize to minimize the total household electricity cost C, and based on The total power consumption of the power-consuming equipment in all periods is adjusted, and based on The charging and discharging of the energy storage battery is regulated in all time periods.

[0011] As a further improvement of an implementation manner of the present invention, the optimization model is linear programming.

[0012] As a further improvement of an implementation manner of the present invention, the optimization model is dynamic programming.

[0013] As a further improvement of an embodiment of the present invention, the optimization model is a genetic algorithm.

[0014] An embodiment of the present invention further provides an electronic device, comprising: a memory, used to store executable instructions; and a processor, used to implement the above control method when executing the executable instructions stored in the memory.

[0015] The embodiment of the present invention further provides a storage medium storing executable instructions for causing a processor to execute the above control method.

[0016] Compared with the prior art, the technical effect of the present invention is that: the embodiment of the present invention provides a control method, device, electronic device and storage medium for a household photovoltaic system, the control method comprises the following steps: the total household electricity cost Where n is a natural number, f t is the electricity price in the tth period, f PV is the unit price of photovoltaic panel power generation subsidy, and the duration of each period is is the amount of electricity purchased by the household from the grid during the tth period; and Optimize to minimize the total household electricity cost C, and based on The total power consumption of the power-consuming equipment in all periods is adjusted, and based on The charging and discharging of the energy storage battery is regulated in all time periods. The control method can minimize the total cost of the household photovoltaic system. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a flow chart of a control method of a household photovoltaic system in an embodiment of the present invention. DETAILED DESCRIPTION

[0018] The present invention will be described in detail below in conjunction with the various embodiments shown in the accompanying drawings. However, these embodiments do not limit the present invention, and any structural, methodological, or functional changes made by a person skilled in the art based on these embodiments are all within the scope of protection of the present invention.

[0019] As used herein, terms indicating spatial relative positions such as "upper," "above," "lower," and "below" are used for the purpose of convenience to describe the relationship of one unit or feature relative to another unit or feature as shown in the accompanying drawings. Terms of spatial relative position may be intended to include different orientations of the device in use or operation in addition to the orientation shown in the drawings. For example, if the device in the figure is turned over, units described as being "below" or "beneath" other units or features will be located "above" the other units or features. Thus, the exemplary term "below" can encompass both above and below orientations. The device may be oriented in other ways (rotated 90 degrees or in other orientations), and the spatially relative descriptors used herein interpreted accordingly.

[0020] Embodiment 1 of the present invention provides a control method for a household photovoltaic system, wherein the household photovoltaic system comprises: a photovoltaic panel, a power-consuming device, an energy storage battery and a grid connection device, wherein the grid connection device is used to connect to a grid; the electric energy generated by the photovoltaic panel can be provided to the power-consuming device and the energy storage battery, and can also be sold to the grid through the grid connection device; the electric energy in the energy storage battery can be provided to the power-consuming device, and can also be sold to the grid through the grid connection device; the grid connection device can obtain electric energy from the grid and provide it to the power-consuming device and the energy storage battery;

[0021] Here, the photovoltaic panel is generally installed on the roof of the house, and when there is sunlight, the photovoltaic panel can generate electricity. The power-consuming equipment is generally household appliances, such as lighting, washing machines, air conditioners, etc. The energy storage battery can be a lithium battery or a lead-acid battery, etc. The grid connection equipment can include a transformer, an inverter, etc.

[0022] like Figure 1 As shown, the following steps are included:

[0023] Step 101: Total household electricity costs Where n is a natural number, f t is the electricity price in the tth period, f PV is the unit price of photovoltaic panel power generation subsidy, and the duration of each period is is the amount of electricity purchased by the household from the grid during the tth period; When the household purchases electricity from the grid, When the household sells electricity to the grid; is the total power consumption of power-consuming devices in the tth period, is the power output of the photovoltaic panel in the tth period, is the discharge amount of the energy storage battery in the tth period. When When the energy storage battery receives and stores electrical energy, the constraints are: SOC min ≤SOC t ≤SOC max , where P b,max , SOC min and SOC max are constants, P b,max >0,0 <SOC min <SOC max ; The dynamic update of the energy storage battery state of charge SOC is: η is the charging efficiency, η ch is the discharge efficiency, E b,max is the total capacity of the energy storage battery; here, n can be 24, so the length of each period is one hour. Here, in practice, the electricity price is generally calculated according to peak electricity consumption and off-peak electricity consumption. During peak electricity consumption, the electricity price is higher, and during off-peak electricity consumption, the electricity price is lower. The full spelling of SOC is State of Charge.

[0024] Optional, in, For loads that can be moved horizontally, such as washing machines and water heaters, their operating time can be adjusted according to the electricity price. Indicates a normal non-movable load.

[0025] Step 101: Use the optimization model to and Optimize to minimize the total household electricity cost C, and based on The total power consumption of the power-consuming equipment in all periods is adjusted, and based on The charging and discharging of the energy storage battery is regulated in all time periods.

[0026] Here, the control method uses an intelligent scheduling algorithm to automatically adjust household electricity consumption and energy storage equipment operation according to the electricity price period and photovoltaic power generation to maximize cost-effectiveness. In addition, the electricity generated by photovoltaic panels can be used to meet household electricity needs as much as possible, reduce dependence on the power grid, and enhance energy security. It is also possible to maximize the revenue from electricity sales through the reasonable scheduling of excess electricity from photovoltaic panels, and reduce fossil energy consumption and corresponding carbon emissions by increasing the proportion of renewable energy use. In summary, this system integrates photovoltaic power generation and household energy storage systems, and cooperates with intelligent management and scheduling technologies to achieve efficient management and economic optimization of household energy.

[0027] In this embodiment, the optimization model is linear programming.

[0028] In this embodiment, the optimization model is dynamic programming.

[0029] In this embodiment, the optimization model is a genetic algorithm.

[0030] In the inventor's experiment, the power output of the photovoltaic panel used was They are: [0,0,0,0,0,0,2,3,4,4.5,5,4.5,4,3,2,1,0,0,0,0,0,0,0,0], in kWh (kilowatt-hour); the total power consumption of internal power-consuming devices They are: [0.5,0.5,0.5,0.5,0.5,0.5,1,1.5,2,2.5,2.5,2,1.5,1,1,1,1,1,1,1,1,1,0.5,0.5], the unit is kWh (kilowatt-hour); the electricity price f t They are: 0.2 yuan / kWh during peak hours (6:00-22:00), 0.1 yuan / kWh during off-peak hours (22:00-6:00), photovoltaic subsidy (yuan / kWh): 0.05 yuan / kWh;

[0031] Calculation process

[0032] The ordinary plan assumes that all household electricity needs are purchased from the grid, without considering the impact of photovoltaic power generation and energy storage systems. Peak electricity charges (6:00-22:00, 16 hours), total demand is 1+1.5+2+2.5+2.5+2+1.5+1+1+1+1+1=18, the cost is 18kWh×0.2 ​​yuan / kWh=3.6 yuan; off-peak electricity charges (22:00-6:00, 8 hours), total demand is 0.5+0.5+0.5+0.5+0.5+0.5=3kWh, the cost is 3kWh×0.1 yuan / kWh=0.3 yuan3kWh×0.1 yuan / kWh=0.3 yuan; the total cost of the ordinary plan: 3.6 yuan + 0.3 yuan = 3.9

[0033] This control method uses photovoltaic power generation to meet electricity demand first. If there is surplus power, it is sold at the peak price and photovoltaic subsidies are taken into account. Comparison of photovoltaic power generation and demand (6:00-22:00), the total power generation is 2+3+4+4.5+5+4.5+4+3+2+1=33kWh, the total demand is 18kWh, the surplus power is 33kWh-18kWh=15, the surplus power sales income and subsidies include: power sales income 15kWh×0.2 ​​yuan / kWh=3 yuan, photovoltaic subsidy 33kWh×0.05 yuan / kWh=1.65 yuan, the total income of the optimization plan is 3 yuan + 1.65 yuan = 4.65 yuan.

[0034] In summary, the total cost of the non-optimized solution is 3.9 yuan, and the total income of this control method is 4.65 yuan.

[0035] Embodiment 2 of the present invention provides a control device for a household photovoltaic system, wherein the household photovoltaic system comprises: a photovoltaic panel, a power-consuming device, an energy storage battery and a grid connection device, wherein the grid connection device is used to connect to a grid; the electric energy generated by the photovoltaic panel can be provided to the power-consuming device and the energy storage battery, and can also be sold to the grid through the grid connection device; the electric energy in the energy storage battery can be provided to the power-consuming device, and can also be sold to the grid through the grid connection device; the grid connection device can obtain electric energy from the grid and provide it to the power-consuming device and the energy storage battery; and comprises the following modules:

[0036] Model creation module for total household electricity costs Where n is a natural number, f t is the electricity price in the tth period, f PV is the unit price of photovoltaic panel power generation subsidy, and the duration of each period is is the amount of electricity purchased by the household from the grid during the tth period; When the household purchases electricity from the grid, When the household sells electricity to the grid; is the total power consumption of power-consuming devices in the tth period, is the power output of the photovoltaic panel in the tth period, is the discharge amount of the energy storage battery in the tth period. When When the energy storage battery receives and stores electrical energy, the constraints are: SOC min ≤SOC t ≤SOC max , where P b,max , SOC min and SOC max are constants, P b,max >0,0 <SOC min <SOC max ; The dynamic update of the energy storage battery state of charge SOC is: η is the charging efficiency, η ch is the discharge efficiency, E b,max is the total capacity of the energy storage battery;

[0037] Optimization module, used to use optimization models to and Optimize to minimize the total household electricity cost C, and based on The total power consumption of the power-consuming equipment in all periods is adjusted, and based on The charging and discharging of the energy storage battery is regulated in all time periods.

[0038] In this embodiment, the optimization model is linear programming.

[0039] In this embodiment, the optimization model is dynamic programming.

[0040] In this embodiment, the optimization model is a genetic algorithm.

[0041] A third embodiment of the present invention provides an electronic device, comprising: a memory for storing executable instructions; and a processor for implementing the control method in the first embodiment when executing the executable instructions stored in the memory.

[0042] Embodiment 4 of the present invention provides a storage medium storing executable instructions for causing a processor to execute and implement the control method in embodiment 1.

[0043] It should be understood that although this specification is described according to implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each implementation mode may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

[0044] The series of detailed descriptions listed above are only specific descriptions of feasible implementation methods of the present invention. They are not intended to limit the scope of protection of the present invention. Any equivalent implementation methods or changes that do not deviate from the technical spirit of the present invention should be included in the scope of protection of the present invention.

Claims

1. A control method for a household photovoltaic system, the household photovoltaic system comprising: Photovoltaic panels, power-consuming devices, energy storage batteries and grid connection devices, wherein the grid connection device is used to connect to the grid; the electric energy generated by the photovoltaic panels can be provided to the power-consuming devices and the energy storage batteries, and can also be sold to the grid through the grid connection device; the electric energy in the energy storage batteries can be provided to the power-consuming devices, and can also be sold to the grid through the grid connection device; the grid connection device can obtain electric energy from the grid and provide it to the power-consuming devices and the energy storage batteries; characterized in that it includes the following steps: Total household electricity costs Where n is a natural number, f t is the electricity price in the tth period, f PV is the unit price of photovoltaic panel power generation subsidy, and the duration of each period is is the amount of electricity purchased by the household from the grid during the tth period; When the household purchases electricity from the grid, When the household sells electricity to the grid; is the total power consumption of power-consuming devices in the tth period, is the power output of the photovoltaic panel in the tth period, is the discharge amount of the energy storage battery in the tth period. When When the energy storage battery receives and stores electrical energy, the constraints are: SOC min ≤SOC t ≤SOC max , where P b,max , SOC min and SOC max are constants, P b,max >0,0 <SOC min <SOC max ; The dynamic update of the energy storage battery state of charge SOC is: η is the charging efficiency, η ch is the discharge efficiency, E b,max is the total capacity of the energy storage battery; Using optimization models and Optimize to minimize the total household electricity cost C, and based on The total power consumption of the power-consuming equipment in all periods is adjusted, and based on The charging and discharging of the energy storage battery is regulated in all time periods.

2. The control method according to claim 1, characterized in that: The optimization model is linear programming.

3. The control method according to claim 1, characterized in that: The optimization model is dynamic programming.

4. The control method according to claim 1, characterized in that: The optimization model is a genetic algorithm.

5. A control device for a household photovoltaic system, the household photovoltaic system comprising: Photovoltaic panels, power-consuming devices, energy storage batteries and grid connection devices, wherein the grid connection device is used to connect to the grid; the electric energy generated by the photovoltaic panels can be provided to the power-consuming devices and the energy storage batteries, and can also be sold to the grid through the grid connection device; the electric energy in the energy storage batteries can be provided to the power-consuming devices, and can also be sold to the grid through the grid connection device; the grid connection device can obtain electric energy from the grid and provide it to the power-consuming devices and the energy storage batteries; characterized in that it includes the following modules: Model creation module for total household electricity costs Where n is a natural number, f t is the electricity price in the tth period, f PV is the unit price of photovoltaic panel power generation subsidy, and the duration of each period is is the amount of electricity purchased by the household from the grid during the tth period; When the household purchases electricity from the grid, When the household sells electricity to the grid; is the total power consumption of power-consuming devices in the tth period, is the power output of the photovoltaic panel in the tth period, is the discharge amount of the energy storage battery in the tth period. When When the energy storage battery receives and stores electrical energy, the constraints are: SOC min ≤SOC t ≤SOC max , where P b,max , SOC min and SOC max are constants, P b,max >0,0 <SOC min <SOC max ; The dynamic update of the energy storage battery state of charge SOC is: η is the charging efficiency, η ch is the discharge efficiency, E b,max is the total capacity of the energy storage battery; Optimization module, used to use optimization models to and Optimize to minimize the total household electricity cost C, and based on The total power consumption of the power-consuming equipment in all periods is adjusted, and based on The charging and discharging of the energy storage battery is regulated in all time periods.

6. The control device according to claim 5, characterized in that: The optimization model is linear programming.

7. The control device according to claim 5, characterized in that: The optimization model is dynamic programming.

8. The control device according to claim 5, characterized in that: The optimization model is a genetic algorithm.

9. An electronic device, characterized in that: include: A memory for storing executable instructions; A processor, configured to implement the control method according to any one of claims 1 to 4 when executing the executable instructions stored in the memory.

10. A storage medium, characterized in that: Executable instructions are stored, which are used to cause the processor to execute and implement the control method described in any one of claims 1 to 4.

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