Energy allocation method, device, electronic equipment and storage medium of electric energy system

Abstract

The present invention discloses an energy allocation method, device, electronic device and storage medium of an electric energy system, and relates to the field of photovoltaic power generation technology. The method comprises: determining the current operation information of the electric energy system when receiving a system energy allocation instruction, the current operation information includes the output power of the photovoltaic power generation equipment and the load demand of the power grid; determining the working parameters of the power supply vehicle cluster based on the load demand and the output power, the working parameters include the working type and the working power, the working type is the discharge type or the charging type, and the working power is the discharge power or the charging power; controlling the photovoltaic power generation equipment to operate based on the output power, and the power supply vehicle cluster to operate based on the working type and the working power, so as to provide the power grid with electric energy that meets the load demand. When receiving the system energy allocation instruction, the charging and discharging type and the charging and discharging power of the power supply vehicle cluster can be determined according to the output power of the photovoltaic power generation equipment and the load demand of the power grid, so as to ensure the stability of the power grid operation and improve the photovoltaic absorption capacity.

Description

Technical Field

[0001] The present invention relates to the field of photovoltaic power generation technology, and in particular to an energy allocation method, device, electronic equipment and storage medium for an electric energy system. Background Art

[0002] With the growth of photovoltaic power generation installed capacity, photovoltaic power generation has become an important part of clean energy. Photovoltaic absorption capacity refers to the ability to transmit the electric energy generated by photovoltaic power generation equipment to the power grid, which will distribute it and supply it to users.

[0003] However, the electricity demand on the user side is dynamically changing, and the power generation capacity of photovoltaic power generation equipment is intermittent and random. The power generation capacity of photovoltaic power generation equipment is greatly affected by factors such as weather and seasons, and the stability of the generated electricity is limited. If the photovoltaic power generation equipment generates more electricity but the power grid's absorption level is low, the "abandonment of light" phenomenon will occur, resulting in a waste of electricity. If the photovoltaic power generation equipment generates less electricity but the power grid's absorption level is high, there will be a shortage of electricity supply, affecting the operational stability of the power grid. Therefore, the energy regulation method between photovoltaic power generation equipment and the power grid is an urgent problem to be solved in the field of photovoltaic power generation. Summary of the invention

[0004] The present invention provides an energy allocation method, device, electronic device and storage medium for an electric energy system, which can determine the charging and discharging type and charging and discharging power of a power supply vehicle cluster according to the output power of photovoltaic power generation equipment and the load demand of the power grid after receiving the system energy allocation instruction, thereby ensuring the stability of the power grid operation and improving the photovoltaic absorption capacity.

[0005] According to one aspect of the present invention, there is provided a method for energy allocation of an electric energy system, the method comprising:

[0006] When receiving the system energy allocation instruction, determining the current operation information of the electric energy system, the current operation information includes the output power of the photovoltaic power generation equipment and the load demand of the power grid;

[0007] Based on the load demand and output power, determine the working parameters of the power supply vehicle cluster, where the working parameters include working type and working power, the working type is a discharge type or a charge type, and the working power is a discharge power or a charge power;

[0008] The photovoltaic power generation equipment is controlled based on the output power, and the power supply vehicle cluster is controlled based on the working type and working power to provide the power grid with electric energy that meets the load demand.

[0009] Optionally, determining the output power of the photovoltaic power generation equipment of the electric energy system includes: determining the initial voltage and initial current of the photovoltaic power generation equipment through an information collector, wherein the initial voltage includes at least one sub-initial voltage, the initial current includes at least one sub-initial current, and the sub-initial voltages and the sub-initial currents correspond to each other one-to-one; determining at least one candidate output power based on at least one sub-initial voltage and at least one sub-initial current; determining the sub-initial current corresponding to the maximum power in at least one candidate output power as the target current, and the sub-initial voltage as the target voltage; and inputting the target current, target voltage, attribute information and environmental information of the photovoltaic power generation equipment into a photovoltaic power generation prediction model for processing to obtain the output power.

[0010] Optionally, determining the load demand of the power grid of the electric energy system includes: determining historical load data of the power grid; processing the historical load data using data classification rules to obtain candidate load data and time identifiers of the candidate load data; inputting the candidate load data and the time identifiers of the candidate load data into a power grid load prediction model for processing to obtain the load demand.

[0011] Optionally, based on load demand and output power, the working parameters of the power supply vehicle cluster are determined, including: determining the power consumption of the power grid based on load demand; determining the power generated by the photovoltaic power generation equipment based on the output power; determining whether the energy difference between the generated power and the consumed power is greater than a preset power value; if the energy difference is greater than the preset power value, determining the working type to be a charging type, and determining the charging power based on the difference between the consumed power and the generated power; if the energy difference is less than or equal to the preset power value, determining the working type to be a discharging type, and determining the discharge power based on the difference between the consumed power and the generated power.

[0012] Optional, output power , where A represents the photovoltaic panel area of ​​the photovoltaic power generation equipment, η represents the conversion efficiency of the photovoltaic panel of the photovoltaic power generation equipment, and G represents the solar radiation intensity. Indicates the loss coefficient of the photovoltaic panel of the photovoltaic power generation equipment; discharge power , charging power ,in, Indicates the number of discharge power supply vehicles in the power supply vehicle cluster, Indicates the number of charging power supply vehicles in the power supply vehicle cluster, Indicates the charging and discharging power of a single power supply vehicle; grid load ,in, represents the basic load of the power grid, Indicates the variable load of the power grid.

[0013] Optionally, before controlling the photovoltaic power generation equipment based on the output power and the power supply vehicle cluster based on the working type and working power, it also includes: determining parameter adjustment requirements and parameter limitation requirements; updating the output power, working type and working power based on the parameter adjustment requirements and parameter limitation requirements.

[0014] Optionally, the parameter adjustment requirement is a first parameter adjustment requirement and / or a second parameter adjustment requirement; determining the parameter adjustment requirement and the parameter limitation requirement includes: determining the parameter limitation conditions based on the stable operating conditions of the power grid, the maximum charging capacity and the maximum discharging capacity of the power supply vehicle cluster; determining the first parameter adjustment requirement according to the parameter adjustment indication input by the user; determining the second parameter adjustment requirement based on the difference between the output power and the reference power and the difference between the load demand and the reference load.

[0015] According to another aspect of the present invention, there is provided an energy allocation device for an electric energy system, the energy allocation device for an electric energy system being used to implement the energy allocation method for an electric energy system in any embodiment of the present invention, the device comprising:

[0016] An acquisition module is used to determine the current operation information of the electric energy system when receiving the system energy allocation instruction, and the current operation information includes the output power of the photovoltaic power generation equipment and the load demand of the power grid;

[0017] A determination module, used to determine the working parameters of the power supply vehicle cluster based on the load demand and the output power, wherein the working parameters include the working type and the working power, the working type is the discharging type or the charging type, and the working power is the discharging power or the charging power;

[0018] The execution module is used to control the photovoltaic power generation equipment based on the output power and the power supply vehicle cluster based on the working type and working power, so as to provide the power grid with electric energy that meets the load demand.

[0019] According to another aspect of the present invention, there is provided an electronic device, the electronic device comprising:

[0020] at least one processor; and a memory communicatively coupled to the at least one processor;

[0021] The memory stores a computer program executable by at least one processor, and the computer program is executed by at least one processor so that the at least one processor can execute the energy allocation method of the electric energy system in any embodiment of the present invention.

[0022] According to another aspect of the present invention, a computer-readable storage medium is provided, which stores computer instructions for implementing the energy allocation method of the electric energy system in any embodiment of the present invention when executed by a processor.

[0023] The energy allocation method of the electric energy system of the present invention includes: upon receiving a system energy allocation instruction, determining the current operating information of the electric energy system, the current operating information including the output power of the photovoltaic power generation equipment and the load demand of the power grid; based on the load demand and the output power, determining the working parameters of the power supply vehicle cluster, wherein the working parameters include the working type and the working power, the working type is the discharge type or the charging type, and the working power is the discharge power or the charging power; controlling the photovoltaic power generation equipment to operate based on the output power and the power supply vehicle cluster to operate based on the working type and the working power, so as to provide the power grid with electric energy that meets the load demand. The technical solution of the present invention can predict the output power of photovoltaic power generation equipment and the load demand of the power grid after receiving the system energy allocation instruction, and determine the charging and discharging type and charging and discharging power of the power supply vehicle cluster according to the output power of the photovoltaic power generation equipment and the load demand of the power grid. For example, when the output power of the photovoltaic power generation equipment is high or the load demand of the power grid is low, the charging work of the power supply vehicle cluster absorbs and stores the electric energy that the power grid cannot consume. When the output power of the photovoltaic power generation equipment is low or the load demand of the power grid is high, the discharging work of the power supply vehicle cluster provides electric energy to the power grid. The power demand of the power grid is maintained by dual energy supply, the stability of the power grid operation is ensured, and the photovoltaic absorption capacity is improved. It solves the problem that when the photovoltaic power generation equipment generates more electric energy but the power grid absorption level is low, the "abandonment of light" phenomenon will occur, resulting in electric energy waste; when the photovoltaic power generation equipment generates less electric energy but the power grid absorption level is high, the phenomenon of insufficient electric energy supply will occur, affecting the operation stability of the power grid, and the like.

[0024] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0026] Figure 1 It is a flowchart of an energy allocation method of an electric energy system provided in Embodiment 1 of the present invention;

[0027] Figure 2 It is a flow chart of an energy allocation method of an electric energy system provided in the second embodiment of the present invention;

[0028] Figure 3 is a structural schematic diagram of an energy allocation device for an electric energy system provided in Embodiment 3 of the present invention;

[0029] Figure 4 It is a structural schematic diagram of an electronic device provided in Embodiment 4 of the present invention. DETAILED DESCRIPTION

[0030] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0031] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0032] Embodiment 1:

[0033] Figure 1 This is a flow chart of an energy allocation method for an electric energy system provided in the first embodiment of the present invention. This embodiment can be applied to improving the photovoltaic absorption capacity, improving the stability of the power grid operation, etc. The method can be executed by the energy allocation device for the electric energy system provided by the present invention. The device can be implemented in the form of hardware and / or software. In a specific embodiment, the device can be integrated in an electronic device. The following embodiments will be described by taking the device integrated in an electronic device as an example. Figure 1 , the method specifically comprises the following steps:

[0034] S101. When receiving a system energy allocation instruction, determine current operation information of the electric energy system.

[0035] The electric energy system of the present invention refers to a system composed of photovoltaic power generation equipment, a power grid and a power supply vehicle cluster. The photovoltaic power generation equipment is used to generate electric energy, the power grid is used to consume electric energy, and the power supply vehicle cluster is used to store electric energy and regulate the stored electric energy (that is, when the electric energy generated by the photovoltaic power generation equipment is insufficient to meet the load demand of the power grid, the stored electric energy is released, and the load demand of the power grid is met by dual energy supply).

[0036] Since the power demand on the grid side and the ability to generate power on the power generation side are dynamic, in order to ensure the stability and energy utilization efficiency of the power system, it is necessary to regularly determine the power demand on the grid side and the ability to generate power on the power generation side. Among them, the system energy allocation instruction can be understood as an update indication of the power demand on the grid side and the ability to generate power on the power generation side. The system energy allocation instruction can be triggered on a timed basis, for example, it can be fifteen minutes, thirty minutes, forty minutes, etc., or it can be triggered by the user based on an interactive device. The current operating information can be understood as the operating parameters of the equipment that can be detected or predicted in the power system. The current operating information includes the output power of the photovoltaic power generation equipment and the load demand of the power grid.

[0037] Specifically, the output power of the photovoltaic power generation equipment is used to determine the ability of the photovoltaic power generation equipment to generate electrical energy. The higher the output power, the more electrical energy is generated. The load demand of the power grid is used to represent the power consumption or required power consumption of users on the power grid side.

[0038] Furthermore, determining the output power of the photovoltaic power generation equipment may be determining the average or maximum output power of the photovoltaic power generation equipment within a period of time (mainly the time period between the last time the system energy allocation instruction was received and the time period between the current time the system energy allocation instruction was received) through a power collector, or the output power of the photovoltaic power generation equipment in the future period predicted by the historical power information of the photovoltaic power generation equipment collected by the power collector, which is not limited in this embodiment. Similarly, determining the load demand of the power grid may be determining the average or maximum load value of the power grid within a period of time (mainly the time period between the last time the system energy allocation instruction was received and the time period between the current time the system energy allocation instruction was received) through a load collector, or the load demand of the power grid in the future period predicted by the historical load information of the power grid collected by the load collector.

[0039] The advantage of this setting is that it can improve the real-time performance of the output power of photovoltaic power generation equipment and the load demand of the power grid, so as to timely adjust the energy distribution method of the power system and improve the stability and energy utilization rate of the power system.

[0040] S102: Determine the working parameters of the power supply vehicle cluster based on load demand and output power.

[0041] Among them, the power supply vehicle cluster can be understood as a device with the ability to store and release electrical energy, and the working parameters can be understood as the information expression of the working mode of the power supply vehicle cluster, including the working type and working power. The working type is the discharge type or the charging type, and the working power is the discharge power or the charging power.

[0042] Specifically, when the working type is the discharge type, the power supply vehicle cluster is in the energy release stage. The power supply vehicle cluster in the energy release stage can provide electric energy to the power grid, and the rate of providing electric energy is related to the discharge power. When the working type is the charging type, the power supply vehicle cluster is in the energy storage stage. The power supply vehicle cluster in the energy storage stage can absorb the electric energy generated by the photovoltaic power generation equipment, and the rate of absorbing electric energy is related to the charging power.

[0043] The advantage of this setting is that the working parameters of the power supply vehicle cluster can be determined according to the output power of the photovoltaic power generation equipment and the load demand of the power grid, and the energy distribution method of the electric energy system can be adjusted in time. When the output power of the photovoltaic power generation equipment is high or the load demand of the power grid is low, the charging work of the power supply vehicle cluster absorbs and stores the electric energy that the power grid cannot consume. When the output power of the photovoltaic power generation equipment is low or the load demand of the power grid is high, the discharge work of the power supply vehicle cluster provides the power grid with part of the electric energy that is lacking in the photovoltaic power generation equipment, thereby improving the stability and energy utilization rate of the electric energy system.

[0044] S103, controlling the photovoltaic power generation equipment to operate based on output power and the power supply vehicle cluster to operate based on working type and working power, so as to provide the power grid with electric energy that meets the load demand.

[0045] For example, assuming that the load demand of the power grid is A, the output power of the photovoltaic power generation equipment is B, the working type of the power supply vehicle cluster is the charging type, and the charging power is C, the photovoltaic power generation equipment is controlled to operate based on the B power to generate electric energy 1, and the power supply vehicle cluster is controlled to absorb electric energy 2 in electric energy 1 based on the C power, and provide electric energy 3 to the power grid. Electric energy 3 is the difference between electric energy 1 and electric energy 2. Electric energy 3 in this embodiment is the electric energy that meets the A load demand.

[0046] The technical solution of this embodiment can predict the output power of photovoltaic power generation equipment and the load demand of the power grid after receiving the system energy allocation instruction, and determine the charging and discharging type and charging and discharging power of the power supply vehicle cluster according to the output power of photovoltaic power generation equipment and the load demand of the power grid. For example, when the output power of photovoltaic power generation equipment is high or the load demand of the power grid is low, the charging work of the power supply vehicle cluster absorbs and stores the electric energy that cannot be absorbed by the power grid. When the output power of photovoltaic power generation equipment is low or the load demand of the power grid is high, the discharging work of the power supply vehicle cluster provides electric energy to the power grid. The power demand of the power grid is maintained by dual energy supply, the stability of the power grid operation is ensured, and the photovoltaic absorption capacity is improved. It solves the problem that when the photovoltaic power generation equipment generates more electric energy but the absorption level of the power grid is low, the "abandonment of light" phenomenon will occur, resulting in electric energy waste; when the photovoltaic power generation equipment generates less electric energy but the absorption level of the power grid is high, the phenomenon of insufficient electric energy supply will occur, affecting the operation stability of the power grid, and the like.

[0047] Embodiment 2:

[0048] Figure 2 This is a flow chart of an energy allocation method for an electric energy system provided in the second embodiment of the present invention. This embodiment can be applied to improving the photovoltaic absorption capacity, improving the stability of the power grid operation, etc. The method can be executed by the energy allocation device for the electric energy system provided by the present invention. The device can be implemented in the form of hardware and / or software. In a specific embodiment, the device can be integrated in an electronic device. The following embodiments will be described by taking the device integrated in an electronic device as an example. Figure 2 , the method specifically comprises the following steps:

[0049] S201. When receiving a system energy allocation instruction, determine current operation information of the electric energy system.

[0050] In this embodiment, the system energy allocation instruction can be understood as an updated indication of the power demand on the grid side and the ability of the power generation side to generate power. The system energy allocation instruction can be triggered by timing or by the user based on an interactive device. The current operating information can be understood as the operating parameters of the equipment that can be detected or predicted in the power system. The current operating information includes the output power of the photovoltaic power generation equipment and the load demand of the power grid. Specifically, the output power of the photovoltaic power generation equipment is used to determine the ability of the photovoltaic power generation equipment to generate power. The higher the output power, the more power is generated. The load demand of the power grid is used to indicate the power consumption or required power consumption of users on the grid side.

[0051] The output power of the photovoltaic power generation equipment and the load demand of the power grid in this embodiment refer to the predicted output power of the photovoltaic power generation equipment and the load demand of the power grid in the future. This embodiment uses the system dynamics method to analyze the dynamic interaction between the photovoltaic power generation equipment, the power supply vehicle cluster and the power grid load, and constructs a dynamic simulation model to simulate the dynamic response of the system under different control strategies, and then predict the future change trend of photovoltaic power generation and power grid load. Specifically, the dynamic simulation model , where x represents the state variable and u represents the control variable. represents the intermediate input and output, y represents the output variable, represents the state equation, It is worth noting that the dynamic simulation model of this embodiment has been recognized by experts in the fields of photovoltaic power generation, power system, vehicle engineering, etc., and has passed the feasibility, key technologies and challenges of the power supply vehicle cluster participating in grid regulation. It has been tested with a large amount of historical data such as photovoltaic power generation, grid load, and power supply vehicle operation data, and can be used to predict future changes in photovoltaic power generation and grid load.

[0052] Considering that the output power of photovoltaic power generation equipment is closely related to factors such as solar radiation and temperature, a photovoltaic power generation equipment model was constructed to simulate the power generation process of photovoltaic power generation equipment. , where A represents the photovoltaic panel area of ​​the photovoltaic power generation equipment, η represents the conversion efficiency of the photovoltaic panel of the photovoltaic power generation equipment, and G represents the solar radiation intensity. Represents the loss coefficient of the photovoltaic panel of the photovoltaic power generation equipment.

[0053] Considering the charging and discharging characteristics, grid connection characteristics and dispatching characteristics of the power supply vehicle cluster, a power supply vehicle cluster model was constructed to simulate the operation process of the power supply vehicle cluster. , charging power ,in, Indicates the number of discharge power supply vehicles in the power supply vehicle cluster, Indicates the number of charging power supply vehicles in the power supply vehicle cluster, Indicates the charging and discharging power of a single power supply vehicle.

[0054] Considering the prediction, dispatching and optimization process of power grid load, a power grid load model is constructed to simulate the changes of power grid load. ,in, represents the basic load of the power grid, Indicates the variable load of the power grid.

[0055] The above three models provide data analysis support for realizing grid connection and regulation optimization control of power supply vehicle clusters in photovoltaic consumption scenarios.

[0056] Determining the output power of a photovoltaic power generation device of an electric energy system includes: determining an initial voltage and an initial current of the photovoltaic power generation device through an information collector, wherein the initial voltage includes at least one sub-initial voltage, the initial current includes at least one sub-initial current, and the sub-initial voltages and the sub-initial currents correspond to each other one-to-one; determining at least one candidate output power based on at least one sub-initial voltage and at least one sub-initial current; determining the sub-initial current corresponding to the maximum power in at least one candidate output power as the target current, and the sub-initial voltage as the target voltage; and inputting the target current, target voltage, attribute information of the photovoltaic power generation device, and environmental information into a photovoltaic power generation prediction model for processing to obtain the output power.

[0057] Under the same external environment, if the output voltage and output current of the photovoltaic cells of the photovoltaic power generation equipment are different, the output power of the photovoltaic power generation equipment will be different. Under certain light and temperature conditions, the photovoltaic cell has a maximum power point (MPP), which is the point where the output power is the highest. In order to achieve the maximum discharge of the photovoltaic power generation equipment, it is necessary to track the maximum power point of the photovoltaic cells of the photovoltaic power generation equipment in real time to ensure that the photovoltaic power generation equipment always outputs at the maximum power.

[0058] Among them, the information collector can be understood as a voltage collector that determines the output voltage of the photovoltaic cell of the photovoltaic power generation equipment and a current collector that determines the output current. The initial voltage can be understood as the output voltage of the photovoltaic cell of the photovoltaic power generation equipment, and the initial current can be understood as the output current of the photovoltaic cell of the photovoltaic power generation equipment. In general, current and voltage are information pairs and have a correlation. The information collector can include multiple voltage collectors and current collectors to collect multiple current and voltage information pairs. The candidate output power can be understood as the power value calculated by each current and voltage information pair. According to the candidate output power and the voltage in the current and voltage information pair, the power-voltage curve of the photovoltaic power generation equipment can be constructed. The peak value in the curve is the maximum power point. The current (i.e., target current) and voltage (i.e., target voltage) corresponding to the maximum power point can be understood as the control parameters that can maximize the power generation of the photovoltaic power generation equipment under this environment.

[0059] Specifically, the attribute information of the photovoltaic power generation equipment can be understood as the photovoltaic panel area, the conversion efficiency of the photovoltaic panel and the loss coefficient of the photovoltaic panel, and the environmental information can be understood as the solar radiation intensity.

[0060] This embodiment can combine historical data and environmental information to predict the output power of photovoltaic power generation equipment in the future and adjust the voltage and current of photovoltaic power generation equipment accordingly. The historical data can be understood as the voltage, current, environmental information and output power that the photovoltaic power generation equipment has used.

[0061] For example, the photovoltaic power generation prediction model can be understood as an algorithm for predicting the output power of the photovoltaic power generation equipment based on the target current, target voltage, property information of the photovoltaic power generation equipment and environmental information. , where A represents the photovoltaic panel area of ​​the photovoltaic power generation equipment, η represents the conversion efficiency of the photovoltaic panel of the photovoltaic power generation equipment, and G represents the solar radiation intensity. represents the loss coefficient of the photovoltaic panel of the photovoltaic power generation equipment, U represents the target voltage, I represents the target current, and the target current, target voltage, attribute information of the photovoltaic power generation equipment and environmental information are input into the photovoltaic power generation prediction model for processing, so as to solve the output power.

[0062] Furthermore, the present embodiment may adopt a maximum power point tracking (MPPT) method to track the maximum power point of the photovoltaic cell in real time, to ensure that the photovoltaic power generation equipment always outputs at the maximum power, and to achieve maximum power generation of the photovoltaic power generation equipment.

[0063] Determining the load demand of the power grid of the electric energy system includes: determining the historical load data of the power grid; processing the historical load data using data classification rules to obtain candidate load data and time identifiers of the candidate load data; inputting the candidate load data and the time identifiers of the candidate load data into the power grid load prediction model for processing to obtain the load demand.

[0064] Among them, the historical load data of the power grid can be understood as the power usage data of the power grid in the past period of time. There is a lot of power usage data in the power grid, and some data is not of reference significance for load forecasting. The data classification rules can be understood as a way to filter out data that is not of reference significance, for example, data that exceeds the preset time is not used, and data that does not match the season is not used. Candidate load data can be understood as the power usage data screened out for load forecasting, and the time identifier of the candidate load data can be understood as the generation time of the candidate load data.

[0065] Specifically, assuming that information is collected every fifteen minutes and only the data from the most recent twenty-four hours is used to predict the load demand of the power grid, the candidate load data is the electricity usage data from the most recent twenty-four hours. The time identifier of the candidate load data is the generation time or collection time of each electricity data in the candidate load data, which can be used to determine the weight of the electricity data in the prediction work. Generally speaking, the more recent the data, the more reference value it has and the higher the weight.

[0066] Exemplarily, the power grid load prediction model may parse the candidate load data and the time identifiers of the candidate load data to predict the load of the power grid in the future (more than fifteen minutes).

[0067] S202: Determine the power consumption of the power grid based on load demand.

[0068] Among them, load demand can be understood as the electric energy required by the user side of the power grid, and the electric energy consumed by the power grid can be understood as the electric energy consumption capacity of the power grid. Under normal circumstances, the load demand on the user side is equal to the electric energy consumed by the power grid or slightly lower than the electric energy consumed by the power grid.

[0069] Specifically, determining the power consumption of the power grid based on load demand can be understood as determining the load demand as the power consumption or determining the sum of the load demand and the preset reserve power as the power consumption. The reserve power is the power consumption during the transmission process of the power grid. The advantage of such a setting is to ensure the stability of the power grid.

[0070] S203: Determine the generated electrical energy of the photovoltaic power generation device based on the output power.

[0071] The generated electric energy of the photovoltaic power generation equipment can be understood as the electric energy that the photovoltaic power generation equipment can generate. Specifically, there is a certain correspondence between the output power of the photovoltaic power generation equipment and the generated electric energy. Based on the output power of the photovoltaic power generation equipment, the generated electric energy of the photovoltaic power generation equipment can be obtained by searching the corresponding relationship between the output power and the generated electric energy.

[0072] S204: Determine whether the electric energy difference between the generated electric energy and the consumed electric energy is greater than a preset electric energy value.

[0073] The preset power value can be understood as a pre-set power redundancy value, which is used to cope with the sudden increase in load of the power grid, so that the power system can provide enough power to the power grid to cope with the short-term increase in load demand on the user side. However, this embodiment will update the energy allocation strategy regularly, so the preset power value will not be very high. The advantage of this setting is that it can reduce the waste of power.

[0074] If the electric energy difference is greater than the preset electric energy value, S205 is executed; if the electric energy difference is less than or equal to the preset electric energy value, S206 is executed.

[0075] The advantage of this setting is that it can improve the working type and working power of the power supply vehicle cluster.

[0076] S205: Determine that the working type is a charging type, and determine the charging power based on the difference between the consumed electric energy and the generated electric energy.

[0077] Specifically, when the electric energy generated by photovoltaic equipment is greater than the electric energy consumed by the power grid, in order to improve the photovoltaic power absorption capacity and avoid energy waste, the power supply vehicle cluster will absorb the electric energy that cannot be absorbed by the power grid. This process is similar to charging the power supply vehicle cluster. Therefore, the working type of the power supply vehicle cluster is charging type, and the charging power is related to the difference between the absorbed electric energy and the generated electric energy.

[0078] For example, the charging power can be understood as the power corresponding to the difference between the consumed power and the generated power. Furthermore, the working power of a single power supply vehicle is certain, and the working number of power supply vehicles is the ratio of the charging power to the working power of a single power supply vehicle.

[0079] S206: Determine that the working type is a discharge type, and determine the discharge power based on the difference between the consumed electric energy and the generated electric energy.

[0080] Specifically, when the electric energy generated by the photovoltaic equipment is less than or equal to the electric energy consumed by the power grid, in order to ensure the stable operation of the power grid, part of the electric energy of the photovoltaic power generation equipment will be provided to the power grid through the power supply vehicle cluster. The sum of this part of the electric energy and the electric energy provided by the photovoltaic power generation equipment can meet the load demand of the power grid. This process is similar to discharging the power supply vehicle cluster. Therefore, the working type of the power supply vehicle cluster is the discharge type, and the discharge power is related to the difference between the consumed electric energy and the generated electric energy.

[0081] Exemplarily, the discharge power can be understood as the power corresponding to the difference between the consumed power and the generated power. Furthermore, the working power of a single power supply vehicle is certain, and the working number of power supply vehicles is the ratio of the discharge power to the working power of a single power supply vehicle.

[0082] S207, controlling the photovoltaic power generation equipment to operate based on output power and the power supply vehicle cluster to operate based on working type and working power, so as to provide the power grid with electric energy that meets the load demand.

[0083] In order to reduce the cost of the electric energy system, improve the utilization rate of electric energy, and reduce the loss of electric energy, this embodiment can also determine the parameter adjustment requirements and parameter restriction requirements before controlling the photovoltaic power generation equipment to operate based on the output power and the power supply vehicle cluster to operate based on the work type and work power; based on the parameter adjustment requirements and parameter restriction requirements, the output power, work type and work power are updated. The photovoltaic power generation equipment is controlled to operate based on the updated output power and the power supply vehicle cluster is controlled to operate based on the updated work type and work power, so as to provide the power grid with electric energy that meets the load demand at low cost and low loss.

[0084] Among them, parameter restriction requirements include but are not limited to restrictions on stable operation of the power grid and restrictions on the charging and discharging capacity of the power supply vehicle. The restrictions on the charging and discharging capacity of the power supply vehicle can be understood as the maximum charging amount and maximum discharging amount of the power supply vehicle cluster. Parameter restriction requirements are necessary conditions for maintaining system stability. The parameter adjustment requirements are the first parameter adjustment requirements and / or the second parameter adjustment requirements. The first parameter adjustment requirements include but are not limited to minimizing the amount of photovoltaic power generation that is not consumed, minimizing the operating cost of the power grid, and minimizing the indoor discomfort time. The second parameter adjustment requirements include but are not limited to the photovoltaic power generation prediction error and the power grid load prediction error. The smaller the error, the more accurate the prediction, and the lower the operating cost and power loss of the power system.

[0085] Specifically, determining parameter adjustment requirements and parameter limitation requirements includes: determining parameter limitation conditions based on the stable operating conditions of the power grid and the maximum charging and discharging amounts of the power supply vehicle cluster; determining the first parameter adjustment requirement based on the parameter adjustment instructions input by the user; and determining the second parameter adjustment requirement based on the difference between the output power and the reference power and the difference between the load demand and the reference load.

[0086] The present application can determine the first parameter adjustment requirement based on the user's parameter adjustment indication. For example, when the user needs to reduce power loss, the first parameter adjustment requirement is determined to minimize the amount of unabsorbed photovoltaic power generation. When the user needs to be more comfortable indoors, the first parameter adjustment requirement is determined to minimize the indoor uncomfortable time.

[0087] In one embodiment, the maximum power point of photovoltaic power generation equipment is tracked in real time to ensure the stable output of photovoltaic power generation units and reduce the volatility of the power grid. For example, a multi-agent collaborative optimization algorithm is used to build a collaborative relationship between multiple agents to achieve dynamic optimization of photovoltaic power generation, power supply vehicle clusters and power grid loads, and ensure safe and stable operation of the power grid. The optimization method of the first parameter adjustment demand indication is:

[0088] , where x represents the decision variable, which represents the parameters or variables that the agent can adjust during the optimization process. In the photovoltaic consumption scenario, the decision variables include the output power of the photovoltaic power generation unit, the charging and discharging strategy of the power supply vehicle, the scheduling of the grid load, etc., and n represents the number of decision variables. represents the objective function, which represents the performance indicator that needs to be minimized during the optimization process, such as minimizing the amount of unabsorbed photovoltaic power generation, minimizing the grid operation cost, minimizing the indoor discomfort time, etc. Indicates the implementation logic of the target table function, which is related to output power, work type and work power. Represents constraints, which represent restrictions or conditions that must be met during the optimization process. In the photovoltaic consumption scenario, the constraints include restrictions on the stable operation of the power grid, restrictions on the charging and discharging capacity of the power supply vehicle, etc., and k represents the number of constraints. When the objective function is successfully optimized, the original output power, work type and work power can be updated based on the output power, work type and work power corresponding to the objective function. When the updated parameters are used, the power system is more stable, with lower resource waste and cost.

[0089] In another embodiment, the output power of photovoltaic power generation equipment and grid load can be accurately predicted and optimized to reduce prediction errors, reasonably dispatch power supply vehicle clusters, and reduce the operation and maintenance costs of power supply vehicles. The optimization method of the second parameter adjustment demand indication is:

[0090] , where y represents the control variable, which represents the decision variable that can be adjusted during the optimization process. In the photovoltaic consumption scenario, the decision variables include the output power of the photovoltaic power generation unit, the charging and discharging strategy of the power supply vehicle, the scheduling of the grid load, etc. represents the number of decision variables, It represents the prediction error, which represents the difference between the prediction model and the actual observation value. In the photovoltaic consumption scenario, the prediction error includes the photovoltaic power generation prediction error, the output power prediction error, the grid load prediction error, etc. represents constraints, which represent the restrictions or conditions that must be met during the optimization process. In the photovoltaic consumption scenario, the constraints include restrictions on the stable operation of the power grid and the restrictions on the charging and discharging capacity of the power supply vehicle. b represents the number of constraints. The line of sight logic representing the prediction error is related to the output power, work type and work power. The original output power, work type and work power can be updated based on the output power, work type and work power corresponding to the minimum error. The power system can be operated with the updated parameters to achieve higher stability and lower resource waste.

[0091] The energy allocation method of the electric energy system of this embodiment includes: upon receiving a system energy allocation instruction, determining the current operating information of the electric energy system, the current operating information including the output power of the photovoltaic power generation equipment and the load demand of the power grid; based on the load demand, determining the power consumption of the power grid; based on the output power, determining the generated power of the photovoltaic power generation equipment; determining whether the energy difference between the generated power and the consumed power is greater than a preset power value; if the energy difference is greater than the preset power value, determining the working type to be a charging type, and determining the charging power based on the difference between the consumed power and the generated power; if the energy difference is less than or equal to the preset power value, determining the working type to be a discharging type, and determining the discharging power based on the difference between the consumed power and the generated power; controlling the photovoltaic power generation equipment to operate based on the output power, and the power supply vehicle cluster to operate based on the working type and working power, so as to provide the power grid with power that meets the load demand. After receiving the system energy allocation instruction, the output power of the photovoltaic power generation equipment and the load demand of the power grid can be determined, and the power grid's consumption power and the photovoltaic power generation equipment's generated power can be determined according to the output power of the photovoltaic power generation equipment and the load demand of the power grid, and then the charging and discharging type and charging and discharging power of the power supply vehicle cluster can be determined. For example, when the output power of the photovoltaic power generation equipment is high or the load demand of the power grid is low, the power supply vehicle cluster can absorb and store the power that the power grid cannot consume. When the output power of the photovoltaic power generation equipment is low or the load demand of the power grid is high, the power supply vehicle cluster can provide power to the power grid through the discharge work. The power grid's power demand is maintained through the dual energy supply method, ensuring the stability of the power grid operation and improving the photovoltaic consumption capacity. This solves the problem that when the photovoltaic power generation equipment generates more power but the power grid's consumption level is low, the "abandonment of light" phenomenon will occur, resulting in power waste, and when the photovoltaic power generation equipment generates less power but the power grid's consumption level is high, there will be a phenomenon of insufficient power supply, affecting the stability of the power grid operation.

[0092] Embodiment three:

[0093] Figure 3 Schematic diagram of the structure of an energy allocation device for an electric energy system provided by the third embodiment of the present invention. Figure 3 As shown, the device includes: an acquisition module 301, a determination module 302 and an execution module 303.

[0094] The acquisition module 301 is used to determine the current operation information of the electric energy system when receiving the system energy allocation instruction. The current operation information includes the output power of the photovoltaic power generation equipment and the load demand of the power grid.

[0095] The determination module 302 is used to determine the working parameters of the power supply vehicle cluster based on the load demand and the output power, wherein the working parameters include the working type and the working power, the working type is the discharging type or the charging type, and the working power is the discharging power or the charging power.

[0096] The execution module 303 is used to control the photovoltaic power generation equipment to operate based on the output power and the power supply vehicle cluster to operate based on the working type and working power, so as to provide the power grid with electric energy that meets the load demand.

[0097] Optionally, the acquisition module 301 is specifically used to determine the initial voltage and initial current of the photovoltaic power generation equipment through an information collector, wherein the initial voltage includes at least one sub-initial voltage, the initial current includes at least one sub-initial current, and the sub-initial voltages and the sub-initial currents correspond to each other one by one; based on at least one sub-initial voltage and at least one sub-initial current, at least one candidate output power is determined; the sub-initial current corresponding to the maximum power in at least one candidate output power is determined as the target current, and the sub-initial voltage is determined as the target voltage; the target current, target voltage, attribute information and environmental information of the photovoltaic power generation equipment are input into the photovoltaic power generation prediction model for processing to obtain the output power.

[0098] Optionally, acquisition module 301 is specifically used to determine historical load data of the power grid; use data classification rules to process the historical load data to obtain candidate load data and time identifiers of the candidate load data; input the candidate load data and the time identifiers of the candidate load data into the power grid load prediction model for processing to obtain load demand.

[0099] Optionally, the determination module 302 is specifically used to determine the power consumption of the power grid based on the load demand; determine the power generated by the photovoltaic power generation equipment based on the output power; determine whether the energy difference between the generated power and the consumed power is greater than a preset power value; if the energy difference is greater than the preset power value, determine that the working type is a charging type, and determine the charging power based on the difference between the consumed power and the generated power; if the energy difference is less than or equal to the preset power value, determine that the working type is a discharging type, and determine the discharging power based on the difference between the consumed power and the generated power.

[0100] Optional, output power , where A represents the photovoltaic panel area of ​​the photovoltaic power generation equipment, η represents the conversion efficiency of the photovoltaic panel of the photovoltaic power generation equipment, and G represents the solar radiation intensity. Indicates the loss coefficient of the photovoltaic panel of the photovoltaic power generation equipment; discharge power , charging power ,in, Indicates the number of discharge power supply vehicles in the power supply vehicle cluster, Indicates the number of charging power supply vehicles in the power supply vehicle cluster, Indicates the charging and discharging power of a single power supply vehicle; grid load ,in, represents the basic load of the power grid, Indicates the variable load of the power grid.

[0101] Optionally, the determination module 302 is also used to determine parameter adjustment requirements and parameter limitation requirements before controlling the photovoltaic power generation equipment based on the output power and the power supply vehicle cluster based on the working type and working power; based on the parameter adjustment requirements and parameter limitation requirements, update the output power, working type and working power.

[0102] Optionally, the parameter adjustment requirement is a first parameter adjustment requirement and / or a second parameter adjustment requirement.

[0103] Optionally, determination module 302 is specifically used to determine parameter restriction conditions based on the stable operating conditions of the power grid, the maximum charging capacity and the maximum discharging capacity of the power supply vehicle cluster; determine the first parameter adjustment requirement according to the parameter adjustment indication input by the user; and determine the second parameter adjustment requirement based on the difference between the output power and the reference power and the difference between the load demand and the reference load.

[0104] The energy allocation device of the electric energy system provided in the embodiment of the present invention can execute the energy allocation method of the electric energy system provided in any embodiment of the present invention, and has the functional modules and beneficial effects corresponding to the execution method.

[0105] Embodiment 4:

[0106] Figure 4 : is a schematic diagram of the structure of an electronic device provided by Embodiment 4 of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0107] like Figure 4As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (also called random access memory, RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12 and the RAM 13 are connected to each other through a bus 14. The input / output (I / O) interface 15 is also connected to the bus 14.

[0108] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0109] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as an energy allocation method for an electric energy system.

[0110] In some embodiments, the energy allocation method of the electric energy system may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the energy allocation method of the electric energy system described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the energy allocation method of the electric energy system in any other appropriate manner (e.g., by means of firmware).

[0111] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0112] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0113] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, device, or apparatus. A computer-readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media may include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0114] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0115] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server) or a computing system that includes middleware components (e.g., an application server) or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein) or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0116] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0117] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0118] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. An energy allocation method for an electric energy system, characterized in that: include: When receiving the system energy allocation instruction, determining the current operation information of the electric energy system, the current operation information including the output power of the photovoltaic power generation equipment and the load demand of the power grid; Based on the load demand and the output power, determine the working parameters of the power supply vehicle cluster, wherein the working parameters include working type and working power, the working type is a discharge type or a charge type, and the working power is a discharge power or a charge power; Controlling the photovoltaic power generation equipment to operate based on the output power and the power supply vehicle cluster to operate based on the working type and the working power, so as to provide the power grid with electric energy that meets the load demand; Before controlling the photovoltaic power generation equipment to operate based on the output power and the power supply vehicle cluster to operate based on the working type and the working power, the method further includes: Determine parameter adjustment requirements and parameter limitation requirements, wherein the parameter limitation requirements include limitations on stable operation of the power grid and limitations on the charging and discharging capacity of the power supply vehicle, the limitations on the charging and discharging capacity of the power supply vehicle are the maximum charging amount and the maximum discharging amount of the power supply vehicle cluster, the parameter adjustment requirements are the first parameter adjustment requirements and / or the second parameter adjustment requirements, the first parameter adjustment requirements include minimizing the amount of photovoltaic power generation that is not consumed, minimizing the power grid operation cost, and minimizing the indoor discomfort time, and the second parameter adjustment requirements include photovoltaic power generation prediction error and power grid load prediction error; Based on the parameter adjustment requirement and the parameter limitation requirement, the output power, the operation type and the operation power are updated.

2. The method according to claim 1, characterized in that The step of determining the output power of the photovoltaic power generation equipment of the electric energy system comprises: Determine the initial voltage and initial current of the photovoltaic power generation device through an information collector, wherein the initial voltage includes at least one sub-initial voltage, the initial current includes at least one sub-initial current, and the sub-initial voltages and the sub-initial currents correspond to each other one by one; determining at least one candidate output power based on the at least one sub-initial voltage and the at least one sub-initial current; Determine that a sub-initial current corresponding to a maximum power among the at least one candidate output power is a target current, and a sub-initial voltage is a target voltage; The target current, the target voltage, the property information of the photovoltaic power generation equipment and the environmental information are input into a photovoltaic power generation prediction model for processing to obtain the output power.

3. The method according to claim 1, characterized in that Determining the load demand of the power grid of the electric energy system includes: determining historical load data for the power grid; Processing the historical load data using data classification rules to obtain candidate load data and time identifiers of the candidate load data; The candidate load data and the time identifier of the candidate load data are input into a power grid load forecasting model for processing to obtain the load demand.

4. The method according to claim 1, characterized in that: The determining the working parameters of the power supply vehicle cluster based on the load demand and the output power includes: Based on the load demand, determining the power consumption of the power grid; Based on the output power, determining the generated electrical energy of the photovoltaic power generation device; Determining whether the electric energy difference between the generated electric energy and the consumed electric energy is greater than a preset electric energy value; If the electric energy difference is greater than the preset electric energy value, determining the working type as a charging type, and determining the charging power based on the difference between the consumed electric energy and the generated electric energy; If the electric energy difference is less than or equal to the preset electric energy value, the working type is determined to be a discharge type, and the discharge power is determined based on the difference between the consumed electric energy and the generated electric energy.

5. The method according to claim 1, characterized in that The output power , where A represents the photovoltaic panel area of ​​the photovoltaic power generation equipment, η represents the conversion efficiency of the photovoltaic panel of the photovoltaic power generation equipment, and G represents the solar radiation intensity. Represents the loss coefficient of the photovoltaic panel of the photovoltaic power generation equipment; The discharge power , the charging power ,in, Indicates the number of discharge power supply vehicles in the power supply vehicle cluster, Indicates the number of charging power supply vehicles in the power supply vehicle cluster, Indicates the charging and discharging power of a single power supply vehicle; The grid load ,in, represents the basic load of the power grid, Indicates the variable load of the power grid.

6. The method according to claim 1, characterized in that The parameter adjustment requirement is a first parameter adjustment requirement and / or a second parameter adjustment requirement; The determining of parameter adjustment requirements and parameter limitation requirements includes: Determining the parameter restriction condition based on the stable operation condition of the power grid and the maximum charge capacity and maximum discharge capacity of the power supply vehicle cluster; Determining the first parameter adjustment requirement according to the parameter adjustment instruction input by the user; The second parameter adjustment requirement is determined based on the difference between the output power and the reference power and the difference between the load requirement and the reference load.

7. An energy allocation device for an electric energy system, characterized in that: The energy allocation device of the electric energy system is used to implement the energy allocation method of the electric energy system according to any one of claims 1 to 6, and the energy allocation device of the electric energy system comprises: An acquisition module, configured to determine current operation information of the electric energy system upon receiving a system energy allocation instruction, wherein the current operation information includes the output power of the photovoltaic power generation equipment and the load demand of the power grid; A determination module, configured to determine working parameters of a power supply vehicle cluster based on the load demand and the output power, wherein the working parameters include a working type and a working power, the working type is a discharging type or a charging type, and the working power is a discharging power or a charging power; An execution module, used for controlling the photovoltaic power generation equipment to operate based on the output power and the power supply vehicle cluster to operate based on the working type and the working power, so as to provide the power grid with electric energy that meets the load demand; The determination module is also used to determine parameter adjustment requirements and parameter limitation requirements before controlling the photovoltaic power generation equipment based on the output power and the power supply vehicle cluster to operate based on the working type and the working power, wherein the parameter limitation requirements include limitations on stable operation of the power grid and limitations on the charging and discharging capacity of the power supply vehicle, and the limitations on the charging and discharging capacity of the power supply vehicle are the maximum charging amount and the maximum discharging amount of the power supply vehicle cluster. The parameter adjustment requirements are the first parameter adjustment requirements and / or the second parameter adjustment requirements. The first parameter adjustment requirements include minimizing the amount of photovoltaic power generation that is not absorbed, minimizing the power grid operation cost, and minimizing the indoor discomfort time. The second parameter adjustment requirements include photovoltaic power generation prediction errors and power grid load prediction errors. Based on the parameter adjustment requirements and the parameter limitation requirements, the output power, the working type, and the working power are updated.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively coupled to the at least one processor; The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the energy allocation method of the electric energy system described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the energy allocation method of the electric energy system described in any one of claims 1 to 6 when executed.

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