Photovoltaic energy storage system control device and method

Abstract

The invention discloses a photovoltaic energy storage system control device and method, and relates to the field of photovoltaic power generation and energy storage, the photovoltaic energy storage system control device comprises a microprocessor, a data acquisition module and a time control module; the data acquisition module is used for acquiring a first parameter set and a second parameter set and sending the first parameter set and the second parameter set to the microprocessor, and the time control module is used for acquiring current time according to a built-in clock, determining a power grid time period to which the current time belongs according to a preset judgment rule and sending the determined power grid time period to the microprocessor. The power grid time period to which the current time belongs is sent to the microprocessor, and the power grid time period to which the current time belongs comprises a peak time period, a valley time period and a flat time period; and the microprocessor is used for formulating a control strategy according to the first parameter set, the second parameter set and the power grid time period to which the current time belongs, and controlling the photovoltaic energy storage system through the control strategy. According to the invention, the energy utilization efficiency and economic benefits of the photovoltaic energy storage system are improved.

Description

Technical Field

[0001] The present application relates to the field of photovoltaic power generation, and in particular to a photovoltaic energy storage system control device and method. Background Art

[0002] With the increasing proportion of renewable energy sources such as photovoltaics and wind power in traditional power systems, and the rapid development and widespread application of smart microgrid technology, research on control methods for photovoltaic energy storage systems has gradually become a key focus in academia and engineering. The core goal of photovoltaic energy storage system control methods is to achieve the storage and rational distribution of photovoltaic power through effective management of the energy storage system, thereby alleviating the impact of the intermittent and volatile photovoltaic power generation on the power grid, increasing the utilization of renewable energy, and optimizing the efficiency of power resources.

[0003] However, existing photovoltaic energy storage system control methods still have certain functional limitations, mainly focusing on basic energy storage and release mechanisms, and lacking comprehensive data analysis and dynamic response capabilities. Summary of the Invention

[0004] The purpose of this application is to provide a photovoltaic energy storage system control device and method that can meet the diverse needs of users.

[0005] To achieve the above objectives, this application provides the following solutions:

[0006] In a first aspect, the present application provides a photovoltaic energy storage system control device, the photovoltaic energy storage system control device comprising: a microprocessor, a data acquisition module, and a time control module, wherein the microprocessor is connected to the data acquisition module and the time control module respectively:

[0007] The data acquisition module is configured to obtain a first parameter set and a second parameter set, and send the first parameter set and the second parameter set to the microprocessor, wherein the first parameter set includes sunlight intensity data and photovoltaic system installed capacity, and the second parameter set includes holiday data, historical weather data, and historical user load demand power;

[0008] The time control module is used to obtain the current time according to the built-in clock, determine the grid time period to which the current time belongs according to a preset judgment rule, and send the grid time period to which the current time belongs to the microprocessor, where the grid time period to which the current time belongs includes a peak time period, a valley time period, and a normal time period;

[0009] The microprocessor is used to formulate a control strategy based on the first parameter set, the second parameter set and the grid time period to which the current time belongs, and control the photovoltaic energy storage system through the control strategy.

[0010] In a second aspect, the present application provides a photovoltaic energy storage system control method, comprising:

[0011] Obtaining a first parameter set and a second parameter set, and sending the first parameter set and the second parameter set to a microprocessor, wherein the first parameter set includes sunlight intensity data and photovoltaic system installation capacity, and the second parameter set includes holiday data, historical weather data, and historical user load demand power;

[0012] Acquire the current time according to the built-in clock, determine the grid time period to which the current time belongs according to a preset judgment rule, and send the grid time period to which the current time belongs to the microprocessor, where the grid time period to which the current time belongs includes a peak time period, a valley time period, and a normal time period;

[0013] A control strategy is formulated according to the first parameter set, the second parameter set, and the grid time period to which the current time belongs, and the photovoltaic energy storage system is controlled by the control strategy.

[0014] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0015] The present application provides a photovoltaic energy storage system control device and method, wherein a data acquisition module is used to obtain a first parameter set and a second parameter set, and send the first parameter set and the second parameter set to a microprocessor, wherein the first parameter set includes sunlight intensity data and photovoltaic system installation capacity, and the second parameter set includes holiday data, historical weather data, and historical user load demand power; a time control module is used to obtain the current time according to a built-in clock, determine the grid time period to which the current time belongs according to preset judgment rules, and send the grid time period to which the current time belongs to the microprocessor, wherein the grid time period to which the current time belongs includes a peak time period, a valley time period, and a normal time period; the microprocessor of the present application formulates a control strategy according to the first parameter set, the second parameter set, and the grid time period to which the current time belongs, thereby improving the energy utilization efficiency and economic benefits of the photovoltaic energy storage system. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 A schematic diagram of a photovoltaic energy storage system control device provided in one embodiment of the present application;

[0018] Figure 2A schematic diagram of a photovoltaic energy storage system control device provided in another embodiment of the present application;

[0019] Figure 3 A schematic diagram of a photovoltaic energy storage system control device provided in another embodiment of the present application;

[0020] Figure 4 A schematic diagram of a photovoltaic energy storage system control device provided in another embodiment of the present application;

[0021] Figure 5 A schematic diagram of a photovoltaic energy storage system control device provided in another embodiment of the present application;

[0022] Figure 6 A flow chart of a photovoltaic energy storage system control method provided in one embodiment of the present application;

[0023] Figure 7 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0024] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0025] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0026] Figure 1 A schematic diagram of a photovoltaic energy storage system control device provided in one embodiment of the present application is shown in FIG. Figure 1 As shown, the photovoltaic energy storage system control device includes: a microprocessor 1, a data acquisition module 2, and a time control module 3. The microprocessor 1 is connected to the data acquisition module 2 and the time control module 3 respectively.

[0027] Data acquisition module 2 is used to obtain a first parameter set and a second parameter set, and send the first parameter set and the second parameter set to the microprocessor, wherein the first parameter set includes sunlight intensity data and photovoltaic system installation capacity, and the second parameter set includes holiday data, historical weather data and historical user load demand power.

[0028] Sunlight intensity data can be obtained by accessing the meteorological service API and the meteorological data platform, allowing users to obtain light intensity data for different time periods. This data covers light intensity information for the past, current, and future days, providing the system with comprehensive light intensity trend analysis. To ensure real-time and accurate data, the collection frequency for sunlight intensity data can be set to once an hour or every half day, providing a more accurate reflection of the changing trends in the next day's light intensity.

[0029] Holiday data includes Saturdays that are not adjusted holidays, Sundays that are not adjusted holidays, and national statutory holidays. Holiday data covers holiday information for the past, current day, and the next few days. The introduction of holiday data can help the system adjust its operating strategy during special periods such as holidays. For example, when electricity demand is low on holidays, it can prioritize charging the energy storage system, powering energy conversion loads in user loads, or prioritizing the use of energy storage systems for power supply during peak holiday electricity demand, thereby optimizing energy distribution and utilization efficiency. Holiday data can be obtained through standardized holiday datasets or by calling the holiday API. For example, holiday is a standardized holiday dataset that provides information on statutory holidays and adjusted holiday arrangements in various regions. This data is usually provided in table or JSON format and can be called through the API interface. Holiday data for a specified date can also be obtained. This data should include information such as the specific date, holiday name, and whether it is an adjusted holiday.

[0030] Historical weather data can be obtained through the API interface or through official data sources.

[0031] Historical user load demand power can be obtained through the energy management system. By logging into the energy management system platform, historical power consumption data can be queried and exported. It can also be obtained from power companies, which typically maintain detailed user power consumption records, which can be used for analysis and modeling. Some power companies offer online services where users can log in to their accounts to view and download historical power consumption data.

[0032] To ensure the accuracy and usability of the collected sunlight intensity data, it is necessary to preprocess the sunlight intensity data, including the following sub-steps A1-A3:

[0033] A1. Remove outliers from sunlight intensity data.

[0034] For example, erroneous data points that are outside a reasonable range or due to sensor failure.

[0035] A2. Verify the sunlight intensity data and eliminate erroneous or duplicate data.

[0036] Step A2 ensures the authenticity and integrity of the sunlight intensity data.

[0037] A3. Convert the format of the verified sunlight intensity data into a standardized format to obtain pre-processed sunlight intensity data.

[0038] Time control module 3 is used to obtain the current time from the built-in clock, determine the grid time period to which the current time belongs based on preset judgment rules, and send the grid time period to the microprocessor. The grid time period to which the current time belongs includes peak time period, off-peak time period, and normal time period. The preset judgment rules include dividing a day into different time periods based on the changing pattern of grid load.

[0039] The time control module 3 obtains the precise current time through a built-in clock chip. Based on preset judgment rules, it divides the day into different grid time periods and determines the specific time period to which the current time belongs. These time periods are usually divided based on the changing patterns of grid load, with the goal of optimizing power efficiency and reducing electricity costs. For example, during peak periods (peak periods), unnecessary grid power consumption is reduced, and during low periods (valley periods), grid power is prioritized. The division of time periods helps to achieve a reasonable allocation of power resources, and different control strategies can be adopted according to different time periods.

[0040] The preset judgment rules are formulated based on the changing patterns of the power grid load, and usually a day is divided into the following three main periods:

[0041] Peak hours: The hours when the grid load is highest, usually with higher electricity prices, such as 7:00 to 10:00, 18:00 to 19:00, and 21:00 to 23:00;

[0042] Off-peak hours: The period when the grid load is the lowest and electricity prices are usually lower, such as 23:00 to 7:00.

[0043] Normal hours: other times between peak hours and off-peak hours, such as 10:00 to 18:00 and 19:00 to 21:00.

[0044] The specific division of these time periods may vary depending on the region and grid policy.

[0045] The microprocessor 1 is configured to formulate a control strategy according to the first parameter set, the second parameter set, and the grid time period to which the current time belongs, and control the photovoltaic energy storage system through the control strategy.

[0046] like Figure 5As shown, the photovoltaic energy storage system can include an energy storage system 7, a photovoltaic power generation system 8, an AC power grid 9, and user loads 10, which together form a complete energy conversion, storage, and utilization system. The photovoltaic power generation system 8 is one of the core components of the photovoltaic energy storage system and is primarily composed of solar panels (photovoltaic modules). Solar panels convert sunlight into DC power, which is then converted into AC power via an inverter. The energy storage system 7 stores the electricity generated by the photovoltaic power generation system and the AC power grid, releasing it when needed. Common energy storage devices include batteries (such as lithium batteries and lead-acid batteries) and supercapacitors. The AC power grid can transmit excess electricity generated by the photovoltaic power generation system to other locations and can also provide supplemental power to users when photovoltaic power generation is insufficient. User loads 10 are the final power consumption end of the photovoltaic energy storage system and are responsible for using the electricity provided by the system. Loads can include various household electrical appliances or machinery required for industrial operations.

[0047] In grid-connected mode, the photovoltaic energy storage system is connected to the power grid. The electricity generated by the photovoltaic power generation system is used to meet the needs of user loads. It can also be stored by the energy storage system 7, or excess electricity can be transmitted to the power grid. In off-grid operation mode, the photovoltaic energy storage system operates independently and is not connected to the power grid. At this time, the photovoltaic power generation system 8 and the energy storage system 7 jointly provide electricity for the user load. During peak electricity consumption periods, when electricity prices are high, the energy storage system 7 can release the stored electricity to the power grid, reducing the user's electricity costs; during low electricity consumption periods, when electricity prices are low, the energy storage system 7 can obtain electricity from the power grid for charging.

[0048] The energy storage system 7 includes a battery pack, an inverter, and a battery management system. The battery pack is used to store and release electrical energy, the inverter is used for bidirectional conversion of electrical energy and charge and discharge control, and the battery management system is used to protect the battery pack. The battery pack is used to store and release electrical energy to achieve energy balance and utilization. The battery pack is typically composed of multiple battery cells and can store the electrical energy generated by the photovoltaic power generation system and release it when needed to meet load demand. The inverter is used for bidirectional conversion of electrical energy and charge and discharge control. It can convert the direct current (DC) power of the battery pack into alternating current (AC) for user loads or for integration into the power grid. It can also convert AC power from photovoltaic power generation and the power grid into DC power to charge the battery pack. The battery management system (BMS) is used to protect the battery pack. The BMS monitors the status of each cell in the battery pack, including parameters such as voltage, current, and temperature, to manage battery charge and discharge and diagnose faults. It also precisely controls the operating status of the battery pack through communication with the inverter to avoid problems such as overcharging and over-discharging.

[0049] In one embodiment, the microprocessor is further configured to:

[0050] A photovoltaic power generation system model is constructed based on the first parameter set, which includes sunlight intensity data and photovoltaic system installation capacity. The output power P of the photovoltaic power generation system is predicted by the photovoltaic power generation model. EV (t).

[0051] Specifically, the photovoltaic power generation model is expressed by the following formula:

[0052] P EV (t) = H(t) / G×V;

[0053] Among them, P EV (t) represents the output power of the photovoltaic power generation system, that is, the power generation; H(t) represents the sunlight intensity, that is, the sunlight intensity data predicted by the system or collected in real time, in W / m 2 The sunlight intensity H(t) is obtained based on weather data and ranges from 0 to 1000 W / m 2 On sunny days, the light intensity is high, and on cloudy days, the light intensity is low; G represents the internationally accepted photovoltaic power generation light intensity (irradiance) standard value, which is 1000W / m 2 ; V represents the installed capacity of the photovoltaic system, in kW. The installed capacity of the photovoltaic system is determined by the design of the photovoltaic system itself. The "capacity" here refers to the maximum power generation that the photovoltaic power generation system can achieve, rather than the physical volume. EV (t) Determine the actual photovoltaic power generation power of the photovoltaic power generation system in each time period. The output power of the photovoltaic power generation system includes the output power of the photovoltaic power generation system on the same day and the output power of the photovoltaic power generation system on the next day. If the sunlight intensity G(t) is the next day, then P EV (t) is the output power of the photovoltaic power generation system the next day. If the sunlight intensity G(t) is the same as that of the day, then P EV (t) is the output power of the photovoltaic power generation system on that day.

[0054] In the photovoltaic energy storage system, the energy supply and demand relationship between the photovoltaic power generation system (EV) and the user load (Load) changes dynamically, and the energy storage system 7 plays a balancing and buffering role in this process.

[0055] When P EV (t)>P Load (t) indicates that at a certain moment t, the output power P of the photovoltaic power generation system EV (t) is greater than the user load power demand P Load (t). Excess electrical energy P EV (t)-P Load (t) can be used to charge the energy storage system 7, with the purpose of storing excess renewable energy for use when photovoltaic power generation is insufficient, power outages occur, or at night.

[0056] The data acquisition module 2 obtains the energy storage system data, which includes the energy storage system charging power P C (t) and the energy storage system discharge power P SC (t).

[0057] Specifically, the data acquisition module 2 can collect data through the Modbus protocol. Use the RS485 or RS232 interface to connect the energy storage system and the data acquisition module 2. In the photovoltaic energy storage system, the Modbus protocol can be used to monitor the operating status of the photovoltaic energy storage equipment in real time, including key parameters such as voltage, current, and power. By configuring the Modbus slave address and register address, the charging power P of the energy storage system can be controlled. C (t) and the energy storage system discharge power P SC (t) Perform real-time reading.

[0058] In the energy storage system, the energy storage system charging power P C (t) and the energy storage system discharge power P SC (t) represents the power level of the energy storage system during charging and discharging. C (t) refers to the power absorbed by the energy storage system from the external power source (such as photovoltaic power generation system) during the charging process. For example, in a distributed energy storage system, the charging power is usually designed based on the peak power of photovoltaic power generation and the rated capacity of the energy storage system. In practical applications, the energy storage system charging power P C The size of (t) is also limited by the battery management system (BMS) to ensure the safety and life of the battery. The charging power is calculated as: P 充电 =I 充电 ×U 充电 , where I 充电 Indicates the charging current, U 充电 Indicates the charging voltage.

[0059] Energy storage system discharge power P SC (t) refers to the power output of the energy storage system to the user load or the grid during the discharge process. It reflects the maximum power support that the energy storage system can provide when needed. The size of the discharge power depends on the rated power of the energy storage system, the charge state of the battery, and the load demand. For example, in the application scenario of peak load shaving, the energy storage system will output electricity at a higher discharge power during the peak load period of the grid to reduce the grid load. The calculation formula for discharge power is: P 放电 =I 放电 ×U 放电 , where I 放电 Indicates the discharge current, U 放电In practical applications, the control of charging and discharging power needs to be dynamically adjusted based on the energy storage system's state of charge, battery health status, and the needs of the grid or user load.

[0060] In one embodiment, "a user load model is constructed based on a second parameter set, the second parameter set includes holiday data, historical weather data and historical user load demand power, and the user load demand power P is predicted by the user load model. Load (t)” includes the following sub-steps B1-B5:

[0061] B1. Obtain a second parameter set, where the second parameter set includes holiday data, historical weather data, and historical user load demand power.

[0062] To ensure the accuracy and availability of holiday data, you can choose to obtain holiday data for a specified date through the open source REST API, including statutory holidays and compensatory holidays. Holiday data needs to be updated regularly, usually at the beginning of each year or when holiday policies are adjusted to ensure data accuracy. The updated holiday data can be stored as a CSV file or database table. For example, a dedicated holiday data table can be created using a MySQL database. Holiday data can be stored as a CSV file or database table and updated at the beginning of each year or when holiday policies are adjusted. The data acquisition module 2 will encapsulate the collected holiday data and sunlight data according to a specific format and send it to the microprocessor in JSON format. The data transmission frequency can be dynamically adjusted according to system requirements.

[0063] B2. Preprocess the second parameter set.

[0064] The second parameter set is processed to remove outliers; extreme values ​​or erroneous data that are obviously inconsistent with reality are identified and eliminated, such as negative load demand power, abnormally high temperature values, etc. Z-score or IQR (interquartile range) can be used to detect outliers.

[0065] The first data set after removing outliers is interpolated to fill missing values; for missing load demand power data, linear interpolation can be performed based on the data of adjacent time points or a time series interpolation method can be used; for missing weather data, the weather conditions of adjacent dates or similar seasons can be used to fill in the missing values.

[0066] B3, dividing the preprocessed second parameter set into a training set and a test set;

[0067] Typically, the data is divided chronologically, for example, using older data as the training set and more recent data as the test set. This allows the model to learn patterns and regularities in historical data during the training phase, and then evaluate its predictive power for future data during the testing phase. The specific division ratio can be determined based on the amount of data and actual needs, with a typical ratio of 70%-80% for the training set and 20%-30% for the test set.

[0068] B4. Input the training set into the initial Prophet model for training to obtain a trained Prophet model. The Prophet model is used to obtain a mapping relationship between holiday data, weather data, and user load demand power.

[0069] In the Prophet model, seasonal effects, such as annual and weekly seasonality, are specified to capture the variations in user load demand power over different time periods. For example, setting yearly_seasonality = True and weekly_seasonality = True allows the model to account for annual and weekly cyclical changes.

[0070] Specifying a holiday effect format converts the acquired holiday data into the format required by the Prophet model, including the holiday name and specific date, and then passes this data into the model as a parameter. The model then learns the difference in user load power demand between holidays and non-holidays based on this holiday data.

[0071] Add weather data as an additional regressor. Use the add_regressor method to incorporate weather characteristics (such as temperature and humidity) into the model, allowing the model to consider the impact of weather on user load power requirements. The model will learn the changing trends of user load power requirements under different weather conditions.

[0072] B5. Input the current day's holiday data and weather data into the trained Prophet model to output the current day's user load demand power. Input the next day's holiday data and weather data into the trained Prophet model to output the next day's user load demand power.

[0073] The user load demand power includes the user load demand power of the current day and the user load demand power of the next day.

[0074] For today's data, we first obtain holiday information (such as whether it is a holiday) and weather data (such as temperature and humidity) from real-time data sources. After preprocessing, this data is fed into the trained Prophet model as input features. The model then uses the learned mapping relationship, combined with the holiday and weather conditions, to predict the user load power demand for the day.

[0075] For the next day's data, holiday data and weather forecast data for the next day are obtained in advance. This data is also preprocessed and input into the trained Prophet model as input features to predict the user load demand power for the next day.

[0076] Photovoltaic power generation system model is based on sunlight intensity data and photovoltaic system The installed capacity can predict photovoltaic power generation. Combining the energy storage system's charge and discharge power data with user load power requirements, the system can optimize the distribution of photovoltaic energy, ensuring that the photovoltaic power generation system is prioritized for charging the energy storage system when sunlight is sufficient, thereby reducing energy waste. By monitoring the energy storage system's charging and discharging power in real time, the system can dynamically adjust the energy storage system's control strategy based on the current energy supply and demand. For example, during off-peak hours when AC grid electricity prices are lower, the energy storage system is prioritized for charging; during peak hours, the energy storage system is used to discharge to meet user load demand, reducing electricity costs.

[0077] The user load model combines holiday data, historical weather data, and historical user load demand power to more accurately predict user load demand. This allows the system to formulate strategies in advance based on the prediction results, ensuring sufficient power supply during high-load periods while avoiding overcharging during low-load periods.

[0078] In one embodiment, the control strategy includes energy storage system charging instructions, energy storage system discharging instructions, and grid charging instructions.

[0079] like Figure 5 As shown, the photovoltaic energy storage system control device also includes a first switch K1, a second switch K2, a third switch K3 and a fourth switch K4. The first switch K1 is connected between the photovoltaic power generation system 8 and the energy storage system 7, the second switch K2 is connected between the energy storage system 7 and the user load 10, one end of the third switch K3 is connected to the AC grid, and the other end is connected to one end of the fourth switch K4, one end of the first switch K1 and one end of the second switch K2. The other end of the fourth switch K4 is connected to the general load and the energy conversion load.

[0080] The energy storage system charging instruction is used to control the first switch K1 to be turned on and the second switch K2 to be turned off. At this time, the photovoltaic power generation system 8 charges the energy storage system 7. The energy storage system discharging instruction is used to control the second switch K2 to be turned on and the first switch K1 to be turned off. At this time, the energy storage system 7 discharges to the user load. The grid charging instruction is used to control the first switch K1 to be closed and the second switch K2 to be turned off. At this time, the AC grid 9 supplies power to the energy storage system 7, or the AC grid supplies power to the user load. Under normal power supply conditions of the AC grid, the third switch K3 and the fourth switch K4 are in the closed state. When the photovoltaic power generation system outputs power P EV(t) is less than the energy storage system charging power P C At (t), the AC grid charges the energy storage system. When the energy storage system discharges power P SC (t) is less than the user load power requirement P Load At (t), the AC grid provides additional power to the user load.

[0081] It should be noted that an inverter is installed at the power output end of the photovoltaic power generation system. When the connection between the photovoltaic power generation system and the energy storage system is cut off (that is, the first switch K1 is disconnected), the logic control unit inside the inverter will detect this state change. The built-in sensors of the inverter will continuously monitor the voltage and current levels from the photovoltaic power generation system. At the same time, the MPPT (maximum power point tracking) function included in the inverter can maximize the energy extracted from the photovoltaic array and ensure the monitoring of the power generation status. If the photovoltaic array does not generate electricity (for example, because it is at night or in bad weather conditions), the MPPT algorithm will recognize this state.

[0082] User loads 10 include important loads 101, energy conversion loads 103, and general loads 102. Energy conversion loads 103 refer to devices that can convert electrical energy into other forms of energy (such as heat, cold, or potential energy). These loads can convert surplus photovoltaic power into other forms of energy, store them, and use them directly, playing the role of energy storage, buffering, and regulation in the system, reducing the feedback and sale of photovoltaic power to the power grid, and effectively improving the energy utilization efficiency of the system. Specifically including:

[0083] Cold storage equipment: This technology converts photovoltaic power into cold energy through a refrigeration system and stores it. It is typically used in air conditioning systems or industrial refrigeration. Operating this equipment during periods of abundant photovoltaic power or low electricity prices allows the cold energy to be released during peak hours, reducing electricity demand during these periods.

[0084] Thermal storage equipment: These devices use photovoltaic power to generate and store thermal energy, such as electric boilers and hot water storage tanks. These devices can operate during off-peak electricity price periods, storing the thermal energy for use in hot water supply or space heating during the day or when needed.

[0085] Water storage equipment: Water is pumped into a high-level water tank or reservoir through a water pump, using the potential energy of the water to store energy. When needed, the water is transported to the point of use through gravity or a water pump, realizing energy conversion and utilization.

[0086] Important loads 101 refer to equipment or systems that require high power supply continuity and stability. These loads are often closely related to users' production and daily lives, and a power outage could have a significant impact. For example:

[0087] Important production equipment: Prevent power outages from causing product scrapping, material loss, or accidents.

[0088] Medical equipment: life support systems in hospitals, operating room equipment, etc.

[0089] Data centers: servers, network equipment, etc., have extremely high requirements for power supply continuity.

[0090] Emergency lighting: Provides basic lighting during power outages to ensure safe evacuation of personnel.

[0091] Communication equipment: base stations, switches, etc., to ensure the normal operation of the communication network.

[0092] In a photovoltaic energy storage system, critical loads are typically prioritized for power supply. The system provides these loads with uninterrupted power through the energy storage system and backup power sources (such as UPS and diesel generators), ensuring their stable operation.

[0093] General loads 102 refer to devices or systems that have relatively low requirements for power supply continuity. These loads will not have a significant impact on users during a short power outage, so their power supply priority can be appropriately adjusted during system operation. For example:

[0094] General lighting: non-emergency lighting equipment.

[0095] Household appliances: such as TVs, refrigerators, washing machines, etc.

[0096] Office equipment: computers, printers, etc.

[0097] In one embodiment, in terms of formulating a control strategy, the microprocessor is specifically configured to:

[0098] During the peak period, if the photovoltaic power generation power of the next day is less than the user load demand power of the next day, a charging instruction for the energy storage system is generated.

[0099] It should be noted that since the built-in clock obtains the current time, the grid time period to which the current time belongs is determined according to the preset judgment rules. The grid time period to which the current time belongs includes peak time period, valley time period and flat time period. Therefore, the peak time period, valley time period and flat time period in this disclosure all refer to the current day. If the photovoltaic power generation power of the next day is less than the user load demand power of the next day, the next day may be cloudy or rainy. Photovoltaic power generation is used first to charge the energy storage system for subsequent use. The first switch K1 is controlled to be turned on by the energy storage system charging instruction, and the second switch K2 is controlled to be turned off by the energy storage system charging instruction; the photovoltaic power generation system charges the energy storage system to supplement the insufficient photovoltaic power generation of the next day, until the energy storage system charging power P C (t) is greater than the first threshold P max1The first threshold refers to the maximum charging power the energy storage system can withstand while safely charging. This value is typically set by the energy storage system manufacturer based on battery characteristics and safety standards. The BMS triggers a protection mechanism to prevent battery overcharging and sends a charge completion instruction to microprocessor 1. Microprocessor 1 receives and responds to the charge completion instruction and controls the first switch K1 to open. At this point, power is supplied to the user load by the photovoltaic power generation system, or by the grid. During the energy storage system charging process, the converter converts the DC power generated by the photovoltaic power generation system into DC power suitable for charging the battery pack.

[0100] The photovoltaic power generation power on the day and the photovoltaic power generation power on the next day are both obtained through the photovoltaic power generation model, and the user load demand power on the day and the user load demand power on the next day are both obtained through the user load model.

[0101] During peak hours, if the photovoltaic power generation power on that day is less than the user load demand power on that day, a discharge instruction for the energy storage system is generated.

[0102] The energy storage system is discharged to supplement the shortage of photovoltaic power generation. The second switch K2 is turned on by the energy storage system discharge instruction, and the first switch K1 is turned off by the energy storage system discharge instruction; the energy storage system supplies power to the user load until the discharge power P of the energy storage system is SC (t) is greater than the second threshold P max2 The BMS triggers a protection mechanism to prevent over-discharge of the battery and sends a discharge completion instruction to microprocessor 1. Microprocessor 1 receives and responds to the discharge completion instruction and controls the second switch K2 to open. At this time, the photovoltaic power generation system or the AC power grid supplies power to the user load. During the discharge process, the converter converts the DC power stored in the battery pack of the energy storage system into AC power.

[0103] During peak hours, if the photovoltaic power generation power on that day is greater than or equal to the user load demand power on that day, a charging instruction for the energy storage system is generated.

[0104] The energy storage system is charged by the excess photovoltaic power generation. The first switch K1 is turned on by the energy storage system charging instruction, and the second switch K2 is turned off by the energy storage system charging instruction; the photovoltaic power generation system charges the energy storage system until the energy storage system charging power P C (t) is greater than the first threshold P max1 The BMS triggers a protection mechanism to prevent battery overcharging and sends a charging completion signal to microprocessor 1. Microprocessor 1 receives and responds to the charging completion signal and controls first switch K1 to open. At this point, the photovoltaic power generation system supplies power to the user load, and excess power is fed back to the grid for sale. During the charging process, the converter converts the DC power generated by the photovoltaic power generation system into DC power suitable for charging the battery pack.

[0105] During peak hours, due to higher grid electricity prices, photovoltaic power generation systems and energy storage systems are prioritized to reduce the cost of purchasing electricity from the grid. During normal hours, grid electricity prices are relatively moderate, but costs must also be considered while ensuring energy balance.

[0106] During normal times, if the photovoltaic power generation power on that day is less than the user load demand power on that day, a discharge instruction for the energy storage system is generated.

[0107] To ensure that the user load demand is met, the second switch K2 is turned on by the energy storage system discharge instruction, and the first switch K1 is turned off by the energy storage system discharge instruction; the energy storage system supplies power to the user load until the discharge power P of the energy storage system reaches SC (t) is greater than the second threshold P max2 , the BMS triggers the protection mechanism to prevent the battery from over-discharge, and sends a discharge completion instruction to the microprocessor 1. The microprocessor 1 receives and responds to the discharge completion instruction and controls the second switch K2 to also be disconnected. At this time, the photovoltaic power generation system supplies power to the user load, or the AC power grid supplies power to the user load.

[0108] During normal times, if the photovoltaic power generation power on that day is greater than or equal to the user load demand power on that day, a charging instruction for the energy storage system is generated.

[0109] During normal periods, if the photovoltaic power generation power of the next day is less than the user load demand power of the next day, a charging instruction for the energy storage system is generated.

[0110] During the off-peak period, if the next day's photovoltaic power generation is less than the next day's user load power demand, a grid charging command is triggered. This grid charging command controls the first switch K1 to close and the second switch K2 to open. At this time, the AC grid supplies power to the user load or energy storage system. Since this period is off-peak, the power supply of the photovoltaic power generation system does not need to be considered. Under normal power supply conditions, the third switch K3 and the fourth switch K4 are closed.

[0111] Because electricity prices are lower during off-peak hours, using grid power can significantly reduce users' electricity costs. In contrast, the cessation of photovoltaic power generation systems and the charging and discharging of energy storage systems may incur additional costs and losses. Furthermore, during off-peak hours, the grid's power supply capacity is sufficient and stable. Off-peak hours are typically times when user loads are low, allowing the grid to provide a stable power supply to meet user electricity needs. Energy storage systems also have limited power supply capabilities at night or during periods of low sunlight. Therefore, prioritizing grid power can better match load demand and avoid frequent charging and discharging of the energy storage system, thereby extending its service life and reducing energy waste due to inefficiencies in the energy storage system's charging and discharging efficiency.

[0112] By rationally utilizing photovoltaic power generation systems and energy storage systems, this disclosure reduces reliance on the AC grid when electricity prices are high or the grid is unstable (e.g., when the grid is experiencing a power outage), and instead utilizes photovoltaic power generation and energy storage systems more frequently for power supply. This not only helps lower electricity costs for users but also provides backup power in the event of grid failures or outages, enhancing the independence and security of regional (or local) power supply systems.

[0113] The microprocessor 1 formulates a control strategy to adapt to different electricity usage scenarios based on sunlight intensity data, holiday data, energy storage system charging power, energy storage system discharging power, photovoltaic power generation power, user load demand power and grid time period information. By generating multiple instructions through the microprocessor 1, it is possible to accurately control the energy scheduling between the photovoltaic power generation system, the energy storage system, the user load and the AC power grid, maximize the use of clean energy, and reduce the dependence of the power load on the power grid. In addition, the present disclosure can meet the diverse energy management needs of users through flexible control strategies and comprehensive analysis of multiple parameter sets. For example, during special periods such as the next day when the sunlight conditions are poor or during holidays, the photovoltaic power generation system can be used to charge the energy storage system first to ensure the stable operation of the user load the next day; during periods when the power grid electricity price fluctuates greatly, the system can reduce the user's electricity cost by implementing peak shaving and valley filling, and valley electricity peak use. This flexible control method not only improves the adaptability and reliability of the system, but also provides users with a more personalized and efficient energy management solution.

[0114] In one embodiment, Figure 2 As shown, the photovoltaic system control device also includes: a display driver module 4, which is connected to the microprocessor 1 and the smart terminal respectively; the display driver module 4 is used to display at least one of the sunlight intensity data, holiday data, control strategy, photovoltaic power generation power and user load demand power in a visual manner on the smart terminal.

[0115] The display driver module 4 receives the data signal sent by the microprocessor 1 and converts this information into a display format that can be recognized by the smart terminal. For example, it can display information such as photovoltaic power generation power, the charge and discharge status of the energy storage system, the remaining capacity, and the impact of future weather on power generation in the form of charts, curves, or text. This visual display not only helps users intuitively understand the operating status of the system, but the display driver module can also customize the display content according to user needs, for example, highlighting key indicators or issuing alarms under specific conditions, further enhancing the system's interactivity and user experience. Smart terminals include but are not limited to random display screens, mobile phones, computers, smart watches, etc.

[0116] In one embodiment, Figure 3As shown, the photovoltaic energy storage system control device further includes: a power grid detection module 5, which is connected to the AC power grid and the microprocessor 1 respectively;

[0117] The power grid detection module 5 is used for:

[0118] Detect the power supply status of the AC power grid;

[0119] If it is detected that the AC power grid is in a power-off state, an off-grid operation instruction is generated and sent to the microprocessor 1 .

[0120] Microprocessors are also used to:

[0121] When the AC grid is in a power-off state, it receives and responds to off-grid operation instructions, controlling the third and fourth switches to disconnect. At this time, the photovoltaic energy storage system is in off-grid operation mode. In off-grid operation mode, the photovoltaic power generation system and the energy storage system form a local microgrid that independently provides power to user loads. The third switch K3 serves as the main switch (also known as the anti-islanding operation switch) between the user load, the energy storage system, the photovoltaic power generation system, and the AC grid.

[0122] It should be noted that when the AC power grid is in a power supply state, the aforementioned control strategy is executed during peak periods, normal periods, and valley periods, and will not be described in detail here.

[0123] In one embodiment, a priority control device is provided between the photovoltaic power generation system, the energy storage system and the user load.

[0124] In off-grid operation, the PV system and energy storage system independently provide power to user loads. At this point, the PV power generation and energy storage system storage may be insufficient to meet the full load. Therefore, a priority control device is required. The priority control device monitors the PV system's output power and allocates power based on load priority. It also monitors the remaining charge (SOC) of the energy storage system and, based on the known outage duration, allocates power based on load priority, the PV system's operating status, and the energy storage system's energy storage status.

[0125] Critical loads (such as vital equipment, medical devices, and emergency lighting) receive the highest priority, ensuring priority power supply during a grid outage. General loads (such as general lighting and household appliances) receive the next highest priority and can be flexibly adjusted based on the energy storage status and photovoltaic power generation. Energy conversion loads (such as cold, heat, and water storage equipment) receive the lowest priority and can operate when power is sufficient, but will be restricted or disconnected when power is insufficient.

[0126] The priority control device uses sensors and communication modules to monitor the PV system's generated power, the energy storage system's status (such as SOC), and the power requirements of each load in real time. Based on pre-set priority rules, the control device dynamically adjusts power distribution. For example, when PV power and energy storage capacity are insufficient, power supply to critical loads is prioritized. The control device automatically adjusts the load's operating status, such as reducing the power of non-critical loads or suspending certain loads, to ensure overall system stability. When PV power and energy storage capacity are insufficient to meet all load demands, the control device allocates power based on load priority. For example, if critical loads have a high power demand, the device prioritizes power from the energy storage system. If the remaining capacity of the energy storage system is low (e.g., less than 60% for a lead-acid battery energy storage system or less than 20% for a lithium battery energy storage system), the control device limits power consumption for all loads to preserve the life of the energy storage system's batteries. In this way, the intelligent priority control device can allocate power from the PV power and energy storage systems based on user load priority in off-grid operation, ensuring stable power supply to critical loads and safe operation of the energy storage system.

[0127] In one embodiment, Figure 4 As shown, the photovoltaic energy storage system control device further includes a switching module 6 , which is connected to the microprocessor 1 , and is used for bidirectional switching between the automatic control mode and the manual control mode.

[0128] Specifically, a relay is usually used as an electronic switch to achieve switching between manual control mode and automatic control mode, and the relay is controlled by the microprocessor 1. The switching module 6 is usually set to respond to the manual mode first. Once the manual mode is activated, the system will immediately switch to manual control and maintain this mode until the manual mode is released. This priority setting ensures that in an emergency, the operator can quickly take over the system control to avoid potential failures or misoperations. The switching module achieves seamless switching between the two modes by quickly detecting the control signal of the microprocessor and the activation signal of the manual mode. During the switching process, key parameters of the system, such as the charge and discharge power of the energy storage system, can be adjusted through manual input to meet specific operating requirements.

[0129] Based on the same inventive concept, Figure 6 As shown, the embodiment of the present application further provides a method for implementing the photovoltaic energy storage system control involved above, and the photovoltaic energy storage system control method includes the following steps S101-S103:

[0130] S101. Obtain a first parameter set and a second parameter set, and send the first parameter set and the second parameter set to a microprocessor, wherein the first parameter set includes sunlight intensity data and photovoltaic system installation capacity, and the second parameter set includes holiday data, historical weather data, and historical user load demand power.

[0131] S102. Obtain the current time according to the built-in clock, determine the grid time period to which the current time belongs according to a preset judgment rule, and send the grid time period to which the current time belongs to the microprocessor, where the grid time period to which the current time belongs includes a peak time period, a valley time period, and a normal time period.

[0132] S103: Formulate a control strategy according to the first parameter set, the second parameter set, and the grid time period to which the current time belongs, and control the photovoltaic energy storage system using the control strategy.

[0133] In one embodiment, the photovoltaic energy storage system control method further includes:

[0134] Constructing a photovoltaic power generation system model according to the first parameter set, and predicting photovoltaic power generation power by using the photovoltaic power generation model, wherein the photovoltaic power generation power includes the photovoltaic power generation power of the day and the photovoltaic power generation power of the next day;

[0135] A user load model is constructed according to the second parameter set, and user load demand power is predicted using the user load model. The user load demand power includes the user load demand power for the current day and the user load demand power for the next day.

[0136] In one embodiment, the control strategy includes energy storage system charging instructions, energy storage system discharging instructions, and grid charging instructions;

[0137] The photovoltaic energy storage system control device also includes a first switch, a second switch, a third switch, and a fourth switch. The first switch is connected between the photovoltaic power generation system and the energy storage system, the second switch is connected between the energy storage system and the important load, one end of the third switch is connected to the AC grid, and the other end is connected to one end of the fourth switch, one end of the first switch K1, and one end of the second switch K2. The other end of the fourth switch K4 is connected to the general load and the energy conversion load.

[0138] The energy storage system charging instruction is used to control the first switch to be turned on and the second switch to be turned off, so that the photovoltaic power generation system charges the energy storage system; the energy storage system discharging instruction is used to control the second switch to be turned on and the first switch to be turned off, so that the energy storage system discharges to the user load; the grid charging instruction is used to control the first switch to be turned on and the second switch to be turned off, so that the AC grid supplies power to the energy storage system or the user load.

[0139] In one embodiment, the control strategy includes:

[0140] During peak hours,

[0141] If the photovoltaic power generation power on the next day is less than the user load demand power on the next day, generating a charging instruction for the energy storage system;

[0142] If the photovoltaic power generation power on that day is less than the user load demand power on that day, generating the energy storage system discharge instruction;

[0143] If the photovoltaic power generation power on that day is greater than or equal to the user load demand power on that day, generating the energy storage system charging instruction;

[0144] In normal times,

[0145] If the photovoltaic power generation power on the next day is less than the user load demand power on the next day, generating a charging instruction for the energy storage system;

[0146] If the photovoltaic power generation power on that day is less than the user load demand power on that day, generating the energy storage system discharge instruction;

[0147] If the photovoltaic power generation power on that day is greater than or equal to the user load demand power on that day, generating the energy storage system charging instruction;

[0148] During the valley period, if the photovoltaic power generation power of the next day is less than the user load demand power of the next day, a grid charging instruction is triggered.

[0149] In one embodiment, the display driver module is connected to the microprocessor and the intelligent terminal respectively, and the photovoltaic system control method further includes:

[0150] The display driving module displays at least one of sunlight data, holiday data, control strategy, photovoltaic power generation power, energy storage system charging power, energy storage system discharging power and user load demand power on the smart terminal in a visual manner.

[0151] In one embodiment, the grid detection module is connected to the AC grid and the microprocessor respectively, and the photovoltaic energy storage system control method further includes:

[0152] detecting a power supply status of the AC power grid;

[0153] If it is detected that the AC power grid is in a power-off state, generating an off-grid operation instruction and sending it to the microprocessor;

[0154] The system receives and responds to the off-grid operation instruction, controls the third switch and the fourth switch to be disconnected. At this time, the photovoltaic energy storage system is in the off-grid operation mode. In the off-grid operation mode, the photovoltaic power generation system and the energy storage system will independently provide power to the important load. The third switch is the main switch between the user load, the energy storage system, the photovoltaic power generation system and the AC power grid.

[0155] In one embodiment, a switching module is connected to the microprocessor, and the switching module is used to perform bidirectional switching between the automatic control mode and the manual control mode.

[0156] In one embodiment, the preset judgment rule includes dividing a day into different time periods according to a change pattern of the grid load.

[0157] In one embodiment, the energy storage system includes a battery pack, an inverter, and a battery management system. The battery pack is used to store and release electrical energy, the inverter is used for bidirectional conversion of electrical energy and charge and discharge control, and the battery management system is used to protect the battery pack.

[0158] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 7 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O) and a communication interface. The processor, memory and input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store a first parameter set and a second parameter set. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a photovoltaic energy storage system control method is implemented.

[0159] Those skilled in the art will understand that Figure 7 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0160] In an exemplary embodiment, a computer device is further provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.

[0161] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0162] In an exemplary embodiment, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0163] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0164] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0165] The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may include, but are not limited to, general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic units, data processing logic units based on quantum computing, and the like.

[0166] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0167] This document uses specific examples to illustrate the principles and implementation methods of this application. The description of the above examples is only intended to help understand the method and core concept of this application. At the same time, for those skilled in the art, based on the concept of this application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A photovoltaic energy storage system control device, characterized in that: The photovoltaic energy storage system control device includes: a microprocessor, a data acquisition module, and a time control module, wherein the microprocessor is connected to the data acquisition module and the time control module respectively; The data acquisition module is configured to obtain a first parameter set and a second parameter set, and send the first parameter set and the second parameter set to the microprocessor, wherein the first parameter set includes sunlight intensity data and photovoltaic system installed capacity, and the second parameter set includes holiday data, historical weather data, and historical user load demand power; The time control module is used to obtain the current time according to the built-in clock, determine the grid time period to which the current time belongs according to a preset judgment rule, and send the grid time period to which the current time belongs to the microprocessor, where the grid time period to which the current time belongs includes a peak time period, a valley time period, and a normal time period; The microprocessor is used to formulate a control strategy based on the first parameter set, the second parameter set and the grid time period to which the current time belongs, and control the photovoltaic energy storage system through the control strategy.

2. The photovoltaic energy storage system control device according to claim 1, characterized in that: The microprocessor is further configured to: Constructing a photovoltaic power generation system model according to the first parameter set, and predicting photovoltaic power generation power by using the photovoltaic power generation model, wherein the photovoltaic power generation power includes the photovoltaic power generation power of the day and the photovoltaic power generation power of the next day; A user load model is constructed according to the second parameter set, and user load demand power is predicted using the user load model. The user load demand power includes the user load demand power for the current day and the user load demand power for the next day.

3. The photovoltaic energy storage system control device according to claim 1, characterized in that: The control strategy includes energy storage system charging instructions, energy storage system discharging instructions and grid charging instructions; The photovoltaic energy storage system control device further includes a first switch, a second switch, a third switch, and a fourth switch, wherein the first switch is connected between the photovoltaic power generation system and the energy storage system, the second switch is connected between the energy storage system and an important load, one end of the third switch is connected to the AC grid, and the other end is connected to one end of the fourth switch, one end of the first switch, and one end of the second switch, and the other end of the fourth switch is connected to a general load and an energy conversion load; The energy storage system charging instruction is used to control the first switch to be turned on and the second switch to be turned off, so that the photovoltaic power generation system charges the energy storage system; the energy storage system discharging instruction is used to control the second switch to be turned on and the first switch to be turned off, so that the energy storage system discharges to the user load; the grid charging instruction is used to control the first switch to be turned on and the second switch to be turned off, so that the AC grid supplies power to the energy storage system or the user load.

4. The photovoltaic energy storage system control device according to claim 2, characterized in that: In terms of formulating the control strategy, the microprocessor is specifically used to: During the peak period, If the photovoltaic power generation power on the next day is less than the user load demand power on the next day, generating a charging instruction for the energy storage system; If the photovoltaic power generation power on that day is less than the user load demand power on that day, generating the energy storage system discharge instruction; If the photovoltaic power generation power on that day is greater than or equal to the user load demand power on that day, generating the energy storage system charging instruction; During the normal period, If the photovoltaic power generation power on the next day is less than the user load demand power on the next day, generating a charging instruction for the energy storage system; If the photovoltaic power generation power on that day is less than the user load demand power on that day, generating the energy storage system discharge instruction; If the photovoltaic power generation power on that day is greater than or equal to the user load demand power on that day, generating the energy storage system charging instruction; During the valley period, if the photovoltaic power generation power of the next day is less than the user load demand power of the next day, a grid charging instruction is triggered.

5. The photovoltaic energy storage system control device according to claim 2, characterized in that: The photovoltaic system control device further includes: a display driving module, wherein the display driving module is connected to the microprocessor and the intelligent terminal respectively; The display driving module is used to display at least one of the sunlight intensity data, the holiday data, the control strategy, the photovoltaic power generation power and the user load demand power on the smart terminal in a visual manner.

6. The photovoltaic energy storage system control device according to claim 1, characterized in that: The photovoltaic energy storage system control device further includes: a power grid detection module, the power grid detection module being connected to the AC power grid and the microprocessor respectively; The power grid detection module is used for: detecting a power supply status of the AC power grid; If it is detected that the AC power grid is in a power-off state, generating an off-grid operation instruction and sending it to the microprocessor; The microprocessor is further configured to: The system receives and responds to the off-grid operation instruction, controls the third switch and the fourth switch to be disconnected. At this time, the photovoltaic energy storage system is in the off-grid operation mode. In the off-grid operation mode, the photovoltaic power generation system and the energy storage system will independently provide power to important loads. The third switch is the main switch between the user load, the energy storage system, the photovoltaic power generation system and the AC power grid.

7. The photovoltaic energy storage system control device according to claim 1, characterized in that: The photovoltaic energy storage system control device further includes a switching module, which is connected to the microprocessor and is used for bidirectional switching between an automatic control mode and a manual control mode.

8. The photovoltaic energy storage system control device according to claim 1, characterized in that: The preset judgment rule includes dividing a day into different time periods according to the changing pattern of the power grid load.

9. The photovoltaic energy storage system control device according to claim 1, characterized in that: The energy storage system includes a battery pack, an inverter and a battery management system. The battery pack is used to store and release electric energy. The inverter is used for bidirectional conversion and charge and discharge control of electric energy. The battery management system is used to protect the battery pack.

10. A photovoltaic energy storage system control method, characterized in that: The photovoltaic energy storage system control method is applied to the photovoltaic energy storage system control device according to any one of claims 1 to 9, wherein the photovoltaic energy storage system control device comprises: a microprocessor, a data acquisition module, and a time control module, wherein the microprocessor is connected to the data acquisition module and the time control module respectively; The photovoltaic energy storage system control method includes: Obtaining a first parameter set and a second parameter set, and sending the first parameter set and the second parameter set to a microprocessor, wherein the first parameter set includes sunlight intensity data and photovoltaic system installation capacity, and the second parameter set includes holiday data, historical weather data, and historical user load demand power; Acquire the current time according to the built-in clock, determine the grid time period to which the current time belongs according to a preset judgment rule, and send the grid time period to which the current time belongs to the microprocessor, where the grid time period to which the current time belongs includes a peak time period, a valley time period, and a normal time period; A control strategy is formulated according to the first parameter set, the second parameter set, and the grid time period to which the current time belongs, and the photovoltaic energy storage system is controlled by the control strategy.

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