Photovoltaic power generation and city power coordinated power supply method, device and storage medium

Abstract

The present application discloses a photovoltaic power generation and city power coordinated power supply method, equipment and storage medium. The present application relates to the general control system technology field. The photovoltaic power generation and city power coordinated power supply method includes: determining the expected power of the photovoltaic power station according to the characteristic parameters of each photovoltaic power station, the light intensity and temperature of the area where the photovoltaic power station is located, and determining the power fluctuation data according to the expected power, line data and real-time power consumption mapped to the time series; determining the power fluctuation data below the preset threshold as the first time period, and the power fluctuation data not below the preset threshold as the second time period; determining the expected power according to the ratio of the adjacent first time period and the second time period; and controlling the city power access at the time point when the expected power is greater than the access threshold. It solves the technical problem that the city power cannot be effectively used for supplementation when photovoltaic power generation is insufficient, and achieves the technical effect of improving the accuracy of city power grid connection and ensuring stable power consumption.

Description

Technical Field

[0001] The present application relates to the general field of control system technology, and in particular to a photovoltaic power generation and mains power coordinated power supply method, device and storage medium. Background Art

[0002] With the continuous advancement of renewable energy technology and the enhancement of environmental awareness, photovoltaic power generation is becoming more and more widely used as a clean energy. However, photovoltaic power generation is greatly affected by weather conditions, and its power generation is uncertain and volatile, which brings challenges to the stable power supply of the power system.

[0003] In the related technologies, photovoltaic power generation systems have certain limitations in power distribution and fail to fully consider the actual power consumption of electrical equipment and the carrying capacity of the lines, resulting in the inability to effectively use municipal electricity to supplement when photovoltaic power generation is insufficient. Summary of the invention

[0004] The main purpose of this application is to provide a method, device and storage medium for coordinated power supply of photovoltaic power generation and municipal power, aiming to solve the technical problem that the actual power consumption of electrical equipment and the carrying capacity of the line are not fully taken into account, resulting in the inability to effectively use municipal power to supplement when photovoltaic power generation is insufficient.

[0005] To achieve the above-mentioned purpose, the present application provides a photovoltaic power generation and city power coordinated power supply method, the photovoltaic power generation and city power coordinated power supply method comprising:

[0006] Determine the expected power of the photovoltaic power station according to characteristic parameters of each photovoltaic power station, the light intensity and temperature of the area where the photovoltaic power station is located, wherein the characteristic parameters include at least one of photovoltaic panel layout information, inclination data, and maximum power point;

[0007] Acquiring line data of each photovoltaic power station and the mains interface;

[0008] Obtain the real-time power consumption of each electrical device based on the smart socket;

[0009] Determine power fluctuation data according to mapping the expected power, the line data and the real-time power consumption to a time series;

[0010] Determine that the power fluctuation data below a preset threshold is a first time period, and the power fluctuation data not below the preset threshold is a second time period;

[0011] Determine the expected power according to the ratio of the first adjacent time period to the second adjacent time period;

[0012] At a time point when the expected power is greater than the access threshold, control the access of the mains power.

[0013] In one embodiment, the step of determining the expected power of the photovoltaic power station according to the characteristic parameters of each photovoltaic power station, the light intensity and the temperature of the area where the photovoltaic power station is located includes:

[0014] Determine the photovoltaic panel layout information according to the photovoltaic panel coordinates and photovoltaic panel intervals of each photovoltaic power station;

[0015] Obtaining the average value of the tilt angles of the photovoltaic panels as the tilt angle data;

[0016] Determining the maximum power point according to the historical power generation of the photovoltaic power station;

[0017] The expected power is determined according to the photovoltaic panel layout information, the inclination data, the maximum power point, the light intensity and the temperature.

[0018] In one embodiment, the step of determining the expected power according to the photovoltaic panel layout information, the inclination data, the maximum power point, the light intensity and the temperature includes:

[0019] Determine the expected illumination energy of the photovoltaic power station according to the photovoltaic panel layout information, the inclination data and the illumination intensity;

[0020] updating the expected light energy according to a correction factor determined by the temperature;

[0021] The expected power is determined by planning based on the updated expected illumination energy as a positive factor and the maximum power point as a negative factor.

[0022] In one embodiment, the step of obtaining line data of each photovoltaic power station and the mains interface includes:

[0023] Acquiring first line data between each of the photovoltaic power stations;

[0024] Acquiring second line data between each of the photovoltaic power stations and the energy storage equipment;

[0025] Acquiring third line data between the energy storage device and the power consumption device;

[0026] Acquiring fourth line data between the mains interface and the energy storage device;

[0027] The line data is determined according to the first line data, the second line data, the third line data, and the fourth line data.

[0028] In one embodiment, the step of obtaining the real-time power consumption of each electrical device based on the smart socket includes:

[0029] Acquire the first real-time power consumption of each of the smart sockets through a cloud service;

[0030] Determine the additional real-time power consumption according to the location information of the working area to which each of the smart sockets belongs;

[0031] The real-time power consumption is determined according to the first real-time power consumption and the additional real-time power consumption.

[0032] In one embodiment, the step of determining power fluctuation data according to mapping the expected power, the line data, and the real-time power consumption to a time series includes:

[0033] Obtaining a scheduling strategy determined by the expected power and the real-time power consumption;

[0034] Determine a power difference value according to the scheduling strategy and the line data;

[0035] The power difference is mapped to the time series to determine the power fluctuation data.

[0036] In one embodiment, before the step of determining that the power fluctuation data below the preset threshold is the first time period, and the power fluctuation data not below the preset threshold is the second time period, the step includes:

[0037] The preset threshold is determined according to a preset value or historical power shortage data of the location information corresponding to the mains power interface.

[0038] In one embodiment, the step of determining the expected power according to the ratio of the adjacent first time period to the second time period includes:

[0039] Determine the average power value of each of the first time period and the second time period;

[0040] Determine a ratio sequence according to a ratio of an average value of electric quantity in adjacent first time period and second time period;

[0041] Determine a first expected power based on the time domain sliding filter processing the ratio sequence;

[0042] An initial population is generated based on the first expected power, and a crossover mutation operation is performed on the initial population to determine the expected power corresponding to the time series.

[0043] In addition, to achieve the above-mentioned purpose, the present application also provides a photovoltaic power generation and mains power collaborative power supply device, and the photovoltaic power generation and mains power collaborative power supply device includes: a memory, a processor, and a computer program stored on the memory and executable on the processor, and the computer program is configured to implement the steps of the photovoltaic power generation and mains power collaborative power supply method as described above.

[0044] In addition, to achieve the above-mentioned purpose, the present application also provides a storage medium, which is a computer-readable storage medium, and the computer-readable storage medium stores a program for implementing the method of coordinated power supply of photovoltaic power generation and municipal power. The program for implementing the method of coordinated power supply of photovoltaic power generation and municipal power is executed by a processor to implement the steps of the method of coordinated power supply of photovoltaic power generation and municipal power as described above.

[0045] The present application provides a method for cooperative power supply of photovoltaic power generation and city electricity. The present application first determines the expected power of the photovoltaic power station according to the characteristic parameters of each photovoltaic power station, the light intensity and temperature of the area where the photovoltaic power station is located, wherein the characteristic parameters include at least one of photovoltaic panel layout information, inclination data and maximum power point; obtains the line data of each photovoltaic power station and the city electricity interface; obtains the real-time power consumption of each electrical device based on the smart socket; determines the power fluctuation data according to the expected power, the line data and the real-time power consumption mapped to the time series; determines the power fluctuation data below the preset threshold as the first time period, and the power fluctuation data not below the preset threshold as the second time period; determines the expected power according to the ratio of the adjacent first time period and the second time period; and controls the city electricity access at the time point when the expected power is greater than the access threshold. The technical problem that the actual power consumption of electrical equipment and the carrying capacity of the line are not fully considered in the related technology, resulting in the inability to effectively use the city electricity for supplementation when photovoltaic power generation is insufficient, is solved, and the technical effect of improving the accuracy of city electricity grid connection and ensuring stable power consumption is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0047] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0048] Figure 1 A schematic diagram of a process flow provided for the first embodiment of the photovoltaic power generation and mains power supply method of the present application;

[0049] Figure 2 A schematic diagram of a process flow provided for Embodiment 2 of the photovoltaic power generation and city power coordinated power supply method of the present application;

[0050] Figure 3 A schematic diagram of a process flow provided in Embodiment 3 of the photovoltaic power generation and city power coordinated power supply method of the present application;

[0051] Figure 4 This is a schematic diagram of the hardware structure involved in the embodiment of the photovoltaic power generation and mains power supply equipment of this application.

[0052] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0053] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0054] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0055] The present application provides a method for cooperative power supply of photovoltaic power generation and city electricity. The present application first determines the expected power of the photovoltaic power station according to the characteristic parameters of each photovoltaic power station, the light intensity and temperature of the area where the photovoltaic power station is located, wherein the characteristic parameters include at least one of photovoltaic panel layout information, inclination data and maximum power point; obtains the line data of each photovoltaic power station and the city electricity interface; obtains the real-time power consumption of each electrical device based on the smart socket; determines the power fluctuation data according to the expected power, the line data and the real-time power consumption mapped to the time series; determines the power fluctuation data below the preset threshold as the first time period, and the power fluctuation data not below the preset threshold as the second time period; determines the expected power according to the ratio of the adjacent first time period and the second time period; and controls the city electricity access at the time point when the expected power is greater than the access threshold. The technical problem that the actual power consumption of electrical equipment and the carrying capacity of the line are not fully considered in the related technology, resulting in the inability to effectively use the city electricity for supplementation when photovoltaic power generation is insufficient, is solved, and the technical effect of improving the accuracy of city electricity grid connection and ensuring stable power consumption is achieved.

[0056] It should be noted that the execution subject of this embodiment can be a photovoltaic power generation and mains power supply system, or a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or a photovoltaic power generation and mains power supply device that can realize the above functions, etc. This embodiment does not specifically limit this. The following takes the photovoltaic power generation and mains power supply system as an example of the execution subject to explain this embodiment and the following embodiments.

[0057] Based on this, the present application proposes a photovoltaic power generation and city power coordinated power supply method of the first embodiment, please refer to Figure 1 The photovoltaic power generation and city power coordinated power supply method comprises:

[0058] Step S110, determining the expected power of the photovoltaic power station according to characteristic parameters of each photovoltaic power station, light intensity and temperature of the area where the photovoltaic power station is located, wherein the characteristic parameters include at least one of photovoltaic panel layout information, tilt angle data, and maximum power point.

[0059] In this embodiment, the expected power refers to the average power that may be generated within a certain period of time calculated based on factors such as design parameters and environmental conditions of the photovoltaic power station.

[0060] Collect characteristic parameters of the photovoltaic power station, including the layout information of the photovoltaic panels, such as the number of rows × the number of columns, the inclination data, that is, the angle between the photovoltaic panels and the horizontal plane, and the maximum power point, that is, the maximum output power of the photovoltaic panels under standard test conditions. Obtain light intensity and temperature data, use meteorological data or install light sensors and thermometers to monitor the light intensity and temperature in the area in real time. Calculate the expected power, and use formulas or software tools to combine the above collected data to calculate the expected power generation of each photovoltaic power station.

[0061] Step S120, obtaining line data of the interface between each photovoltaic power station and the mains.

[0062] In this embodiment, line data refers to the relevant parameters of the power transmission line from the photovoltaic power station to the power consumption equipment, such as resistance, reactance, etc. These parameters will affect the efficiency and loss of power transmission. Measure line parameters, use professional instruments to measure the line resistance, reactance and other parameters from the photovoltaic power station to the mains interface. Record data, record the measured line data for subsequent analysis.

[0063] Step S130, obtaining the real-time power consumption of each electrical device based on the smart socket.

[0064] In this embodiment, real-time power consumption refers to the power consumption of each power-consuming device at the current moment, which can be obtained through real-time monitoring of smart sockets or other smart meters. Install smart sockets or smart meters on each power-consuming device to monitor and record power consumption in real time. Data transmission: Real-time power consumption data is transmitted to the central control system through wireless communication technology.

[0065] Step S140, determining power fluctuation data based on mapping the expected power, the line data and the real-time power consumption to a time series.

[0066] In this embodiment, a time series is a series of data points arranged in chronological order, which means that the expected power, line data and real-time power consumption are arranged in chronological order for easy analysis. Data sorting, the expected power, line data and real-time power consumption are sorted into a time series in chronological order. Fluctuation analysis, the time series data is analyzed to determine the power fluctuation.

[0067] Step S150, determining that the power fluctuation data that is lower than a preset threshold is a first time period, and the power fluctuation data that is not lower than the preset threshold is a second time period.

[0068] In this embodiment, the time period is divided according to the comparison result of the power fluctuation data and the preset threshold value. The time period below the threshold value is the first time period, and the time period not below the threshold value is the second time period. Set the threshold value, and set a power fluctuation threshold value according to actual needs. Compare and classify, and compare the power fluctuation data with the threshold value to classify the first time period and the second time period.

[0069] Step S160, determining the expected power according to the ratio of the adjacent first time period and the second time period.

[0070] In this embodiment, the expected power refers to the expected power demand in a specific period, which is calculated by the ratio of adjacent periods. Calculate the ratio, calculate the ratio of power between the adjacent first period and the second period. Determine the expected power, determine the expected power according to the ratio.

[0071] Step S170, controlling the connection of the mains power at a time point when the expected power is greater than the connection threshold.

[0072] In this embodiment, mains access means that when photovoltaic power generation cannot meet the power demand, mains supply is started to ensure the continuity of power supply. The expected power is monitored and whether the expected power reaches the access threshold is continuously monitored. The access operation is performed and when the expected power is greater than the access threshold, mains access is automatically or manually started.

[0073] In this embodiment, effective coordination between photovoltaic power generation and city electricity is achieved, energy utilization efficiency is optimized, and the stability and economy of power supply are ensured.

[0074] For example, photovoltaic power station A and photovoltaic power station B have characteristic parameters: station A: photovoltaic panel layout information is 10×10, tilt angle is 30 degrees, and maximum power point is 100kW; station B: photovoltaic panel layout information is 8×8, tilt angle is 45 degrees, and maximum power point is 80kW. The light intensity in the area is 1000W / m², and the temperature is 25°C. Based on these parameters, it can be calculated that the expected power of station A and station B is 100kW and 80kW respectively. Next, the line data of each photovoltaic power station and the mains interface are obtained, assuming that the line resistance of station A and station B is 0.1Ω and 0.2Ω respectively. Then, the real-time power consumption of each electrical device is obtained based on the smart socket, assuming that the current power consumption is 50kW. According to the expected power, line data and real-time power consumption mapped to the time series, the power fluctuation data is determined. Assume that at a certain moment, the power fluctuation data of station A is 90kW, and the power fluctuation data of station B is 70kW. By comparing these data with a preset threshold, such as 80kW, it can be determined that the data below the preset threshold is the first period, such as 90kW at station A, and the data not below the preset threshold is the second period, such as 70kW at station B. The expected power is determined based on the ratio of the adjacent first period to the second period. In this example, the expected power can be calculated as (90kW *70kW) / (90kW + 70kW) = 31.82kW. Finally, when the expected power is greater than the access threshold, the mains access is controlled to meet the power demand. In this example, since the expected power is greater than the access threshold, the mains access will be connected at this time to provide additional power support.

[0075] The present application provides a method for cooperative power supply of photovoltaic power generation and city electricity. The present application first determines the expected power of the photovoltaic power station according to the characteristic parameters of each photovoltaic power station, the light intensity and temperature of the area where the photovoltaic power station is located, wherein the characteristic parameters include at least one of photovoltaic panel layout information, inclination data and maximum power point; obtains the line data of each photovoltaic power station and the city electricity interface; obtains the real-time power consumption of each electrical device based on the smart socket; determines the power fluctuation data according to the expected power, the line data and the real-time power consumption mapped to the time series; determines the power fluctuation data below the preset threshold as the first time period, and the power fluctuation data not below the preset threshold as the second time period; determines the expected power according to the ratio of the adjacent first time period and the second time period; and controls the city electricity access at the time point when the expected power is greater than the access threshold. The technical problem that the actual power consumption of electrical equipment and the carrying capacity of the line are not fully considered in the related technology, resulting in the inability to effectively use the city electricity for supplementation when photovoltaic power generation is insufficient, is solved, and the technical effect of improving the accuracy of city electricity grid connection and ensuring stable power consumption is achieved.

[0076] Based on Example 1, please refer to Figure 2 Embodiment 2 of the present application proposes a photovoltaic power generation and city power coordinated power supply method, step S110 includes:

[0077] Step S111, determining the photovoltaic panel layout information according to the photovoltaic panel coordinates and photovoltaic panel intervals of each photovoltaic power station;

[0078] Step S112, obtaining the average value of the tilt angles of the photovoltaic panels as the tilt angle data;

[0079] Step S113, determining the maximum power point according to the historical power generation of the photovoltaic power station;

[0080] Step S114, determining the expected power according to the photovoltaic panel layout information, the inclination data, the maximum power point, the light intensity and the temperature.

[0081] In this embodiment, the photovoltaic panel layout information is determined according to the photovoltaic panel coordinates and intervals. The photovoltaic panel layout information refers to the specific arrangement of the photovoltaic panels on the installation site, including the number of rows, the number of columns, and the interval distance between each photovoltaic panel. This information is very important for calculating the shading and light receiving area of ​​the photovoltaic power station. Use GPS or other positioning equipment to measure the precise coordinates of each photovoltaic panel. Measure and record the distance between adjacent photovoltaic panels. Draw a layout diagram of the photovoltaic panel based on the coordinate and interval data. The inclination data refers to the angle between the photovoltaic panel and the horizontal plane, which affects the efficiency of the photovoltaic panel in receiving sunlight. Use an inclinometer to measure the inclination angle of each photovoltaic panel. Take the average of the inclination angles of all photovoltaic panels to obtain the average inclination angle of the entire photovoltaic power station. The maximum power point (MPP) refers to the maximum output power of the photovoltaic panel under standard test conditions. By analyzing historical power generation data, the maximum power point under current conditions can be estimated. Collect historical power generation data and collect historical power generation data from the data records of the photovoltaic power station. Use statistical analysis methods, such as regression analysis, to determine the maximum power point under current light and temperature conditions. Expected power refers to the electricity that a photovoltaic power plant is expected to generate under specific environmental conditions. This requires consideration of factors such as photovoltaic panel layout, inclination, maximum power point, light intensity and temperature. Apply formula calculations, use appropriate formulas or models, and combine all of the above factors to calculate the expected power. For example:

[0082] Expected power = number of photovoltaic panels × single panel area × light intensity × temperature correction factor × tilt correction factor × maximum power point.

[0083] Based on the PV panel layout information, the expected power is adjusted to account for possible shading and system efficiency losses.

[0084] For example, a photovoltaic power station has the following characteristic parameters: Number of photovoltaic panels: 100. Area of ​​a single panel: 1.6 square meters. Average inclination angle: 30 degrees. Light intensity: 1000 W / m². Temperature: 25°C. Maximum power point obtained from historical power generation data analysis: 250 W. Based on the above information, the expected power can be calculated: Expected power = 100×1.6×1000×1×1×0.25=40000 W=40 kW.

[0085] Optionally, step S114 includes:

[0086] Step S1141, determining the expected illumination energy of the photovoltaic power station according to the photovoltaic panel layout information, the inclination data and the illumination intensity;

[0087] Step S1142, updating the expected illumination energy according to the correction coefficient determined by the temperature;

[0088] Step S1143, planning is performed based on the updated expected illumination energy as a positive factor and the maximum power point as a negative factor to determine the expected power.

[0089] In this embodiment, the expected illumination energy is determined according to the photovoltaic panel layout information, the inclination data and the illumination intensity. The expected illumination energy refers to the solar energy that the photovoltaic panel is expected to receive under specific environmental conditions. This requires consideration of the arrangement of the photovoltaic panels, the inclination angle and the current illumination intensity. The effective light receiving area is calculated. The effective light receiving area of ​​each photovoltaic panel is calculated according to the photovoltaic panel layout information and the inclination data. Consider the shielding effect and reflection loss. The current illumination intensity is applied to the effective light receiving area to obtain a preliminary expected illumination energy. The output efficiency of the photovoltaic panel changes with temperature. Generally, the higher the temperature, the lower the output efficiency of the photovoltaic panel. Therefore, it is necessary to correct the expected illumination energy according to the temperature. Determine the temperature correction coefficient, and calculate the temperature correction coefficient according to the temperature coefficient of the photovoltaic panel (usually a negative value) and the current temperature. Apply the temperature correction, apply the temperature correction coefficient to the preliminary expected illumination energy, and obtain the updated expected illumination energy. Determine the expected power according to the updated expected illumination energy and the maximum power point. The expected power refers to the power that a photovoltaic power station is expected to generate under specific environmental conditions. This requires considering the updated expected sunlight energy and the maximum power point of the photovoltaic panel. Plan the positive factor, using the updated expected sunlight energy as the positive factor, which represents the energy received by the photovoltaic panel. Plan the negative factor, using the maximum power point as the negative factor, which represents the maximum output capacity of the photovoltaic panel. Calculate the expected power and determine the expected power based on the proportional relationship between the positive factor and the negative factor. Use the following formula:

[0090]

[0091] The maximum possible output refers to the maximum output power of the photovoltaic panel under ideal conditions without considering any losses.

[0092] For example, a photovoltaic power station has the following characteristic parameters: Number of photovoltaic panels: 100. Area of ​​a single panel: 1.6 square meters. Average inclination angle: 30 degrees. Light intensity: 1000 W / m². Temperature: 25°C. Maximum power point obtained from analysis of historical power generation data: 250 W, temperature coefficient: -0.4% / °C.

[0093] Assume that due to the layout and inclination, the effective light receiving area of ​​each photovoltaic panel is 1.4 square meters. Preliminary expected light energy = 100 × 1.4 × 1000 = 140000 W. Temperature correction factor = 1−(25−25) × (−0.4%) = 1. Updated expected light energy = 140000 W. Under ideal conditions, without considering any losses, the maximum possible output of each photovoltaic panel is 250 W. Then calculate the expected power.

[0094] Based on any of the above embodiments, the third embodiment of the present application proposes a photovoltaic power generation and city power coordinated power supply method, referring to Figure 3 , step S120, comprising:

[0095] Step S121, obtaining first line data between each of the photovoltaic power stations;

[0096] Step S122, obtaining second line data between each of the photovoltaic power stations and the energy storage equipment;

[0097] Step S123, obtaining third line data between the energy storage device and the power consumption device;

[0098] Step S124, obtaining fourth line data between the mains interface and the energy storage device;

[0099] Step S125, determining the line data according to the first line data, the second line data, the third line data and the fourth line data.

[0100] In this embodiment, the first line data between each photovoltaic power station is obtained. The first line data refers to the information of the transmission line connecting different photovoltaic power stations. These data are very important for understanding the power transmission capacity and possible mutual support between photovoltaic power stations. The resistance, reactance and capacitance of each transmission line are measured using electrical measuring instruments. The actual length of each transmission line is measured and recorded. According to the measured data, a transmission line diagram between photovoltaic power stations is drawn. The second line data refers to the information of the transmission line connecting the photovoltaic power station and the energy storage device. These data are essential for evaluating the ability of the photovoltaic power station to transmit electricity to the energy storage device. The connection point between each photovoltaic power station and the energy storage device is identified and marked. The resistance, reactance and capacitance of each transmission line are measured using electrical measuring instruments. The actual length of each transmission line is measured and recorded. According to the measured data, a transmission line diagram between the photovoltaic power station and the energy storage device is drawn. The third line data refers to the information of the transmission line connecting the energy storage device and the power consumption device. These data are essential for evaluating the ability of the energy storage device to transmit electricity to the power consumption device. The connection point between each energy storage device and the power consumption device is identified and marked. Use electrical measuring instruments to measure the resistance, reactance and capacitance of each transmission line. Measure and record the actual length of each transmission line. Based on the measured data, draw a transmission line diagram between the energy storage device and the power consumption device. The fourth line data refers to the information of the transmission line connecting the mains interface and the energy storage device. These data are essential for evaluating the ability of the mains to transmit power to the energy storage device. Identify and mark the connection point between the mains interface and the energy storage device. Use electrical measuring instruments to measure the resistance, reactance and capacitance of each transmission line. Measure and record the actual length of each transmission line. Based on the measured data, draw a transmission line diagram between the mains interface and the energy storage device. Overall line data refers to the information of all transmission lines that are comprehensively considered to evaluate the power transmission capacity and efficiency of the entire system. Integrate the first line data, the second line data, the third line data and the fourth line data. Based on the integrated data, analyze the maximum transmission capacity of each transmission line. Evaluate the power transmission performance and efficiency of the entire system based on the line capacity and system requirements. Based on the evaluation results, put forward suggestions for optimizing the line layout to improve the power transmission efficiency and reliability of the system.

[0101] For example, a photovoltaic power station system includes two photovoltaic power stations (PV1 and PV2), an energy storage device (ES) and an electrical device (Load). It is necessary to obtain all line data of this system. Measure the transmission line parameters between PV1 and PV2, record the line length, and draw a line map. Measure the transmission line parameters between PV1 and ES, record the line length, and draw a line map. Measure the transmission line parameters between PV2 and ES, record the line length, and draw a line map. Measure the transmission line parameters between ES and Load, record the line length, and draw a line map. Measure the transmission line parameters between the mains interface and ES, record the line length, and draw a line map. Integrate all line data and analyze the maximum transmission capacity of each transmission line. Evaluate the power transmission performance and efficiency of the entire system. Based on the evaluation results, put forward suggestions for optimizing the line layout.

[0102] In this embodiment, the transmission loss of the power station interaction is determined by the line data between each photovoltaic power station, the power storage cost is determined by the line data between the photovoltaic power station and the energy storage device, the loss from storage to power consumption is determined by the line data between the energy storage device and the power-consuming device, and the cost of the mains access is determined by the line data between the mains interface and the energy storage device, thereby providing a basis for the design and optimization of the system based on the above costs.

[0103] Based on any of the above embodiments, in the fourth embodiment of the present application, step S130 includes:

[0104] Step S131, obtaining the first real-time power consumption of each smart socket through a cloud service;

[0105] Step S132, determining the additional real-time power consumption according to the location information of the working area to which each of the smart sockets belongs;

[0106] Step S133: determining the real-time power consumption according to the first real-time power consumption and the additional real-time power consumption.

[0107] In this embodiment, the first real-time power consumption refers to the current power consumption data read directly from the smart socket. These data are usually measured in real time by the power metering chip built into the smart socket and uploaded through the cloud service. Configure the smart socket to ensure that all smart sockets are properly connected to the home Wi-Fi network and can communicate with the cloud service. Access the cloud service API and develop or use an existing application programming interface to obtain the real-time power consumption data of the smart socket from the cloud service. Through API calls, the real-time power consumption data of each smart socket is read from the cloud service regularly and the data is stored in a local database or memory. Additional real-time power consumption refers to the increase in power consumption caused by factors such as temperature changes and equipment aging under specific conditions. These factors may vary depending on the working area. Each smart socket is assigned a unique identifier and associated with the location information of the working area where it is located. According to the location information of the working area, environmental factors that may affect power consumption, such as temperature, humidity, etc., are analyzed. Combined with environmental factors and historical power consumption data, the additional real-time power consumption of each smart socket is estimated. Real-time power consumption refers to the final power consumption after comprehensively considering the power consumption data directly read by the smart socket and the additional power consumption calculated based on the location information. The first real-time power consumption is added to the additional real-time power consumption to obtain the total real-time power consumption of each smart socket. The integrated real-time power consumption data is updated to the local database or memory for further analysis and processing.

[0108] For example, there are three working areas: living room, bedroom and kitchen, each of which is equipped with a smart socket to monitor power consumption. Now, the real-time power consumption of the whole family needs to be calculated. Configure the smart sockets to ensure that they can communicate with the cloud service. Through API calls, read the real-time power consumption data of each smart socket from the cloud service, for example, the smart socket in the living room shows 50 watts, the smart socket in the bedroom shows 30 watts, and the smart socket in the kitchen shows 70 watts. Collect the location information of the smart sockets, for example, the living room is located in the south, the bedroom is located in the north, and the kitchen is located in the east. Analyze environmental factors, assuming that the south-facing living room is exposed to more sunlight, resulting in increased use of air conditioning, so the estimated additional real-time power consumption of the living room is 10 watts; the bedroom is estimated to have an additional real-time power consumption of 5 watts due to less use of air conditioning; the kitchen is estimated to have an additional real-time power consumption of 15 watts due to frequent cooking activities. Integrate the power consumption data. The total real-time power consumption of the living room is 50 watts (first real-time power consumption) + 10 watts (additional real-time power consumption) = 60 watts; the total real-time power consumption of the bedroom is 30 watts + 5 watts = 35 watts; the total real-time power consumption of the kitchen is 70 watts + 15 watts = 85 watts. Update the power consumption information and update the integrated real-time power consumption data to the local database or memory.

[0109] In this embodiment, the first real-time power consumption of the smart socket is obtained through the cloud service to realize real-time monitoring of each power-consuming device, and then the additional real-time power consumption is determined according to the location information of the working area to which the smart socket belongs, so as to improve the calculation accuracy of the power consumption. Then, by real-time acquisition and analysis of power consumption data, users can identify high-energy-consuming devices and peak power consumption periods, thereby optimizing power consumption strategies and reducing energy costs. This has a positive impact on energy management for both homes and businesses. Overall, this embodiment effectively improves the efficiency and accuracy of power management, optimizes energy use, enhances user experience, and provides support for intelligent decision-making through real-time monitoring, precise calculation and data integration.

[0110] Based on any of the above embodiments, in the fourth embodiment of the present application, step S140 includes:

[0111] Step S141, obtaining a scheduling strategy determined by the expected power and the real-time power consumption;

[0112] Step S142, determining a power difference value according to the scheduling strategy and the line data;

[0113] Step S143, mapping the power difference to the time series to determine the power fluctuation data.

[0114] In this embodiment, according to the expected power, line data and real-time power consumption mapped to the time series, the step of determining the power fluctuation data. The scheduling strategy refers to the plan for power distribution and use based on the expected power and real-time power consumption. This helps to optimize the use of power resources and reduce waste. Obtain the expected power generation or power supply data from the photovoltaic power station or the power grid. Collect the real-time power consumption data of each power-consuming device through a smart socket or other monitoring device. According to the expected power and real-time power consumption, analyze the power supply and demand, and formulate a reasonable power distribution and use plan. The power difference refers to the difference between the expected power and the actual power at a specific time point. This difference can help understand the actual operating status of the power system and whether the scheduling strategy needs to be adjusted. Apply the formulated scheduling strategy to the power system to guide the distribution and use of power. Measure the current actual power through the monitoring device. Compare the expected power with the actual power and calculate the power difference. The power fluctuation data refers to a time series formed by arranging the power difference in chronological order. This time series can help analyze the fluctuation of the power system and predict future power demand. Select a suitable time interval to establish a time series. At each time point, record the corresponding power difference. By analyzing the time series, we can understand the power fluctuation of the power system.

[0115] For example, suppose there is a photovoltaic power station, and it is necessary to determine the power fluctuation data based on the expected power, line data, and real-time power consumption. Collect expected power data, for example, the expected power generation of the photovoltaic power station in a certain time period is 100 kWh. Obtain real-time power consumption data, for example, the current real-time power consumption is 80 kWh. Analyze the data and formulate a scheduling strategy, such as giving priority to the power supply of important equipment in a certain period of time. Apply the scheduling strategy to guide the distribution and use of electricity. Measure the actual power, for example, the current actual power is 90 kWh. Calculate the power difference, the expected power is 100 kWh, the actual power is 90 kWh, so the power difference is 10 kWh. Establish a time series, for example, record data once a minute. Record the power difference, for example, at the first minute, the power difference is 10 kWh; at the second minute, the power difference is 5 kWh; and so on. Analyze the power fluctuation. By observing the changes in the power difference in the time series, you can understand the fluctuation of the power system and adjust the scheduling strategy accordingly.

[0116] In this embodiment, the first real-time power consumption of the smart socket is obtained through the cloud service, and the additional real-time power consumption is determined in combination with the location information of the smart socket to improve the accuracy of the power consumption data. Then, by integrating the first real-time power consumption and the additional real-time power consumption, more comprehensive power consumption data can be provided, and power consumption can be monitored and analyzed in real time, and power fluctuation data based on expected power, line data and real-time power consumption can be obtained, providing a basis for the management and optimization of the power system.

[0117] Based on any of the above embodiments, in Embodiment 5 of the present application, step S150 includes:

[0118] Step S151, determining the preset threshold value according to a preset value or the historical power shortage data of the location information corresponding to the mains power interface.

[0119] In this embodiment, the preset value refers to a fixed value set in advance, which is used as a standard for judging whether the power fluctuation exceeds the normal range. This value can be set according to experience, industry standards or specific needs. According to the characteristics and operation requirements of the power system, a reasonable preset value is set. For example, the preset value can be set to 5% power fluctuation. In the subsequent analysis, this preset value is used to judge whether the power fluctuation data exceeds the normal range. The historical power gap data refers to the difference between the actual power consumption and the expected power consumption at the corresponding position of the mains interface in a specific time period. These data can help understand the supply and demand situation of the power system and adjust the preset threshold accordingly. Collect historical power gap data and obtain historical power gap data from the corresponding position of the mains interface. These data may include power consumption differences in different time periods. Analyze the historical power gap data to find out the rules and characteristics. For example, indicators such as the average power gap and the maximum power gap can be calculated. According to the analysis results of the historical data, a reasonable preset threshold is determined. For example, if the historical data shows that the average power gap is 3%, the preset threshold can be set to 5%.

[0120] For example, a photovoltaic power station needs to determine the preset threshold value based on the preset value or the historical power gap data of the location information corresponding to the mains interface. Set the preset value to 5% power fluctuation. In subsequent analysis, use this preset value to determine whether the power fluctuation data exceeds the normal range. Collect the historical power gap data of the location corresponding to the mains interface, such as the average power gap for each month in the past year. Analyze the historical data and find that the average power gap is 3% and the maximum power gap is 7%. According to the analysis results of the historical data, set the preset threshold to 5%.

[0121] In this embodiment, a reasonable preset threshold is determined according to actual conditions to provide a basis for subsequent power fluctuation data analysis.

[0122] Based on any of the above embodiments, in Embodiment 5 of the present application, step S160 includes:

[0123] Step S161, determining the average power value of each of the first time period and the second time period;

[0124] Step S162, determining a ratio sequence according to the ratio of the average power values ​​of the first time period and the second time period adjacent to each other;

[0125] Step S163, determining a first expected power by processing the ratio sequence based on a time domain sliding filter;

[0126] Step S164: generating an initial population based on the first expected power, and performing a crossover mutation operation on the initial population to determine the expected power corresponding to the time series.

[0127] In this embodiment, the power mean refers to the average value of power fluctuation data in a specific time period. This value can help understand the power consumption of the power system in each time period. The time series is divided into multiple first time periods and second time periods. For each time period, the average value of its power fluctuation data is calculated. The ratio sequence refers to a sequence formed by comparing the power means of two adjacent time periods and arranging the obtained ratios in chronological order. This sequence can help understand the power fluctuation trend of the power system. For each pair of adjacent first time periods and second time periods, the ratio of their power means is calculated. A ratio sequence is established, and all calculated ratios are arranged in chronological order to form a ratio sequence. Time domain sliding filtering is a signal processing technology used to smooth time series data. By performing time domain sliding filtering on the comparison value sequence, more stable and reliable expected power data can be obtained. Sliding filtering is applied, and the time domain sliding filtering algorithm is applied to the comparison value sequence to eliminate the influence of noise and outliers. According to the filtered ratio sequence, the first expected power is determined. An initial population is generated based on the first expected power, and a crossover mutation operation is performed on the initial population to determine the expected power corresponding to the time series. Genetic algorithm is an optimization search algorithm that solves optimization problems by simulating natural selection and genetic mechanisms. In this step, a genetic algorithm is used to optimize the prediction of expected power. Based on the first expected power, an initial population is generated, where each individual represents a possible expected power solution. Crossover and mutation operations are performed on the initial population to generate new individuals. The fitness of each individual is calculated, that is, the difference between the expected power of its corresponding solution and the actual power. Based on the fitness evaluation results, the optimal solution is selected as the final expected power prediction.

[0128] For example, a photovoltaic power station needs to determine the expected power based on the ratio of adjacent first time periods and second time periods. Divide the time series into multiple first time periods and second time periods. Calculate the average power of each time period. For each pair of adjacent first time periods and second time periods, calculate the ratio of their average power. Arrange all calculated ratios in chronological order to form a ratio sequence. Apply a time domain sliding filter algorithm to the ratio sequence to eliminate the influence of noise and outliers. Determine the first expected power based on the filtered ratio sequence. Generate an initial population based on the first expected power. Perform crossover and mutation operations on the initial population to generate new individuals. Calculate the fitness of each individual, and select the optimal solution as the final expected power prediction.

[0129] In this embodiment, by calculating the average value of electricity in adjacent time periods and determining the ratio, the trend of electricity change is captured more accurately, and the error caused by fluctuations in a single time period is reduced, thereby improving the accuracy of electricity prediction. The time domain sliding filter is used to process the ratio sequence, so that the prediction model can dynamically adapt to the trend of electricity change. In addition, the model can still maintain a high prediction accuracy when facing different loads or environmental changes. Then, the initial population is generated and the cross-mutation operation is performed to explore the solution space of electricity prediction. At the same time, the processing of the ratio sequence can effectively filter out noise and outliers, thereby enhancing the robustness of the model and making the prediction results more stable. In summary, through the technical effects of accurate electricity prediction, dynamic adaptability, application of optimization algorithms, and enhanced model robustness, the accuracy and efficiency of electricity prediction are significantly improved, providing strong support for the management and decision-making of the power system.

[0130] The present application provides a photovoltaic power generation and mains power collaborative power supply device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the photovoltaic power generation and mains power collaborative power supply method in the above-mentioned embodiment one.

[0131] Reference below Figure 4 , which shows a schematic diagram of the structure of a photovoltaic power generation and mains power supply device suitable for implementing the embodiment of the present application. The photovoltaic power generation and mains power supply device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 4 The photovoltaic power generation and AC power cooperative power supply equipment shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0132] like Figure 4As shown, the photovoltaic power generation and mains power supply equipment may include a processing device 1001 (such as a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM: Read Only Memory) 1002 or the program loaded from the storage device 1003 to the random access memory (RAM: Random Access Memory) 1004. Various programs and data required for the operation of the thermal management device of the PCS energy storage system are also stored in RAM1004. The processing device 1001, ROM1002 and RAM1004 are connected to each other through a bus 1005. The input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 1003 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 1009. The communication device 1009 can allow the photovoltaic power generation and the mains power supply device to communicate wirelessly or wired with other devices to exchange data. Although the photovoltaic power generation and the mains power supply device with various systems are shown in the figure, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented or provided alternatively.

[0133] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0134] The photovoltaic power generation and mains power coordinated power supply equipment provided by the present application adopts the photovoltaic power generation and mains power coordinated power supply method in the above-mentioned embodiment, aiming to solve the technical problem that the actual power consumption of electrical equipment and the carrying capacity of the line are not fully considered, resulting in the inability to effectively use the mains power to supplement when photovoltaic power generation is insufficient. Compared with the prior art, the beneficial effects of the photovoltaic power generation and mains power coordinated power supply equipment provided by the present application are the same as the beneficial effects of the photovoltaic power generation and mains power coordinated power supply equipment provided by the above-mentioned embodiment, and the other technical features of the photovoltaic power generation and mains power coordinated power supply equipment are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0135] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0136] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0137] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the photovoltaic power generation and mains power coordinated power supply method in the above-mentioned embodiment.

[0138] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM: Random Access Memory), a read-only memory (ROM: Read Only Memory), an erasable programmable read-only memory (EPROM: Erasable Programmable Read Only Memory or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM: CD-Read Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency: Radio Frequency), etc., or any suitable combination of the above.

[0139] The computer-readable storage medium may be included in the photovoltaic power generation and mains power supply device; or may exist independently without being assembled into the photovoltaic power generation and mains power supply device.

[0140] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the photovoltaic power generation and mains power supply device, the photovoltaic power generation and mains power supply device: determines the expected power of the photovoltaic power station according to the characteristic parameters of each photovoltaic power station, the light intensity and temperature of the area where the photovoltaic power station is located, wherein the characteristic parameters include at least one of photovoltaic panel layout information, inclination data, and maximum power point; obtains the line data of each photovoltaic power station and the mains power interface; obtains the real-time power consumption of each electrical device based on the smart socket; determines the power fluctuation data according to the expected power, the line data and the real-time power consumption mapped to the time series; determines the power fluctuation data below the preset threshold as the first time period, and the power fluctuation data not below the preset threshold as the second time period; determines the expected power according to the ratio of the adjacent first time period and the second time period; and controls the mains power access at the time point when the expected power is greater than the access threshold.

[0141] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0142] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0143] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0144] The readable storage medium provided in the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned photovoltaic power generation and mains power supply method, and can be intended to solve the technical problem that the actual power consumption of electrical equipment and the carrying capacity of the line are not fully considered, resulting in the inability to effectively use the mains power to supplement when photovoltaic power generation is insufficient. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in the present application are the same as the beneficial effects of the photovoltaic power generation and mains power supply method provided in the above-mentioned embodiment, which will not be repeated here.

[0145] An embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the above-mentioned method for coordinated power supply of photovoltaic power generation and municipal power.

[0146] The computer program product provided by the present application can solve the technical problem that the actual power consumption of electrical equipment and the carrying capacity of the line are not fully considered, resulting in the inability to effectively use the mains to supplement when photovoltaic power generation is insufficient. Compared with the prior art, the beneficial effects of the computer program product provided by the embodiment of the present application are the same as the beneficial effects of the photovoltaic power generation and mains coordinated power supply method provided by the above embodiment, which will not be elaborated here.

[0147] The above are only preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent processing scope of the present application.

Claims

1. A photovoltaic power generation and city power coordinated power supply method, characterized in that: The photovoltaic power generation and city power coordinated power supply method comprises: Determine the expected power of the photovoltaic power station according to characteristic parameters of each photovoltaic power station, the light intensity and temperature of the area where the photovoltaic power station is located, wherein the characteristic parameters include at least one of photovoltaic panel layout information, inclination data, and maximum power point; Acquiring line data of each photovoltaic power station and the mains interface; Obtain the real-time power consumption of each electrical device based on the smart socket; Determine power fluctuation data according to mapping the expected power, the line data and the real-time power consumption to a time series; Determine that the power fluctuation data below a preset threshold is a first time period, and the power fluctuation data not below the preset threshold is a second time period; Determine the average power value of each of the first time period and the second time period; Determine a ratio sequence according to a ratio of an average value of electric quantity in adjacent first time period and second time period; Determine a first expected power based on the time domain sliding filter processing the ratio sequence; generating an initial population based on the first expected power, and performing a crossover mutation operation on the initial population to determine an expected amount of electricity corresponding to the time series; At a time point when the expected power is greater than the access threshold, control the access of the mains power.

2. The photovoltaic power generation and city power coordinated power supply method according to claim 1, characterized in that: The step of determining the expected power of the photovoltaic power station according to the characteristic parameters of each photovoltaic power station, the light intensity and the temperature of the area where the photovoltaic power station is located, comprises: Determine the photovoltaic panel layout information according to the photovoltaic panel coordinates and photovoltaic panel intervals of each photovoltaic power station; Obtaining the average value of the tilt angles of the photovoltaic panels as the tilt angle data; Determining the maximum power point according to the historical power generation of the photovoltaic power station; The expected power is determined according to the photovoltaic panel layout information, the inclination data, the maximum power point, the light intensity and the temperature.

3. The photovoltaic power generation and city power coordinated power supply method according to claim 2, characterized in that: The step of determining the expected power according to the photovoltaic panel layout information, the inclination data, the maximum power point, the light intensity and the temperature comprises: Determine the expected illumination energy of the photovoltaic power station according to the photovoltaic panel layout information, the inclination data and the illumination intensity; updating the expected light energy according to a correction factor determined by the temperature; The expected power is determined by planning based on the updated expected illumination energy as a positive factor and the maximum power point as a negative factor.

4. The photovoltaic power generation and city power coordinated power supply method according to claim 1, characterized in that: The step of obtaining line data of each photovoltaic power station and the mains interface includes: Acquiring first line data between each of the photovoltaic power stations; Acquiring second line data between each of the photovoltaic power stations and the energy storage equipment; Acquiring third line data between the energy storage device and the power consumption device; Acquiring fourth line data between the mains interface and the energy storage device; The line data is determined according to the first line data, the second line data, the third line data, and the fourth line data.

5. The photovoltaic power generation and city power coordinated power supply method according to claim 1, characterized in that: The step of obtaining the real-time power consumption of each electrical device based on the smart socket includes: Acquire the first real-time power consumption of each of the smart sockets through a cloud service; Determine the additional real-time power consumption according to the location information of the working area to which each of the smart sockets belongs; The real-time power consumption is determined according to the first real-time power consumption and the additional real-time power consumption.

6. The photovoltaic power generation and city power coordinated power supply method according to claim 1, characterized in that: The step of mapping the expected power, the line data and the real-time power consumption to a time series to determine the power fluctuation data comprises: Obtaining a scheduling strategy determined by the expected power and the real-time power consumption; Determine a power difference value according to the scheduling strategy and the line data; The power difference is mapped to the time series to determine the power fluctuation data.

7. The photovoltaic power generation and city power coordinated power supply method according to claim 1, characterized in that: Before the step of determining that the power fluctuation data below the preset threshold is a first period, and the power fluctuation data not below the preset threshold is a second period, the method includes: The preset threshold is determined according to a preset value or historical power shortage data of the location information corresponding to the mains power interface.

8. A photovoltaic power generation and city power coordinated power supply device, characterized in that: The photovoltaic power generation and mains power supply collaborative device comprises: a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the photovoltaic power generation and mains power supply collaborative method as described in any one of claims 1 to 7.

9. A storage medium, characterized in that: The storage medium is a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the photovoltaic power generation and mains power supply coordinated method as described in any one of claims 1 to 7 are implemented.

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