Photovoltaic array optimization generation method and device, electronic equipment and storage medium

Abstract

The invention provides a photovoltaic array optimization generation method and device, electronic equipment and a storage medium, and the method comprises the steps: calculating a target inclination angle of a photovoltaic module unit in a target photovoltaic power station based on meteorological data and factory site geographic data of the target photovoltaic power station; obtaining an inverter type of a target photovoltaic power station, and determining a target number of photovoltaic module units connected with each inverter according to the inverter type; according to the factory site geographic data, calculating a target distance between the photovoltaic module units; and inputting the target inclination angle, the target number and the target spacing into an array optimization model for array optimization, and generating an optimized array of the target photovoltaic power station. Compared with the prior art, according to the embodiment of the invention, illumination absorption is maximized through the target inclination angle obtained through calculation, so that the power generation efficiency is improved; and the target inclination angle, the assembly number and the spacing are input into the array optimization model, so that a scientific basis can be brought to the design of the photovoltaic power station, and the overall performance and economic benefits of the system are further improved.

Description

Technical Field

[0001] The present disclosure relates to the field of data processing technology, and in particular to a method and device for optimizing generation of a photovoltaic array, an electronic device, and a storage medium. Background Art

[0002] In a photovoltaic power station, the battery array is the core part of energy conversion, and its design is directly related to the power generation capacity and operating efficiency of the entire system. Unreasonable battery array layout and configuration will not only lead to low efficiency in capturing light energy, but also increase line losses and maintenance costs, thus affecting the overall economic benefits of the photovoltaic power station.

[0003] In order to improve the power generation efficiency of photovoltaic systems, reduce unnecessary operating losses, reduce the long-term operating costs of power stations, and shorten the construction period and economic cost recovery period, the design of battery arrays is particularly important. Reasonable battery array design needs to comprehensively consider multiple factors such as geographical location, climate conditions, light intensity, shadow shielding, battery panel type and performance parameters to ensure that the battery array can maximize the absorption of solar energy and efficiently convert it into electrical energy.

[0004] At the same time, the main electrical connection of the photovoltaic array, as a key link connecting the battery array and the power grid, also has an important impact on the operating efficiency and reliability of the photovoltaic system. Reasonable main electrical connection design can simplify the protection configuration, reduce line losses, and improve the operating reliability and stability of the system. By optimizing the layout and configuration of the main electrical connection, the difficulty and cost of operation and maintenance of photovoltaic power stations can be further reduced, and the economy and competitiveness of the entire system can be improved. At present, the design of photovoltaic arrays is manually designed based on experience, and the optimization design level of photovoltaic arrays depends on the designers, which will lead to low operating efficiency of the photovoltaic system. Summary of the invention

[0005] The present disclosure provides a method and device for optimizing the generation of a photovoltaic array, an electronic device and a storage medium, the main purpose of which is to solve the problem of low operating efficiency of a photovoltaic system caused by poor photovoltaic array design.

[0006] According to a first aspect of the present disclosure, a method for optimizing generation of a photovoltaic array is provided, comprising:

[0007] Calculating a target tilt angle of a photovoltaic module unit in the target photovoltaic power station based on meteorological data and plant site geographic data of the target photovoltaic power station;

[0008] Acquire the inverter type of the target photovoltaic power station, and determine the target number of photovoltaic module units connected to each inverter according to the inverter type;

[0009] Calculating the target spacing between the photovoltaic module units according to the plant site geographic data;

[0010] The target tilt angle, the target number and the target spacing are input into an array optimization model to perform array optimization, thereby generating an optimized array of the target photovoltaic power station.

[0011] In some embodiments, the method further comprises:

[0012] The meteorological data and the plant site geographic data are analyzed to determine the installation control method of the photovoltaic component unit.

[0013] In some embodiments, the step of calculating the target tilt angle of the photovoltaic module unit in the target photovoltaic power station based on the meteorological data and the plant site geographic data of the target photovoltaic power station includes:

[0014] Calculating the optimal tilt angle of the photovoltaic module unit based on the light radiation in the meteorological data;

[0015] The wind load of the target photovoltaic power station is determined according to the meteorological data, and the load simulation is performed based on the optimal tilt angle to determine the target tilt angle.

[0016] In some embodiments, the step of calculating the target spacing between the photovoltaic module units according to the plant site geographic data includes:

[0017] Calculating the shadow length of the photovoltaic module unit according to the plant site geographic data;

[0018] Based on the projection shadow length, a target spacing between the photovoltaic assembly units is determined.

[0019] According to a second aspect of the present disclosure, a device for optimizing generation of a photovoltaic array is provided, comprising:

[0020] A first calculation unit, configured to calculate a target tilt angle of a photovoltaic module unit in the target photovoltaic power station based on meteorological data and plant site geographic data of the target photovoltaic power station;

[0021] A first determination unit, configured to obtain an inverter type of the target photovoltaic power station, and determine a target number of photovoltaic assembly units connected to each inverter according to the inverter type;

[0022] A second calculation unit, used for calculating a target spacing between the photovoltaic module units according to the plant site geographic data;

[0023] The optimization unit is used to input the target tilt angle, the target number and the target spacing into an array optimization model to perform array optimization and generate an optimized array of the target photovoltaic power station.

[0024] In some embodiments, the device further comprises

[0025] The second determination unit is used to analyze the meteorological data and the plant site geographical data to determine the installation control method of the photovoltaic component unit.

[0026] In some embodiments, the first computing unit includes:

[0027] A first calculation module, used for calculating the optimal tilt angle of the photovoltaic module unit based on the light radiation in the meteorological data;

[0028] The first determination module is used to determine the wind load of the target photovoltaic power station according to the meteorological data, and to perform load simulation based on the optimal tilt angle to determine the target tilt angle.

[0029] In some embodiments, the second computing unit includes:

[0030] A second calculation module is used to calculate the shadow length of the photovoltaic module unit according to the plant site geographic data;

[0031] The second determination module is used to determine the target spacing between the photovoltaic assembly units based on the projection shadow length.

[0032] According to a third aspect of the present disclosure, there is provided an electronic device, including:

[0033] at least one processor; and

[0034] a memory communicatively connected to the at least one processor; wherein,

[0035] 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 to enable the at least one processor to perform the method described in the first aspect.

[0036] According to a fourth aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable the computer to execute the method described in the first aspect.

[0037] According to a fifth aspect of the present disclosure, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements the method as described in the first aspect above.

[0038] The present disclosure provides a method and device, electronic device and storage medium for optimizing and generating a photovoltaic array. The method comprises the following steps: calculating a target tilt angle of a photovoltaic component unit in a target photovoltaic power station based on meteorological data and plant site geographic data of the target photovoltaic power station; obtaining an inverter type of the target photovoltaic power station, and determining a target number of photovoltaic component units connected to each inverter according to the inverter type; calculating a target spacing between the photovoltaic component units according to the plant site geographic data; and inputting the target tilt angle, the target number and the target spacing into an array optimization model for array optimization to generate an optimized array of the target photovoltaic power station. Compared with the related art, the embodiment of the present disclosure calculates the target tilt angle so that the photovoltaic modules can receive solar radiation at the optimal angle, maximize light absorption, and thus improve power generation efficiency; reasonably determining the number of photovoltaic module units connected to each inverter according to the inverter type helps to improve the working efficiency of the inverter, ensure the stability and reliability of the system, and avoid inverter overload or no-load; calculating the target spacing between photovoltaic module units can effectively reduce the shading effect between modules, ensure that sunlight reaches each module, reduce power generation losses, and improve overall power generation capacity; inputting the target tilt angle, number of modules and spacing into the array optimization model can provide a scientific basis for the design of photovoltaic power stations, and further improve the overall performance and economic benefits of the system.

[0039] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present disclosure.

[0041] Figure 1 A schematic diagram of a process for optimizing and generating a photovoltaic array provided by an embodiment of the present disclosure;

[0042] Figure 2 A schematic flow chart of another method for optimizing and generating a photovoltaic array provided in an embodiment of the present disclosure;

[0043] Figure 3 A schematic diagram of the structure of a photovoltaic array optimization generation device provided by an embodiment of the present disclosure;

[0044] Figure 4 A schematic diagram of the structure of another photovoltaic array optimization generation device provided by an embodiment of the present disclosure;

[0045] Figure 5 A schematic block diagram of an exemplary electronic device provided for an embodiment of the present disclosure. DETAILED DESCRIPTION

[0046] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0047] The following describes the photovoltaic array optimization generation method and device, electronic device and storage medium according to the embodiments of the present disclosure with reference to the accompanying drawings.

[0048] Figure 1 A schematic flow chart of a method for optimizing and generating a photovoltaic array provided in an embodiment of the present disclosure.

[0049] like Figure 1 As shown, the method comprises the following steps:

[0050] Step 101 : Calculate a target tilt angle of a photovoltaic module unit in a target photovoltaic power station based on meteorological data and plant site geographic data of the target photovoltaic power station.

[0051] In the embodiments of the present disclosure, in order to design and optimize the performance of the target photovoltaic power station, the meteorological data and the geographical data of the plant site of the target photovoltaic power station are analyzed in detail to calculate the target tilt angle of the photovoltaic module unit. Meteorological data refers to information related to the climatic conditions of the area where the target photovoltaic power station is located, including but not limited to sunshine hours, light radiation intensity, temperature, wind speed, precipitation, humidity, etc. These data are of great significance. The sunshine hours and light radiation intensity affect the power generation efficiency of the photovoltaic module. The stronger the light, the higher the power generation capacity; the temperature will affect the working performance of the photovoltaic module, and too high temperature may reduce the power generation efficiency; the calculation of wind speed is related to the safety and wind resistance of the module, especially under extreme weather conditions; precipitation and humidity have an impact on cleaning and maintenance requirements.

[0052] Site geographic data is information related to the geographical location of the photovoltaic power station, including but not limited to topography, landforms, soil types, vegetation cover, local latitude and longitude, etc. These data help evaluate the specific impact of the environment on the performance of the photovoltaic power station: topography and landforms may affect the shadow casting of photovoltaic modules. Therefore, areas with higher terrain usually have better unobstructed lighting conditions; latitude and longitude determine the trajectory of the sun and the intensity of radiation, thus affecting the optimal tilt angle of the target photovoltaic power station components.

[0053] The target tilt angle refers to the installation angle of the photovoltaic module relative to the horizontal plane. The choice of this angle directly affects the power generation efficiency of the photovoltaic power station. It is usually calculated based on the local latitude, seasonal changes, and the length of sunshine. In general, the closer the tilt angle is to the local latitude, the higher the power generation efficiency of the photovoltaic module throughout the year. The appropriate tilt angle is determined by calculation so that the module can receive maximum sunlight all day long.

[0054] Based on the detailed meteorological data collected at the specific geographical location of the target photovoltaic power station and the geographical data of the plant site, the optimal target tilt angle of the photovoltaic module units in the photovoltaic power station can be accurately calculated. This calculation process will first comprehensively consider key meteorological factors such as the local solar radiation intensity, sunshine duration, seasonal changes, and the latitude of the geographical location. For example, in high-latitude areas, in order to maximize the capture of solar energy in winter, photovoltaic modules may need to be set at a higher tilt; while in low-latitude areas, in order to effectively utilize the strong sunlight throughout the year, the modules may tend to be installed at a near-horizontal angle.

[0055] At the same time, the geographical data of the site, including topography, ground reflectivity (i.e., Albedo effect), height and position of surrounding buildings or trees, etc., will also have an important impact on the selection of the tilt angle of photovoltaic modules. For example, if the photovoltaic power station is located in an open area with high reflectivity, the appropriate tilt angle can help capture and utilize the sunlight reflected from the ground. On the contrary, if there are tall buildings or trees around the power station, it may be necessary to adjust the tilt angle of the module to reduce shadows and ensure that each module can receive as much direct sunlight as possible.

[0056] By systematically analyzing and calculating the meteorological data and geographical data of the target PV power station, the target tilt angle obtained provides the necessary basis for the efficient placement of PV modules, and also lays the foundation for improving the overall performance and economic benefits of the power station.

[0057] By calculating the target tilt angle, it is possible to ensure that the photovoltaic modules receive solar radiation at the best angle, thereby improving the overall power generation capacity. By considering meteorological data and geographical conditions, the impact of wind loads on the modules can be minimized, and the safety and durability of the overall structure can be improved. This provides data support for the subsequent photovoltaic module layout, quantity configuration, spacing design, etc., so as to formulate the most optimized power station design plan.

[0058] Step 102: Obtain the inverter type of the target photovoltaic power station, and determine the target number of photovoltaic module units connected to each inverter according to the inverter type.

[0059] In the embodiments of the present disclosure, the inverter is a key device in a photovoltaic power station that converts direct current (DC) into alternating current (AC). In a photovoltaic system, the main function of the inverter is to convert the electrical energy generated by the photovoltaic module into AC that can be used by the power grid and monitor and manage the operation of the system.

[0060] According to the scale, configuration and application requirements of the photovoltaic power station, inverters can be divided into several different types: Centralized inverters are suitable for large photovoltaic power stations, and usually the output of multiple photovoltaic modules is concentrated into one or several inverters for management. The advantages of this inverter are high efficiency and relatively low cost, but in some cases, if a component fails, it may affect the power generation of the entire system; string inverters are suitable for small and medium-sized photovoltaic power stations. Since each inverter is connected to a specific group of photovoltaic modules, the power generation efficiency of each group can be managed more flexibly. This method can reduce the impact of local shading on the overall power generation capacity of the system; micro inverters are equipped with a separate inverter for each photovoltaic module, which can maximize power generation. Micro inverters effectively deal with shading and performance differences between different modules and are suitable for small residential photovoltaic systems; multi-functional smart inverters combine energy storage and management functions to improve the flexibility and efficiency of the system.

[0061] When determining the inverter type, factors such as the size of the power plant, budget, desired power generation efficiency, and future maintenance requirements need to be considered. After determining the inverter type, the next step is to calculate the target number of PV module units connected to each inverter based on the characteristics of the selected inverter and the design requirements of the power plant. The rated power of the inverter matches the power of the PV module, and the rated power of each inverter and the single power of the PV module need to be considered. When setting the number of PV modules, the redundancy and safety of the system also need to be considered. In practical applications, in order to avoid affecting the power generation efficiency of the entire power plant due to the failure of certain components, it is usually recommended to maintain a certain redundancy configuration. For example, the number of connected PV modules is controlled between 80% and 90% of the rated power of the inverter to ensure that the inverter is not overloaded and the stability of the system can be maintained in severe weather or abnormal conditions.

[0062] After the quantity is determined, the number of connected components of each inverter is integrated into the design of the entire PV power station: according to the number of PV modules connected to each inverter, draw the equipment wiring diagram to clarify the electrical connection relationship between the various parts; by comprehensively considering the number of each inverter and PV module, evaluate the power generation capacity of the entire power station to ensure that it meets the expected output of the project; optimize the layout of the inverters and the arrangement of the components to facilitate subsequent operation and maintenance, and ensure that problems can be quickly located and handled when failures occur.

[0063] Step 103: Calculate the target spacing between the photovoltaic module units according to the plant site geographic data.

[0064] In the embodiments of the present disclosure, in the design and layout process of the photovoltaic power station, reasonable spacing can not only maximize the capture of solar energy, but also ensure the safety and stability of the system in long-term operation. Before calculating the spacing between photovoltaic modules, it is necessary to collect and analyze relevant plant site geographic data, mainly including the following aspects: The geographical location determines the angle and time at which the photovoltaic modules receive sunlight, affecting the intensity of solar radiation. The longitude and latitude information of the plant site will help determine the trajectory of the sun in different seasons and weather conditions. The terrain (such as slope, altitude, surrounding buildings and vegetation) will affect the lighting conditions and possible shadows of the photovoltaic modules. Therefore, a detailed terrain analysis is necessary. Climate conditions include climate factors such as common local wind speed, precipitation and temperature range. When designing the spacing, it is necessary to consider the impact of wind to avoid damage to the modules due to improper wind flow, and also consider the problem of water accumulation caused by precipitation.

[0065] When calculating the target spacing, it is usually based on the fact that the tilt angle of the PV module directly affects the amount of sunlight received and the projection area. In order to avoid shadows between adjacent modules and ensure that the maximum amount of sunlight is captured, a sunshine analysis is required: according to the longitude and latitude of the site and the season, the sunrise and sunset angles of the sun are analyzed to calculate the shadow length of each PV module at different time periods. Ensure that the spacing between PV modules is greater than or equal to the length of the shadow at a specific tilt angle.

[0066] When designing the spacing between PV modules, local wind loads must also be considered. If the modules are too close together, they may collide with each other or be damaged by strong winds. It is generally recommended to leave at least 10-20% safety spacing around the modules to ensure safety. In addition, the impact of wind speed is more obvious, especially in high wind speed areas, and sufficient clearance needs to be considered during design to allow wind energy to flow freely.

[0067] Design the layout of the PV panels based on the target spacing. Create a detailed site layout diagram showing the specific location of each panel to ensure they are arranged within the predetermined spacing.

[0068] Step 104 : inputting the target tilt angle, the target number and the target spacing into an array optimization model to perform array optimization, and generate an optimized array of the target photovoltaic power station.

[0069] In the embodiments of the present disclosure, in order to achieve array optimization of a photovoltaic power station, several key parameters determined previously (ie, target tilt angle, target number, and target spacing) need to be input into an array optimization model to generate an optimal photovoltaic array layout.

[0070] The target tilt angle is the angle between the photovoltaic module and the horizontal plane, which affects the light receiving effect of the photovoltaic module. The appropriate tilt angle can optimize the sunlight conditions of the module in different seasons and time periods and improve the power generation efficiency of the photovoltaic module. Therefore, the determined target tilt angle will serve as an important input to the array optimization model.

[0071] The target number refers to the number of PV module units connected to each inverter. This parameter helps us understand the total design requirements and ensure that each inverter works within the load tolerance range. By analyzing the target number, we can determine the reasonable distribution of PV modules in the power station, thereby optimizing the power generation capacity.

[0072] The target spacing is the distance setting between the components in the photovoltaic array. Reasonable spacing can effectively avoid shadows between components and improve the power generation efficiency of the overall system. In addition, appropriate spacing can also ensure the safety of workers during maintenance or inspection. Therefore, this parameter is also crucial in the array optimization process.

[0073] After determining the above target parameters, these parameters are then input into the array optimization model. This model usually uses specific software tools or algorithms that can process the relationship between multiple variables to achieve the best array layout.

[0074] The array optimization model can use different optimization algorithms, such as genetic algorithms, particle swarm optimization (PSO) or simulated annealing. These algorithms can effectively explore the power generation potential and technical feasibility under different configurations when dealing with complex multi-objective optimization problems. In the array optimization model, in addition to inputting the target tilt angle, target number and target spacing, some constraints need to be set. For example: the physical size and maximum height limit of the photovoltaic module; the requirements of wind load to avoid collision between array layers; possible shadow factors, such as the influence of surrounding buildings and plants; these constraints ensure that the generated array layout not only optimizes the power generation capacity, but also meets safety and regulatory requirements.

[0075] The model will evaluate different arrangements and compare the power generation efficiency and other performance indicators of each configuration among multiple candidate solutions, such as annual power generation, system cost and maintenance requirements. Ultimately, the model will output the best array configuration, including detailed information such as the specific location, tilt angle, spacing, etc. of each photovoltaic module. This layout is actually the result of comprehensive optimization of the set parameters and is the basis for maximizing the power generation benefits of photovoltaic power plants.

[0076] The present disclosure provides a method for optimizing and generating a photovoltaic array. The method comprises the following steps: calculating a target tilt angle of photovoltaic component units in a target photovoltaic power station based on meteorological data and plant site geographic data of the target photovoltaic power station; obtaining an inverter type of the target photovoltaic power station, and determining a target number of photovoltaic component units connected to each inverter according to the inverter type; calculating a target spacing between the photovoltaic component units according to the plant site geographic data; inputting the target tilt angle, the target number, and the target spacing into an array optimization model for array optimization, and generating an optimized array of the target photovoltaic power station. Compared with the related art, the embodiment of the present disclosure calculates the target tilt angle so that the photovoltaic modules can receive solar radiation at the optimal angle, maximize light absorption, and thus improve power generation efficiency; reasonably determining the number of photovoltaic module units connected to each inverter according to the inverter type helps to improve the working efficiency of the inverter, ensure the stability and reliability of the system, and avoid inverter overload or no-load; calculating the target spacing between photovoltaic module units can effectively reduce the shading effect between modules, ensure that sunlight reaches each module, reduce power generation losses, and improve overall power generation capacity; inputting the target tilt angle, number of modules and spacing into the array optimization model can provide a scientific basis for the design of photovoltaic power stations, and further improve the overall performance and economic benefits of the system.

[0077] In order to clearly illustrate the embodiments of the present disclosure, this embodiment provides a flow chart of another method for optimizing and generating a photovoltaic array.

[0078] like Figure 2 As shown, the method comprises the following steps:

[0079] Step 201, calculating the optimal tilt angle of the photovoltaic module unit based on the light radiation in the meteorological data.

[0080] Step 202: determine the wind load of the target photovoltaic power station according to the meteorological data, and perform load simulation based on the optimal tilt angle to determine the target tilt angle.

[0081] Specifically, in steps 201 to 202, the collected meteorological data, especially the light radiation, is used to calculate the optimal tilt angle of the photovoltaic module unit. Meteorological data usually includes information on light radiation in different seasons and time periods. These data can be obtained through on-site meteorological measuring instruments, satellite remote sensing or historical data records. Light radiation refers to the solar radiation received per unit area per unit time, usually expressed in kilowatts per square meter (kW / m 2 )express.

[0082] The calculation of the optimal tilt angle is usually based on the following principle: the closer the tilt angle of the module is to the direction of solar radiation, the more sunlight it receives. The commonly used calculation formula can be used in the following way:

[0083]

[0084] Among them, H is the altitude angle of the sun in a day, and D is the projection distance of the sun in the horizontal direction of the ground.

[0085] At the same time, you can also use the empirical formula:

[0086] θ opt =φ+15°×(n / 365)

[0087] Where φ is the local latitude and n is the number of days in a year. By comparing the radiation data for different dates, the annual average is found, giving the best average tilt angle.

[0088] Since solar radiation varies due to seasonal variations, it is recommended to account for seasonal adjustments in the calculation of the optimal tilt angle. For example, in winter, the optimal tilt angle may need to be larger to capture lower solar radiation.

[0089] Once the optimal tilt angle is determined, the next step is to evaluate the wind load of the PV plant based on meteorological data. The meteorological data should include wind speed information, usually expressed in meters per second (m / s). Wind load refers to the force exerted by wind on PV modules, and increases with increasing wind speed.

[0090] Wind loads can be calculated using the following formula:

[0091] F=0.5×C d ×ρ×A×V 2

[0092] Where, F is the wind load (Newton N); C d is the aerodynamic drag coefficient, which depends on the design of the photovoltaic module; ρ is the air density (about 1.225kg / m 3 ); A is the front area of ​​the photovoltaic module (m 2); V is the wind speed (m / s). The calculation results of these wind loads will provide basic data for subsequent load simulation. After obtaining the optimal tilt angle and wind load, load simulation can be performed to ensure the safety and stability of photovoltaic modules under actual conditions. Using computer simulation software, a model is established to simulate the impact of wind load on photovoltaic modules at the optimal tilt angle. These software can usually take into account a variety of factors, including module spacing, interference from the surrounding environment, and load conditions at different wind speeds. Through simulation, the wind load conditions borne by photovoltaic modules under different wind speeds and climatic conditions are analyzed. By changing simulation parameters such as wind speed and module tilt angle, their effects on the safety and stability of the modules can be observed to ensure normal operation under extreme weather conditions. Through load simulation analysis, an actual target tilt angle is finally determined. This angle must meet the following conditions at the same time: meet the highest light efficiency, ensure that at this target tilt angle, the photovoltaic module can receive the maximum amount of light, and thus achieve efficient power generation; ensure structural safety, according to the results of load simulation, ensure that the target tilt angle can still maintain the structural safety of the module under the most unfavorable conditions (such as the highest wind speed) to prevent damage or displacement of the module caused by wind.

[0093] Step 203: Obtain the inverter type of the target photovoltaic power station, and determine the target number of photovoltaic module units connected to each inverter according to the inverter type.

[0094] Specifically in step 203, the output voltage of the string formed by the series connection of solar cell modules must vary within the allowable input voltage range for normal operation of the inverter. The total power of the solar cell modules connected to the DC input side of each inverter should be greater than the rated input power of the inverter and should not exceed the maximum allowable input power of the inverter. After the solar cell modules are connected in series, their maximum output voltage is not allowed to exceed the maximum allowable system voltage of the solar cell modules themselves. The DC cable path from each solar panel to the inverter should be as short as possible to reduce DC losses.

[0095] The number of solar cell modules connected in series is determined by the maximum input voltage and minimum operating voltage of the inverter, as well as the maximum system voltage allowed by the solar cell modules. The number of solar cell strings connected in parallel is determined by the rated capacity of the inverter.

[0096] Step 204, calculating the shadow length of the photovoltaic module unit according to the plant site geographic data.

[0097] Step 205: determining a target spacing between the photovoltaic module units based on the projection shadow length.

[0098] Specifically, in steps 204 to 205, before starting the calculation, it is first necessary to collect the geographical data of the site related to the photovoltaic power station. These data usually include: latitude and longitude, the specific geographical location of the site, which helps to determine the angle of solar radiation; altitude, which affects the air density and solar radiation intensity; terrain features, such as surrounding buildings, mountains or forests, etc. These factors may affect the formation of light and shadows; local meteorological conditions, such as seasonal weather changes, sunshine duration and solar altitude angle, etc.

[0099] Next, the projection shadow length of the PV module unit is calculated based on the geographical data of the site and the tilt angle of the module. The projection shadow length refers to the length of the shadow of the PV module on the ground, which usually depends on the altitude angle of the sun, the tilt angle of the module, and the actual height of the module.

[0100] Once the shadow length is determined, the next step is to determine the target spacing between PV module units based on this shadow length. The design of this spacing must take into account the impact of shadows and ensure that the PV modules can receive sufficient light under different sunlight conditions. When selecting the spacing between PV modules, the following factors need to be considered: shadow overlap. When the shadow length of a PV module overlaps with that of an adjacent module, it may result in reduced light and lower power generation efficiency. Therefore, the spacing between modules must be sufficient to avoid shadow overlap when the sun's altitude angle is low.

[0101] Different types of PV modules may differ in height and width, so the actual size of the specific module should be considered when calculating the spacing. Fixed and tracking PV systems may have different spacing requirements, and tracking systems may require larger spacing to avoid their own shadows. Such as wind direction, the height of surrounding buildings and the additional shadows they may produce.

[0102] Step 206: input the target tilt angle, the target number and the target spacing into an array optimization model to perform array optimization, and generate an optimized array of the target photovoltaic power station.

[0103] Specifically, in step 206, after determining the target tilt angle, target number, and target spacing, these parameters are then input into an array optimization model. This model usually uses specific software tools or algorithms that can process the relationship between multiple variables to achieve the best array layout.

[0104] The array optimization model can use different optimization algorithms, such as genetic algorithms, particle swarm optimization (PSO) or simulated annealing. These algorithms can effectively explore the power generation potential and technical feasibility under different configurations when dealing with complex multi-objective optimization problems. In the array optimization model, in addition to inputting the target tilt angle, target number and target spacing, some constraints need to be set. For example: the physical size and maximum height limit of the photovoltaic module; the requirements of wind load to avoid collision between array layers; possible shadow factors, such as the influence of surrounding buildings and plants; these constraints ensure that the generated array layout not only optimizes the power generation capacity, but also meets safety and regulatory requirements.

[0105] The model will evaluate different arrangements and compare the power generation efficiency and other performance indicators of each configuration among multiple candidate solutions, such as annual power generation, system cost and maintenance requirements. Ultimately, the model will output the best array configuration, including detailed information such as the specific location, tilt angle, spacing, etc. of each photovoltaic module. This layout is actually the result of comprehensive optimization of the set parameters and is the basis for maximizing the power generation benefits of photovoltaic power plants.

[0106] It should be noted that the embodiments of the present disclosure may include multiple steps. For the convenience of description, these steps are numbered, but these numbers do not limit the execution time slots or execution order between the steps; these steps can be implemented in any order, and the embodiments of the present disclosure do not limit this.

[0107] Corresponding to the above-mentioned method for optimizing and generating a photovoltaic array, the present invention also provides a device for optimizing and generating a photovoltaic array. Since the device embodiment of the present invention corresponds to the above-mentioned method embodiment, details not disclosed in the device embodiment can be referred to the above-mentioned method embodiment, and will not be described in detail in the present invention.

[0108] Figure 3 A schematic diagram of a photovoltaic array optimization generation device provided by an embodiment of the present disclosure is shown in FIG. Figure 3 As shown, including:

[0109] A first calculation unit 31 is used to calculate a target tilt angle of a photovoltaic module unit in the target photovoltaic power station based on meteorological data and plant site geographical data of the target photovoltaic power station;

[0110] A first determining unit 32 is used to obtain an inverter type of the target photovoltaic power station, and determine a target number of photovoltaic assembly units connected to each inverter according to the inverter type;

[0111] A second calculation unit 33, used to calculate the target spacing between the photovoltaic module units according to the plant site geographic data;

[0112] The optimization unit 34 is used to input the target tilt angle, the target number and the target spacing into an array optimization model to perform array optimization and generate an optimized array of the target photovoltaic power station.

[0113] The present disclosure provides a device for optimizing and generating a photovoltaic array. The device calculates a target tilt angle of a photovoltaic component unit in a target photovoltaic power station based on meteorological data and plant site geographic data of the target photovoltaic power station; obtains an inverter type of the target photovoltaic power station, and determines a target number of photovoltaic component units connected to each inverter according to the inverter type; calculates a target spacing between the photovoltaic component units according to the plant site geographic data; and inputs the target tilt angle, the target number, and the target spacing into an array optimization model for array optimization, thereby generating an optimized array of the target photovoltaic power station. Compared with the related art, the embodiment of the present disclosure calculates the target tilt angle so that the photovoltaic modules can receive solar radiation at the optimal angle, maximize light absorption, and thus improve power generation efficiency; reasonably determining the number of photovoltaic module units connected to each inverter according to the inverter type helps to improve the working efficiency of the inverter, ensure the stability and reliability of the system, and avoid inverter overload or no-load; calculating the target spacing between photovoltaic module units can effectively reduce the shading effect between modules, ensure that sunlight reaches each module, reduce power generation losses, and improve overall power generation capacity; inputting the target tilt angle, number of modules and spacing into the array optimization model can provide a scientific basis for the design of photovoltaic power stations, and further improve the overall performance and economic benefits of the system.

[0114] Furthermore, in a possible implementation of this embodiment, as Figure 4 As shown, the device also includes

[0115] The second determination unit 35 is used to analyze the meteorological data and the plant site geographical data to determine the installation control method of the photovoltaic module unit.

[0116] Furthermore, in a possible implementation of this embodiment, as Figure 4 As shown, the first calculation unit 31 includes:

[0117] A first calculation module 311 is used to calculate the optimal tilt angle of the photovoltaic module unit based on the light radiation in the meteorological data;

[0118] The first determination module 312 is used to determine the wind load of the target photovoltaic power station according to the meteorological data, and to perform load simulation based on the optimal tilt angle to determine the target tilt angle.

[0119] Furthermore, in a possible implementation of this embodiment, as Figure 4 As shown, the second calculation unit 33 includes:

[0120] A second calculation module 331 is used to calculate the shadow length of the photovoltaic module unit according to the plant site geographic data;

[0121] The second determination module 332 is used to determine the target spacing between the photovoltaic assembly units based on the projection shadow length.

[0122] It should be noted that the above explanation of the method embodiment is also applicable to the device of this embodiment, and the principle is the same, which is not limited in this embodiment.

[0123] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.

[0124] Figure 5 A schematic block diagram of an example electronic device 500 that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0125] like Figure 5 As shown, the device 500 includes a computing unit 501, which can perform various appropriate actions and processes according to a computer program stored in a ROM (Read-Only Memory) 502 or a computer program loaded from a storage unit 508 to a RAM (Random Access Memory) 503. In the RAM 503, various programs and data required for the operation of the device 500 can also be stored. The computing unit 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. An I / O (Input / Output) interface 505 is also connected to the bus 504.

[0126] A number of components in the device 500 are connected to the I / O interface 505, including: an input unit 506, such as a keyboard, a mouse, etc.; an output unit 507, such as various types of displays, speakers, etc.; a storage unit 508, such as a disk, an optical disk, etc.; and a communication unit 509, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 509 allows the device 500 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0127] The computing unit 501 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 501 include, but are not limited to, a CPU (Central Processing Unit), a GPU (Graphic Processing Units), various dedicated AI (Artificial Intelligence) computing chips, various computing units running machine learning model algorithms, a DSP (Digital Signal Processor), and any appropriate processor, controller, microcontroller, etc. The computing unit 501 performs the various methods and processes described above, such as a method for optimizing the generation of a photovoltaic array. For example, in some embodiments, the method for optimizing the generation of a photovoltaic array may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 508. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 500 via the ROM 502 and / or the communication unit 509. When the computer program is loaded into the RAM 503 and executed by the computing unit 501, one or more steps of the method described above may be performed. Alternatively, in other embodiments, the computing unit 501 may be configured to execute the aforementioned photovoltaic array optimization generation method in any other appropriate manner (for example, by means of firmware).

[0128] Various embodiments of the systems and techniques described above herein may be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application Specific Standard Products), SOCs (System On Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include: being implemented in one or more computer programs that may be executed and / or interpreted on a programmable system including at least one programmable processor that may be a special purpose or general purpose programmable processor that may receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0129] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0130] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any suitable combination of the foregoing. More specific examples of machine-readable storage media may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a RAM, a ROM, an EPROM (Electrically Programmable Read-Only-Memory) or a flash memory, an optical fiber, a CD-ROM (Compact Dis sc Read-Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0131] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (Cathode-Ray Tube) or LCD (Liquid Crystal Display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball), through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0132] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: LAN (Local Area Network), WAN (Wide Area Network), the Internet, and blockchain networks.

[0133] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship between the client and the server is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services ("Virtual Private Server", or "VPS" for short). The server may also be a server of a distributed system, or a server combined with a blockchain.

[0134] It should be noted that artificial intelligence is a discipline that studies how computers can simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, planning, etc.), and includes both hardware-level and software-level technologies. Artificial intelligence hardware technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, and big data processing; artificial intelligence software technologies mainly include computer vision technology, speech recognition technology, natural language processing technology, as well as machine learning / deep learning, big data processing technology, knowledge graph technology, and other major directions.

[0135] The various numerical numbers such as first and second involved in the present disclosure are only for the convenience of description and are not used to limit the scope of the embodiments of the present disclosure, but also indicate the order of precedence.

[0136] At least one in the present disclosure may also be described as one or more, and a plurality may be two, three, four or more, which is not limited in the present disclosure. In the embodiments of the present disclosure, for a technical feature, the technical features in the technical feature are distinguished by "first", "second", "third", "A", "B", "C" and "D", etc., and there is no order of precedence or size between the technical features described by the "first", "second", "third", "A", "B", "C" and "D".

[0137] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0138] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A method for optimizing generation of a photovoltaic array, characterized in that: include: Calculating a target tilt angle of a photovoltaic module unit in the target photovoltaic power station based on meteorological data and plant site geographic data of the target photovoltaic power station; Acquire the inverter type of the target photovoltaic power station, and determine the target number of photovoltaic module units connected to each inverter according to the inverter type; Calculating the target spacing between the photovoltaic module units according to the plant site geographic data; The target tilt angle, the target number and the target spacing are input into an array optimization model to perform array optimization, thereby generating an optimized array of the target photovoltaic power station.

2. The method according to claim 1, characterized in that The method further comprises: The meteorological data and the plant site geographic data are analyzed to determine the installation control method of the photovoltaic component unit.

3. The method according to claim 1, characterized in that The step of calculating the target tilt angle of the photovoltaic module unit in the target photovoltaic power station based on the meteorological data and the plant site geographic data of the target photovoltaic power station comprises: Calculating the optimal tilt angle of the photovoltaic module unit based on the light radiation in the meteorological data; The wind load of the target photovoltaic power station is determined according to the meteorological data, and the load simulation is performed based on the optimal tilt angle to determine the target tilt angle.

4. The method according to claim 1, characterized in that The step of calculating the target spacing between the photovoltaic module units according to the plant site geographic data includes: Calculating the shadow length of the photovoltaic module unit according to the plant site geographic data; Based on the projection shadow length, a target spacing between the photovoltaic assembly units is determined.

5. A device for optimizing generation of a photovoltaic array, characterized in that: include: A first calculation unit, configured to calculate a target tilt angle of a photovoltaic module unit in the target photovoltaic power station based on meteorological data and plant site geographic data of the target photovoltaic power station; A first determination unit, configured to obtain an inverter type of the target photovoltaic power station, and determine a target number of photovoltaic assembly units connected to each inverter according to the inverter type; A second calculation unit, used for calculating a target spacing between the photovoltaic module units according to the plant site geographic data; The optimization unit is used to input the target tilt angle, the target number and the target spacing into an array optimization model to perform array optimization and generate an optimized array of the target photovoltaic power station.

6. The device according to claim 5, characterized in that The device also includes The second determination unit is used to analyze the meteorological data and the plant site geographical data to determine the installation control method of the photovoltaic component unit.

7. The device according to claim 5, characterized in that The first computing unit comprises: A calculation module, used for calculating the optimal tilt angle of the photovoltaic module unit based on the light radiation in the meteorological data; A determination module is used to determine the wind load of the target photovoltaic power station according to the meteorological data, and to perform load simulation based on the optimal tilt angle to determine the target tilt angle.

8. An electronic device, characterized in that: include: at least one processor; as well as 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 to enable the at least one processor to perform the method according to any one of claims 1 to 4.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-4.

10. A computer program product, characterized in that The invention comprises a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 4.

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