Photovoltaic power station design system and method based on ecological collaborative optimization

Abstract

The invention provides a photovoltaic power station design system and method based on ecological collaborative optimization, and relates to the technical field of data processing. The system comprises an initial configuration module which is used for generating an initial layout structure of a photovoltaic module, performing energy-saving and consumption-reducing calculation and economic analysis according to generating capacity data, and obtaining initial energy-saving and consumption-reducing data and initial economic analysis data; the secondary optimization module is used for optimizing the parameters of the photovoltaic module based on the economical efficiency analysis data and determining energy-saving and consumption-reducing data and economical efficiency analysis data through the generating capacity optimization data; the ecological evaluation module is used for determining ecological benefit data of the photovoltaic power station according to the ecological influence parameters; and the collaborative optimization module is used for setting a power generation income weight and an ecological benefit weight so as to optimize the photovoltaic module layout structure and generate a photovoltaic power station design scheme based on ecological collaborative optimization. The method is used for realizing collaborative optimization of power generation benefits and ecological benefits of the photovoltaic power station, so that the power station gives consideration to ecological protection while improving the power generation efficiency.

Description

Background Art

[0002] As climate change and resource depletion become more serious, the use of renewable energy is becoming more and more important. Photovoltaic power stations are widely used as clean energy around the world. Photovoltaic power stations have gradually become an important part of the power system due to their abundant energy sources, environmental protection and high efficiency.

[0003] However, the design schemes of photovoltaic power stations in related technologies usually give priority to economic factors such as power generation and cost-effectiveness, with the main goal of improving the energy output and return on investment of the power station, ignoring the synergistic relationship with the environmental ecology. This design model that is only guided by economic benefits will have a negative impact in ecologically fragile areas such as deserts and wetlands. For example, in arid and semi-arid areas, the layout of photovoltaic modules and the configuration of the support system may damage surface vegetation, aggravate soil erosion, and put the ecosystem under greater pressure. As a result, some photovoltaic power stations have a significant negative impact on the local ecological environment during operation. Therefore, there is still room for improvement in the design system of photovoltaic power stations.

[0004] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure, and therefore may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention

[0005] The purpose of the embodiments of the present disclosure is to provide a photovoltaic power station design system based on ecological collaborative optimization, a photovoltaic power station design method based on ecological collaborative optimization, an electronic device and a computer-readable storage medium, so as to achieve the collaborative optimization of the power generation value and the ecological value of the photovoltaic power station at least to a certain extent, so that the photovoltaic power station can take into account ecological protection while improving the power generation efficiency.

[0006] Other features and advantages of the present disclosure will become apparent from the following detailed description, or may be learned in part by the practice of the present disclosure.

[0007] According to a first aspect of an embodiment of the present disclosure, a photovoltaic power station design system based on ecological collaborative optimization is provided, including: an initial configuration module, which is used to generate a preliminary layout structure of photovoltaic components based on equipment data and environmental data of the photovoltaic power station, and determine the power generation data of the photovoltaic power station in combination with photovoltaic component parameters, and perform energy-saving and consumption reduction calculations and economic analysis based on the power generation data to obtain preliminary energy-saving and consumption reduction data and preliminary economic analysis data; a secondary optimization module, which is used to optimize the photovoltaic component parameters based on the economic analysis data, generate a photovoltaic component layout structure and power generation optimization data based on the optimized photovoltaic component parameters, and determine energy-saving and consumption reduction data and economic analysis data through the power generation optimization data; an ecological assessment module, which is used to calculate ecological impact parameters based on the photovoltaic component layout structure, and determine the ecological benefit data of the photovoltaic power station based on the ecological impact parameters; a collaborative optimization module, which is used to set power generation income weights and ecological benefit weights based on the ecological benefit data, the energy-saving and consumption reduction data and the economic analysis data, so as to optimize the photovoltaic component layout structure and generate a photovoltaic power station design scheme based on ecological collaborative optimization.

[0008] According to a second aspect of an embodiment of the present disclosure, a photovoltaic power station design method based on ecological collaborative optimization is provided, including: generating a preliminary layout structure of photovoltaic components based on equipment data and environmental data of the photovoltaic power station, and determining the power generation data of the photovoltaic power station in combination with photovoltaic component parameters, performing energy-saving and consumption reduction calculations and economic analysis based on the power generation data to obtain preliminary energy-saving and consumption reduction data and preliminary economic analysis data; optimizing the photovoltaic component parameters based on the economic analysis data, generating a photovoltaic component layout structure and power generation optimization data based on the optimized photovoltaic component parameters, and determining energy-saving and consumption reduction data and economic analysis data through the power generation optimization data; calculating ecological impact parameters based on the photovoltaic component layout structure, and determining the ecological benefit data of the photovoltaic power station based on the ecological impact parameters; setting power generation income weights and ecological benefit weights based on the ecological benefit data, the energy-saving and consumption reduction data and the economic analysis data to optimize the photovoltaic component layout structure, and generate a photovoltaic power station design scheme based on ecological collaborative optimization.

[0009] According to a third aspect of an embodiment of the present disclosure, an electronic device is provided, including: a processor; and a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the above-mentioned photovoltaic power station design method based on ecological collaborative optimization is implemented.

[0010] According to a fourth aspect of an embodiment of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the photovoltaic power station design method based on ecological collaborative optimization described above is implemented.

[0011] The technical solution provided by the embodiments of the present disclosure may have the following beneficial effects: The photovoltaic power station design system based on ecological collaborative optimization in the exemplary embodiment of the present disclosure is composed of an initial configuration module, a secondary optimization module, an ecological assessment module and a collaborative optimization module.

[0012] On the one hand, the initial configuration module generates a preliminary layout structure based on the equipment and environmental data of the photovoltaic power station, and performs energy-saving and consumption-reduction analysis and economic evaluation through the calculation of power generation data, thus realizing the preliminary layout design of the photovoltaic system, so that the system takes into account energy-saving and economic factors in the preliminary design stage. This module can reasonably utilize resources in the site selection and layout of the power station, forming a preliminary balance between power generation and cost-effectiveness.

[0013] On the other hand, the secondary optimization module further optimizes the parameters of photovoltaic modules based on the preliminary economic analysis data, generates more optimized layout structure and power generation data, and enables the system to achieve a better configuration in terms of module spacing, inclination and other parameters. This module increases power generation through refined design, reduces unnecessary energy consumption and economic losses, and thus further improves the economy and resource utilization efficiency of the system, which helps to improve the power generation efficiency of photovoltaic power stations and reduce resource waste, forming a more efficient layout plan.

[0014] On the other hand, the ecological assessment module calculates ecological impact parameters based on the data of the photovoltaic module layout structure, so that the system can quantify the impact on the ecological environment in the layout design. This module provides ecological benefit data, which can evaluate the potential impact of photovoltaic power stations on regional ecology, so that the photovoltaic system design not only has advantages in economy, but also optimizes the component layout in terms of ecological adaptability, reduces the negative impact on ecological factors such as vegetation, soil and soil and water conservation, and generates ecological benefit assessment results including windbreak and sand fixation, vegetation restoration, etc., to achieve an environmentally friendly system layout.

[0015] In addition, the collaborative optimization module establishes a balance mechanism between power generation benefits and ecological benefits by setting the power generation income weight and ecological benefit weight, so that the photovoltaic module layout not only optimizes the power generation capacity of the power station, but also minimizes the negative impact on the ecological environment and enhances the positive benefits to the ecological environment. This module further optimizes the component layout structure to generate a photovoltaic power station design that conforms to ecological collaborative optimization, achieving the effect of balancing power generation benefits and ecological protection. It is suitable for photovoltaic power station projects in ecologically sensitive areas and improves the overall sustainability of the photovoltaic system.

[0016] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the specification are used to explain the principles of the present disclosure. Obviously, the accompanying drawings described below are only some embodiments of the present disclosure, and for ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without creative work.

[0018] Figure 1 The schematic diagram shows the composition of a photovoltaic power station design system based on ecological collaborative optimization according to some embodiments of the present disclosure.

[0019] Figure 2 The flowchart of the initial configuration module according to some embodiments of the present disclosure is schematically shown.

[0020] Figure 3 The flowchart of the secondary optimization module according to some embodiments of the present disclosure is schematically shown.

[0021] Figure 4 The flowchart of the ecological assessment module according to some embodiments of the present disclosure is schematically shown.

[0022] Figure 5 A flowchart of a collaborative optimization module according to some embodiments of the present disclosure is schematically shown.

[0023] Figure 6 A schematic diagram of a process flow of a photovoltaic power station design method based on ecological collaborative optimization according to some embodiments of the present disclosure is schematically shown.

[0024] Figure 7 A schematic diagram of the structure of a computer system of an electronic device according to some embodiments of the present disclosure is schematically shown.

[0025] Figure 8 A schematic diagram of a computer-readable storage medium according to some embodiments of the present disclosure is schematically shown.

[0026] In the drawings, the same or corresponding reference numerals represent the same or corresponding parts. DETAILED DESCRIPTION

[0027] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementations described in the following exemplary embodiments do not represent all implementations consistent with this specification. Instead, they are merely examples of devices and methods consistent with some aspects of this specification as detailed in the appended claims.

[0028] The terms used in this specification are for the purpose of describing specific embodiments only and are not intended to limit this specification. The singular forms "a", "the" and "the" used in this specification and the appended claims are also intended to include plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0029] It should be understood that although the terms first, second, third, etc. may be used in this specification to describe various information, this information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of this specification, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0030] In addition, the described features, structures or characteristics may be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure may be practiced without one or more of the specific details, or other methods, components, devices, steps, etc. may be adopted. In other cases, known methods, devices, implementations or operations are not shown or described in detail to avoid blurring the various aspects of the present disclosure.

[0031] Furthermore, the drawings are only schematic illustrations and are not necessarily drawn to scale. The block diagrams shown in the drawings are only functional entities and do not necessarily correspond to physically separate entities. That is, these functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0032] In an exemplary embodiment of the present disclosure, a photovoltaic power station design system based on ecological collaborative optimization is first provided. Figure 1 The schematic diagram shows a structure of a photovoltaic power station design system based on ecological collaborative optimization according to some embodiments of the present disclosure. Figure 1As shown, the photovoltaic power station design system 100 based on ecological collaborative optimization may include an initial configuration module 1, a secondary optimization module 2, an ecological assessment module 3 and a collaborative optimization module 4. Among them, the initial configuration module 1 can be used to generate a preliminary layout structure of photovoltaic components based on the equipment data and environmental data of the photovoltaic power station, and determine the power generation data of the photovoltaic power station in combination with the photovoltaic component parameters, and perform energy saving and consumption reduction calculation and economic analysis according to the power generation data to obtain preliminary energy saving and consumption reduction data and preliminary economic analysis data; the secondary optimization module 2 can be used to optimize the photovoltaic component parameters based on the economic analysis data, generate the photovoltaic component layout structure and power generation optimization data according to the optimized photovoltaic component parameters, and determine the energy saving and consumption reduction data and economic analysis data through the power generation optimization data; the ecological assessment module 3 can be used to calculate the ecological impact parameters based on the photovoltaic component layout structure, and determine the ecological benefit data of the photovoltaic power station according to the ecological impact parameters; the collaborative optimization module 4 can be used to set the power generation income weight and the ecological benefit weight based on the ecological benefit data, the energy saving and consumption reduction data and the economic analysis data, so as to optimize the photovoltaic component layout structure and generate a photovoltaic power station design scheme based on ecological collaborative optimization.

[0033] Among them, the initial configuration module is responsible for the basic layout design of the photovoltaic power station. By combining the equipment data and environmental data of the photovoltaic power station, the preliminary layout structure of the photovoltaic components is generated. It first estimates the power generation data, and then performs energy-saving and consumption-reduction calculations and economic analysis based on the power generation data, thereby obtaining preliminary energy-saving and consumption-reduction data and preliminary economic analysis data. The equipment data can represent the technical parameters and performance data of various types of equipment in the photovoltaic power station, including but not limited to the current, voltage, and power parameters of the photovoltaic components, the efficiency and power range of the inverter, the type and support height of the bracket system, and the length and cross-section of the cable. The equipment data is used to support the layout design of the photovoltaic power station and the preliminary setting of the power station operation parameters. The environmental data can represent the natural environment data of the area where the photovoltaic power station is located, including topographic features, sunshine intensity, wind speed, temperature, humidity, precipitation, soil characteristics, vegetation distribution, etc. The environmental data provides basic information for the layout design and ecological impact assessment of the photovoltaic power station, so that the design scheme is more in line with the ecological characteristics and environmental conditions of the region. The preliminary layout structure of photovoltaic modules can represent the preliminary arrangement of photovoltaic modules in the power station area generated based on equipment data and environmental data, including the inclination angle of the modules, north-south and east-west spacing, series-parallel configuration, etc. The photovoltaic module parameters can represent the electrical and physical parameters of a single photovoltaic module, including but not limited to the maximum power, voltage, current, open circuit voltage, short circuit current, conversion efficiency, temperature coefficient, etc. of the module. These parameters are used to accurately design the initial layout of the module and adjust it during the optimization process to improve the system efficiency. The power generation data can represent the power generation information of the power station calculated based on the preliminary layout structure of photovoltaic modules and the module parameters, including daily power generation, monthly power generation, annual power generation and other indicators. The power generation data provides a quantitative basis for energy conservation and consumption reduction and economic analysis, and is used to measure the power generation performance of the photovoltaic system. The energy conservation and consumption reduction data can represent the energy conservation and emission reduction indicators of the photovoltaic power station calculated based on the power generation data, including the amount of fossil energy saved, the amount of carbon dioxide emissions reduced, and the amount of smoke and pollutant emissions reduced. The economic analysis data can represent the economic indicators of the photovoltaic power station calculated based on the power generation data and preliminary energy-saving and consumption-reduction data, including return on investment, payback period, net present value, internal rate of return, average annual income, etc.

[0034] The secondary optimization module further optimizes the parameters of photovoltaic modules based on the preliminary economic analysis data. This module generates more reasonable module layout structure and power generation optimization data through module parameter optimization, and recalculates the system's energy saving and consumption reduction data and economic analysis data through these optimized power generation data. This allows for more refined parameter adjustments to improve system efficiency and economy.

[0035] The ecological assessment module is used to evaluate the potential impact of the layout of photovoltaic modules on the environment. Based on the layout structure of photovoltaic modules, this module calculates ecological impact parameters and generates ecological benefit data of photovoltaic power stations based on these parameters. The ecological assessment module ensures that the layout of photovoltaic power stations not only has economic benefits, but also reduces negative environmental impacts. Ecological impact parameters can represent a set of parameters that quantify the factors that may affect the regional ecosystem through the layout structure of photovoltaic modules, including wind and sand impact, soil moisture changes, surface temperature regulation, vegetation coverage, dust suppression effect, etc. Ecological impact parameters are used to evaluate the potential impact of the layout of photovoltaic power stations on the environment and provide basic data for subsequent optimization design. Ecological benefit data can represent the positive contribution of photovoltaic power stations to the regional ecological environment calculated based on ecological impact parameters, including comprehensive data on wind and sand fixation benefits, soil moisture maintenance, vegetation restoration, climate regulation, etc. Ecological benefit data reflects the potential value of photovoltaic power stations in ecological protection and restoration, and is used for quantitative analysis of ecological benefits during collaborative optimization.

[0036] The collaborative optimization module sets the power generation benefit weight and ecological benefit weight based on the ecological benefit data, energy saving and consumption reduction data and economic analysis data provided by the ecological assessment module. Through this weight setting, the collaborative optimization module achieves a trade-off between power generation benefit and ecological protection, and further optimizes the layout structure of photovoltaic components to generate a photovoltaic power station design scheme with both power generation and ecological benefits. The power generation benefit weight can be expressed in the collaborative optimization module as the relative weight value given to the photovoltaic power station layout on power production and economic benefits. The power generation benefit weight is used to measure the impact of power generation benefit on layout design during the optimization process to ensure that the economic benefits of the power station are not lower than the preset target. The ecological benefit weight can be expressed in the collaborative optimization module as the relative weight value given to the photovoltaic power station layout on ecological protection and environmental improvement. The ecological benefit weight is used to balance the ecological protection needs when optimizing the design, ensure that the impact of the layout design on the ecological environment is minimized, and achieve comprehensive optimization of economic and ecological benefits together with the power generation benefit weight.

[0037] The photovoltaic power station design system based on ecological collaborative optimization in the example embodiment of the present disclosure generates a preliminary layout structure of photovoltaic components through an initial configuration module, and combines equipment data and environmental data to ensure that the layout structure meets the photovoltaic component parameter requirements while achieving accurate determination of power generation data. The energy-saving and consumption-reduction data and economic analysis data calculated thereby lay a scientific basis for the subsequent optimization process, and provide data support for energy-saving and consumption-reduction and cost control, thereby effectively avoiding the waste of resources caused by unreasonable layout. Through the secondary optimization module, the system further optimizes the photovoltaic component parameters on the basis of the preliminary economic analysis data, generates an optimized photovoltaic component layout structure and power generation optimization data, and this secondary optimization based on the economic analysis data ensures that the photovoltaic power station maximizes the energy-saving and consumption-reduction effect while maintaining the power generation efficiency, and provides further refined economic analysis data, so that the layout plan achieves a reasonable balance between power generation and cost, thereby overcoming the defect that it is difficult to balance cost and benefit in the existing photovoltaic power station design. The ecological assessment module calculates the ecological impact parameters based on the optimized photovoltaic module layout structure, comprehensively evaluates the potential effects of the layout design on ecological factors such as wind and sand impact, soil moisture, surface temperature and vegetation coverage, and forms ecological benefit data. By quantifying the ecological impact of the layout structure, this module enables photovoltaic power stations to take environmental protection into account in the design, avoiding the environmental damage that may be caused by the traditional photovoltaic power station layout in ecologically sensitive areas, especially vegetation destruction and soil erosion, so that it is more suitable for long-term application in ecologically fragile areas. On the basis of obtaining ecological benefit data, energy-saving and consumption-reduction data and economic analysis data, the collaborative optimization module further optimizes the photovoltaic module layout structure by setting the power generation income weight and ecological benefit weight, so that the layout not only has advantages in terms of economy, but also meets the requirements of ecological protection to the greatest extent. By balancing power generation benefits and ecological protection, this module enables the photovoltaic power station design to achieve the coordination of economic benefits and ecological value under complex environmental conditions, providing a comprehensive solution for improving the applicability of photovoltaic power stations in diverse ecological environments, and effectively making up for the shortcomings of traditional design technology in balancing ecology and economy.

[0038] Next, the photovoltaic power station design system based on ecological collaborative optimization in the above exemplary embodiment will be further described.

[0039] In some embodiments, the initial configuration module includes a light resource processing unit, a preliminary layout design unit, a power generation calculation unit, an energy saving and consumption reduction calculation unit, and an economic analysis unit. Among them, the light resource processing unit can be used to analyze the light resource data based on the environmental data of the photovoltaic power station to determine the sunshine condition parameters of the photovoltaic power station; the preliminary layout design unit can be used to generate the preliminary layout structure of the photovoltaic components based on the sunshine condition parameters, including the series and parallel configuration of the components, the plane layout, the bracket system settings and the system loss settings; the power generation calculation unit can be used to calculate the power generation data of the photovoltaic power station based on the preliminary layout structure of the photovoltaic components; the energy saving and consumption reduction calculation unit can be used to perform energy saving and consumption reduction calculation based on the power generation data to generate the preliminary energy saving and consumption reduction data; the economic analysis unit can be used to perform economic analysis based on the preliminary energy saving and consumption reduction data and the power generation data to generate the economic analysis data.

[0040] Combination Figure 2 The workflow of the initial configuration module is described in detail.

[0041] The light resource processing unit in the initial configuration module can be used to analyze the light resource data based on the environmental data of the photovoltaic power station, so as to determine the sunshine condition parameters of the photovoltaic power station. The light resource data in the light resource processing unit may include data such as solar irradiance, sunshine duration, and solar altitude angle. The light resource data can be collected and analyzed based on the specific geographical and climatic characteristics of the area where the power station is located. The working principle of the light resource processing unit is to convert the collected environmental data into sunshine condition parameters through preset algorithms and models, so as to accurately reflect the light resource status of the photovoltaic power station area. In a specific implementation, the light resource processing unit can integrate a data acquisition module to receive local sunshine data in real time or extract light resource information from an existing meteorological database. The data acquisition module may include hardware devices such as light sensors and sunshine meters to accurately capture the daily and hourly solar radiation intensity, or use the historical data of the meteorological station for long-term light resource evaluation. It can also be replaced by receiving light resource distribution information through remote sensing technology and satellite data processing systems to calculate the irradiance in a specific time period. In other words, the light resource processing unit provides key input data for subsequent layout design by analyzing sunshine conditions, ensuring that the generated layout structure conforms to the actual situation of light resources.

[0042] The preliminary layout design unit can be used to generate the preliminary layout structure of the photovoltaic module based on the sunshine condition parameters, including the series-parallel configuration of the components, the plane layout, the bracket system setting and the system loss setting. First, the series-parallel configuration of the components is configured based on the sunshine conditions and the electrical parameters of the components according to the voltage and current range required by the system to ensure that the system operates at the maximum power point. The principle of the series-parallel configuration is to connect the photovoltaic components in a specific series and parallel manner to achieve the superposition of voltage and current to meet the input requirements of the inverter. In a specific implementation, the open circuit voltage, short circuit current and temperature coefficient of the components can be calculated, and the number of components and the series-parallel mode can be automatically configured by the controller, or it can be replaced by manually selecting a suitable combination of components. In terms of plane layout, the position of the components is optimized according to parameters such as sunshine angle, component size and arrangement spacing to reduce the impact of shading. The implementation details may include placing the components at the optimal inclination angle of the components, and the calculation of the component spacing is based on the projection area formula and the shadow length. The bracket system setting determines the bracket inclination, material and height according to the sunshine conditions and local wind speed conditions. In different terrains, ground brackets, slope brackets or single-axis tracking brackets can be used to adapt to the environment. In terms of system loss setting, based on the layout structure and bracket configuration, the system loss parameters are comprehensively set by measuring factors such as cable voltage drop and component connection loss, thereby providing a reference for subsequent power generation and energy saving calculations.

[0043] The power generation calculation unit calculates the power generation data of the photovoltaic power station based on the preliminary layout structure of the photovoltaic components. The core of this unit is to use the electrical characteristics of the photovoltaic components and the configuration parameters in the current layout structure, combined with the sunshine condition parameters to deduce the power generation capacity of the power station. The principle of power generation calculation is to obtain accurate data on power generation by real-time simulation of the output current and voltage of the components under different light intensities. In terms of specific implementation methods, modeling can be carried out based on the test data of standard irradiation intensity, combined with temperature coefficient and sunshine hours, to simulate the output of the components in real time. The model can be implemented using software algorithms, such as a power station power generation simulation tool based on Python, or a component electrical characteristics simulation platform based on Simulink, or algorithms such as artificial neural networks can be used to predict and analyze nonlinear changes in sunshine conditions. The implementation method of this unit can select different calculation methods according to actual conditions. For example, under complex terrain conditions, distributed power station simulation can be used to track the power generation of components in each area in real time to avoid calculation deviations caused by unified modeling.

[0044] The energy-saving and consumption-reduction calculation unit performs energy-saving and consumption-reduction calculations based on the power generation data to generate the preliminary energy-saving and consumption-reduction data. The energy-saving and consumption-reduction calculation of this unit involves the evaluation of the equivalent energy-saving amount of photovoltaic power generation replacing traditional fossil energy, and the factors considered include carbon dioxide emission reduction, coal saving, and emission reduction effects of other greenhouse gases. The principle of energy-saving and consumption-reduction calculation is to quantify the environmental benefits of the photovoltaic system by converting the power generation of the photovoltaic system into equivalent fossil energy consumption. In the implementation details, the energy-saving and consumption-reduction data can usually be calculated based on the grid emission factor, that is, the average carbon emissions per unit of power generation, and the specific formula is as follows: energy saving = power generation × emission factor. Of course, it is also possible to convert the coal consumption standard for power production to obtain specific data for energy saving and consumption reduction. For power station projects with large power generation, the carbon emission comparison algorithm can be added to compare the carbon emission differences between different energy sources to more accurately determine the energy-saving and consumption-reduction effects.

[0045] The economic analysis unit performs an economic analysis based on the preliminary energy-saving and consumption-reduction data and the power generation data to generate the economic analysis data. The core of the economic analysis is to evaluate the return on investment of the photovoltaic system, including the initial cost, operation and maintenance cost and long-term benefits. The main indicators of the analysis include net present value, internal rate of return, payback period, etc. The principle of economic analysis is to judge the feasibility of system investment by quantitatively evaluating the power generation income, energy-saving benefits and project costs. In the specific implementation details, it can be calculated through the existing economic analysis model. Typical analysis formulas include: net present value = present value of future cash flow - initial investment, and the internal rate of return is calculated by calculating the future cash flow discount rate to reach the rate of return when the initial investment is made. In order to facilitate economic analysis in different scenarios, the unit can be configured with a variety of methods. For example, in complex investment situations, the Monte Carlo simulation method can be used to predict the investment income under different conditions, or the investment payback period of the system can be quickly evaluated based on the payback period model.

[0046] In some embodiments, the preliminary layout design unit includes a series-parallel configuration subunit, a plane layout calculation subunit, a bracket system configuration subunit, and a system loss setting subunit. Specifically: The series-parallel configuration subunit can be used to calculate the series-parallel configuration matrix of the photovoltaic components based on the sunshine condition parameters. , the matrix elements Indicates The series and The current and voltage characteristics of the PV modules in parallel configuration satisfy the relationship: in, and Respectively represent the current and voltage of a single photovoltaic module, and Represents the number of components in series and parallel respectively.

[0047] The plane layout calculation subunit can be used to calculate the solar radiation condition parameters and the series-parallel configuration matrix. Determining the optimal spacing between PV panels , the optimal spacing is determined by the integral equation to minimize the shadow projection area between components , satisfying the relationship: in, Indicates the coverage area of ​​PV panels, Indicates the location coordinates of the photovoltaic module, is the inclination angle, Represents a function of inclination and position.

[0048] The bracket system configuration subunit can be used based on the optimal spacing and the configuration matrix Calculate the optimal height of the bracket and angle , the height and angle are determined by the following optimization matrix formula: in, represents the bracket height and angle vector, Represents a multidimensional optimization function that depends on the PV module configuration and layout spacing.

[0049] The system loss setting subunit can be used to configure the matrix based on , optimal spacing and bracket parameters Determine the overall loss function of the system , the overall loss function is expressed as: in, and is the loss coefficient, is the coverage area of ​​the PV panels, is the shaded area function.

[0050] In some embodiments, the secondary optimization module includes a power generation optimization unit, a cable calculation unit, a bracket calculation unit, a layout generation unit, and a secondary calculation unit. Among them, the power generation optimization unit can be used to adjust the inclination angle and component spacing of the photovoltaic module based on the preliminary economic analysis data, and the adjustment includes secondary optimization of the inclination angle and component spacing optimization to generate optimized photovoltaic module parameters; the cable calculation unit can be used to perform cable calculation based on the optimized photovoltaic module parameters, and the cable calculation includes length calculation, section selection and voltage drop calculation of string and distributed cables, and generates cable optimization data; the bracket calculation unit can be used to perform bracket calculation based on the cable optimization data and the optimized photovoltaic module parameters, and the bracket calculation includes bracket height calculation and steel consumption statistics, and generates bracket optimization data; the layout generation unit can be used to generate the photovoltaic module layout structure based on the optimized photovoltaic module parameters, the cable optimization data and the bracket optimization data; the secondary calculation unit can be used to calculate the power generation optimization data based on the photovoltaic module layout structure, and determine the energy saving and consumption reduction data and economic analysis data through the power generation optimization data.

[0051] Combination Figure 3 The workflow of the secondary optimization module is described in detail.

[0052] The power generation optimization unit in the secondary optimization module can be used to adjust the inclination angle and component spacing of the photovoltaic module based on the preliminary economic analysis data, and the adjustment includes the secondary optimization of the inclination angle and the optimization of the spacing of the components to generate the optimized photovoltaic module parameters. The power generation optimization unit improves the light receiving effect of the component by optimizing the layout, thereby improving the power generation efficiency. The secondary optimization of the inclination angle is to determine the optimal inclination angle of the component so that it can obtain higher light efficiency under different seasons and sunshine conditions, avoiding seasonal power generation losses caused by the fixed inclination angle setting. In specific implementation, the unit can simulate the light capture effect under each inclination angle with the help of the simulation model of light intensity and incident angle, and select the angle configuration with the largest power generation. At the same time, the spacing optimization of the unit is adjusted according to the optimal spacing of the photovoltaic components to reduce mutual shading between components. Its implementation details include calculating the minimum unobstructed spacing of the components according to the component size, sunshine angle and geographical latitude to avoid power generation losses caused by dense layout. Alternative implementation methods include using an automatic adjustment system to dynamically adjust the inclination and spacing of the components according to the real-time lighting conditions, thereby further improving power generation. The unit forms a photovoltaic module layout that better meets environmental conditions by optimizing the inclination angle and spacing, and ultimately generates the optimal module parameter configuration.

[0053] The cable calculation unit is used to perform cable calculations based on the optimized PV module parameters, including length calculation, cross-section selection and voltage drop calculation of string and distributed cables, and generate cable optimization data. The working principle of the cable calculation unit is to select the appropriate cable cross-section and length by calculating the transmission distance and voltage requirements between the PV module and the inverter or power collection point to ensure that the power loss is minimized during power transmission. The string cable length calculation usually calculates the shortest path length from the string to the inverter based on the layout of the PV strings; while the distributed cable length is calculated in sections based on the distance from the component to the grid access point. In terms of specific implementation details, the cross-section selection of the cable needs to consider the comprehensive requirements of current and voltage drop, and the formula for calculating the cross-sectional area to meet the cable withstand voltage value is used to ensure the safety of the cable under high-power operation. The voltage drop calculation calculates the voltage drop of each section through the line resistance and current, and controls the voltage drop within the preset standard range. Alternative implementation methods may include using a multi-segment cable selection scheme to adjust the cable cross-section of different paths according to voltage requirements to further optimize cost and safety. The unit is optimized in terms of power generation and transmission efficiency, and the generated cable optimization data provides more practical parameters for subsequent bracket and layout design.

[0054] The bracket calculation unit is used to calculate the bracket based on the cable optimization data and the optimized photovoltaic module parameters, including bracket height calculation and steel consumption statistics, and generate bracket optimization data. This unit optimizes the bracket height and structure to enable the photovoltaic module to obtain stable support at different angles and spacings, and reduces the material consumption on the basis of ensuring strength. The principle of bracket height calculation is to determine the optimal support height according to the inclination angle of the photovoltaic module and the ground environmental conditions, so that the module reaches the preset angle. In terms of specific implementation details, the bracket height is usually derived through the geometric relationship between the inclination angle, the module spacing and the illumination angle to form a height configuration suitable for different seasons to avoid shading and dust accumulation problems. The steel consumption statistics are based on the height and width of the bracket, the weight of the module and the wind load standard, and the most suitable bracket material and section thickness are selected through material strength analysis to reduce unnecessary material consumption. Alternative implementation methods may include the use of lightweight and high-strength materials, such as aluminum alloys, composite materials, etc., to reduce the amount of steel and construction costs. The bracket optimization of this unit not only improves the stability and life of the photovoltaic module, but also reduces the material cost, providing solid support structure data for the layout generation unit.

[0055] The layout generation unit is used to generate the layout structure of photovoltaic modules based on the optimized photovoltaic module parameters, cable optimization data and bracket optimization data. The role of this unit is to comprehensively apply the optimized parameters to generate a module layout plan that meets the actual needs of the power station. The design principle of the layout generation unit is to form an efficient module layout plan by integrating the inclination angle, spacing, cable path and bracket height of the photovoltaic modules to ensure that each module is in the best power generation position. In the specific implementation, the layout generation unit calculates the module position through the arrangement algorithm, taking into account the influence of light, terrain and ground obstacles to reduce the overlap of module shadows. In terms of implementation details, the layout generation unit can adopt a partitioned arrangement method to divide the components into multiple sub-areas according to the terrain so as to accurately adjust the arrangement form of each area. Alternative implementation methods may include using intelligent layout software to simulate the power generation efficiency of different layout schemes through three-dimensional modeling, and select the scheme with the highest power generation. The layout generation of this unit ensures the reasonable distribution of photovoltaic modules in the power station area and improves the overall power generation efficiency of the system.

[0056] The secondary calculation unit is used to calculate the power generation optimization data based on the layout structure of the photovoltaic components, and determine the energy-saving and consumption-reduction data and economic analysis data through the power generation optimization data. The core of the secondary calculation unit is to combine the final generated layout structure with the light resource conditions, accurately simulate the power generation of the photovoltaic power station, and further quantify the energy saving and economic benefits. The calculation principle of the power generation optimization data is to predict the power generation output of the photovoltaic power station by inputting the optimized component parameters and layout data, and generate real power generation data. In terms of specific implementation details, the power generation optimization data can be calculated in real time through simulation software based on the sunshine intensity, component electrical characteristics and layout structure. The energy-saving and consumption-reduction data is determined by comparing the power generation with the traditional power consumption to quantify the energy-saving benefits of the system. The economic analysis data is further based on the power generation optimization data and the energy-saving and consumption-reduction data to analyze the return on investment, rate of return, etc. Alternative implementation methods include using machine learning models to fit and predict historical data to further improve the accuracy of the data. The power generation optimization data, energy-saving and consumption-reduction data and economic analysis data generated by the secondary calculation unit provide a scientific decision-making basis for the final design, making the overall performance of the photovoltaic power station more competitive and environmentally friendly.

[0057] In some embodiments, the power generation optimization unit includes a tilt angle optimization calculation subunit, a spacing optimization calculation subunit, and a component parameter matrix generation subunit. Specifically: The inclination optimization calculation subunit can be used to establish an inclination optimization function based on the preliminary economic analysis data. , and determine the optimal inclination angle through the inclination optimization function : in, Indicates at location The photovoltaic module is at an inclination angle The power generation efficiency under Indicates the inclination angle of the photovoltaic module, Indicates the tilt angle of the photovoltaic module The cost function under Indicates the coverage area of ​​PV panels.

[0058] The spacing optimization calculation subunit can be used to establish a spacing optimization model based on the tilt optimization function and the shielding effect between components, and determine the optimal spacing by the following formula: : in, Indicates the optimal inclination and spacing The power generated by photovoltaic modules under Indicates that due to the spacing The occlusion loss function caused by

[0059] The component parameter matrix generation subunit can be used to generate a component parameter matrix based on the optimal inclination angle. and optimal spacing Constructing the PV module parameter matrix : in, and Represent the component current and voltage at the optimal tilt angle and optimal spacing, respectively. and Respectively represent the number of PV panels connected in series and in parallel.

[0060] In some embodiments, the ecological assessment module includes a wind and sand fixation unit, an ecological economic benefit calculation unit, an ecological service value assessment unit, and an ecological benefit determination unit. Among them, the wind and sand fixation unit can be used to calculate the wind and sand impact parameters based on the photovoltaic module layout structure, and the wind and sand impact parameters include the inhibitory effect of the photovoltaic module on the migration of wind and sand, and generate corresponding wind and sand fixation data; the ecological economic benefit calculation unit can be used to calculate the ecological economic benefit parameters based on the wind and sand fixation data, and the ecological economic benefit parameters include the potential income data of agricultural planting and animal husbandry in the photovoltaic power station area; the ecological service value assessment unit can be used to calculate the ecological service value parameters based on the photovoltaic module layout structure, and the ecological service value parameters include the quantitative parameters of soil moisture regulation, surface temperature change and vegetation coverage, and generate ecological service value data for ecological benefit analysis; the ecological benefit determination unit can be used to determine the ecological benefit data based on the wind and sand fixation data, the ecological economic benefit parameters and the ecological service value data.

[0061] Combination Figure 4 The workflow of the ecological assessment module is described in detail.

[0062] The wind and sand fixation unit in the ecological assessment module is used to calculate the wind and sand impact parameters based on the layout structure of photovoltaic modules, which include the inhibitory effect of photovoltaic modules on wind and sand migration, and generate corresponding wind and sand fixation data. The wind and sand fixation unit determines the wind blocking effect of the modules in the wind and sand area by analyzing the layout characteristics of photovoltaic modules, and reduces the wind speed and the degree of sand and dust migration. The core of the wind and sand impact parameters lies in the blocking and deceleration effect formed by the arrangement of modules. This effect is based on the damping principle of fluid mechanics, which disperses or weakens the wind force when it encounters the modules, thereby inhibiting the lateral migration of sand and dust. In the specific implementation method, the wind and sand fixation unit calculates the wind speed reduction coefficient and sand and dust suppression rate by inputting the module height, spacing and arrangement density, and uses the aerodynamic model to generate comprehensive wind and sand fixation data. Alternative implementation methods include using field measurement equipment, setting up wind speed sensors and sand and dust monitoring instruments around the power station to quantitatively record the changes in wind and sand migration and generate corresponding data. The wind and sand fixation unit provides data support for the ecological adaptability of the power station in dust-prone areas by calculating and measuring the inhibitory effect of the module layout on wind and sand.

[0063] The eco-economic benefit calculation unit is used to calculate eco-economic benefit parameters based on wind and sand fixation data, which include potential income data of agricultural planting and animal husbandry in the photovoltaic power station area. This unit estimates the income of agricultural and animal husbandry activities in and around the photovoltaic power station by combining the wind and sand fixation effect. The core of the eco-economic benefit is that the wind and sand fixation effect of photovoltaic modules can create a more stable microenvironment for agriculture and animal husbandry, and reduce the adverse effects of wind and sand on crops and livestock. In terms of specific implementation details, the eco-economic benefit calculation unit uses the income calculation model to evaluate the potential economic benefits brought by agricultural production increase or animal husbandry environment improvement based on the agricultural and animal husbandry planting income standards in the region, combined with data such as wind suppression rate and dust reduction. Alternative implementation methods include constructing a regional simulation model, simulating and analyzing the income increase and decrease effects of different agricultural and animal husbandry models by quantitatively inputting different wind and sand prevention parameters. The eco-economic benefit calculation unit evaluates the positive impact of the photovoltaic power station layout on the surrounding environment from an economic perspective, so that the system brings additional economic value while taking into account the power generation benefits.

[0064] The ecological service value assessment unit is used to calculate the ecological service value parameters based on the layout structure of photovoltaic modules, which include quantitative parameters of soil moisture regulation, surface temperature change and vegetation coverage, and generate ecological service value data for ecological benefit analysis. The core of the ecological service value assessment unit is that the reasonable layout of photovoltaic modules helps to regulate microclimate conditions, such as maintaining soil moisture by blocking sunlight and reducing water evaporation, reducing surface temperature fluctuations and promoting plant growth and coverage. In the specific implementation details, the soil moisture regulation parameters are calculated based on the changes in ambient humidity and evaporation rate by measuring the moisture retention under the shading of the module; the surface temperature change is calculated by the microclimate effect model formed by the module layout, measuring the temperature difference between the shadow area and the exposed area of ​​the module; the vegetation coverage parameter is affected by the shading of the module to evaluate the growth status and coverage ratio of plants inside and outside the photovoltaic power station. An alternative implementation method is to use a field sensor system to record the soil moisture, temperature and vegetation coverage in different areas in real time, and then quantify and analyze the ecological service value of the photovoltaic layout. The ecological service value assessment unit provides quantitative data on the environmental improvement of the power station layout, so that the power station design not only has energy benefits, but also has a positive contribution to the ecological environment.

[0065] The ecological benefit determination unit is used to determine the ecological benefit data based on the windbreak and sand fixation data, ecological economic benefit parameters and ecological service value data. The calculation principle of the ecological benefit is to weight and integrate the parameters and data generated by each unit, and summarize the impacts of windbreak and sand fixation, economic benefits and ecological services according to the preset ecological indicator system. In terms of specific implementation details, the ecological benefit determination unit uses a multi-factor weighted model to assign weights according to the ecological priorities of different regions, such as increasing the weight of windbreak and sand fixation in ecologically sensitive areas, and focusing on the weight of economic benefits in agricultural areas, and finally generating a comprehensive ecological benefit score. Alternative implementation methods include establishing a hierarchical analysis model, and hierarchically dividing and weighting each benefit in a data-driven manner. The ecological benefit determination unit realizes the comprehensive quantification of the ecological impact of the photovoltaic power station layout, provides a decision-making basis for the sustainable design of the power station, and effectively balances the relationship between energy development and environmental protection.

[0066] In some embodiments, the ecological service value assessment unit includes a soil moisture adjustment calculation subunit, a surface temperature change calculation subunit, a vegetation coverage calculation subunit, and an ecological service value data generation subunit. Specifically: The soil moisture adjustment calculation subunit can be used to determine the soil moisture adjustment parameter based on the photovoltaic module layout structure. The calculation formula of the soil moisture adjustment parameter is: in, Indicates soil moisture changes. For photovoltaic modules in position The shading effect of It represents the rate of change of soil moisture per unit time. Indicates the coverage area of ​​PV panels.

[0067] The ground surface temperature change calculation subunit can be used to calculate the ground surface temperature change parameter based on the photovoltaic module layout structure. The calculation formula of the ground surface temperature change parameter is: in, Represents the change in surface temperature, Indicates location The temperature Laplace operator at , is the thermal diffusion coefficient, A function that represents the adjustment function of the component shading effect on the thermal radiation in the area.

[0068] The vegetation coverage rate calculation subunit may be used to calculate a vegetation coverage rate change parameter based on the photovoltaic assembly layout structure, and the vegetation coverage rate parameter is expressed as: in, represents the vegetation coverage vector, represents the growth function matrix, represents the photovoltaic module layout position matrix, Represents the matrix of vegetation growth rates associated with PV panel layout.

[0069] The ecological service value data generation subunit can be used to generate ecological service value data based on the soil moisture adjustment parameter, the surface temperature change parameter and the vegetation coverage change parameter. The calculation formula of the ecological service value data is: in, Represents the ecological service value data.

[0070] In some embodiments, the collaborative optimization module includes an eco-friendly layout unit, a power generation income weight setting unit, an ecological benefit weight setting unit, and a comprehensive optimization scheme generation unit. Among them, the eco-friendly layout unit can be used to adjust the layout structure of the photovoltaic components based on the ecological benefit data, and the adjustment includes optimizing the arrangement mode and support system configuration of the photovoltaic components to generate an eco-friendly layout strategy; the power generation income weight setting unit can be used to set the power generation income weight based on the energy-saving and consumption-reduction data and the economic analysis data; the ecological benefit weight setting unit can be used to set the ecological benefit weight based on the ecological benefit data; the comprehensive optimization scheme generation unit can be used to further optimize the layout structure of the photovoltaic components based on the power generation income weight, the ecological benefit weight and the eco-friendly layout strategy to generate the photovoltaic power station design based on ecological collaborative optimization.

[0071] Combination Figure 5 The workflow of the ecological assessment module is described in detail.

[0072] The eco-friendly layout unit in the collaborative optimization module is used to adjust the layout structure of the photovoltaic components based on the ecological benefit data, wherein the adjustment includes optimizing the arrangement mode and support system configuration of the photovoltaic components to generate an eco-friendly layout strategy. The core of the eco-friendly layout unit is to ensure that the photovoltaic components cause minimal interference to the environment while generating electricity according to the ecological benefit data. The working principle of this unit is to avoid ecological damage and achieve ecological goals such as soil and water conservation and soil moisture regulation through the reasonable arrangement of photovoltaic components and the scientific design of the support structure. In terms of specific implementation details, the optimization of the arrangement mode involves the adjustment of the component spacing and arrangement angle, so that it can effectively reduce the shadow effect and soil moisture evaporation; the support system configuration optimizes the bracket height, inclination and basic materials according to the geological structure and wind data to adapt to the load-bearing requirements in different ecological environments. Alternative implementation methods include using ecological models to simulate the ecological impact of different arrangement schemes and select the layout form with the highest eco-friendliness. Through scientific design, this unit realizes the adaptability of photovoltaic power stations in ecologically sensitive areas and improves the environmental friendliness of the layout structure.

[0073] The power generation income weight setting unit is used to set the power generation income weight based on the energy-saving and consumption-reduction data and the economic analysis data. The core of the power generation income weight setting is to give it a relative priority in layout optimization by quantifying the power generation benefits. The principle is to measure the contribution of power generation to the overall benefits of the system through economic analysis and energy-saving and consumption-reduction results, so that the weight distribution can balance the power generation and other ecological benefits. In the specific implementation details, the setting of the power generation income weight is usually based on the economic return and energy-saving and consumption-reduction per unit of power generation. The calculation formula includes: power generation income weight = unit power generation income × energy saving coefficient / total income, so as to ensure that the power generation income weight occupies an appropriate proportion in the optimization of the system. Alternative implementation methods include fitting the changing trend of power generation income under different conditions through regression analysis of historical data to obtain power generation income weights that are more suitable for different environments. The power generation income weight setting unit provides important reference data for layout optimization through quantitative analysis of power generation income, ensuring the economy of photovoltaic power stations.

[0074] The ecological benefit weight setting unit is used to set the ecological benefit weight based on the ecological benefit data. The core of the ecological benefit weight setting is to determine the relative priority of the photovoltaic power station in the optimization according to its ecological contribution, so as to balance the economic and ecological needs. The principle of setting the ecological benefit weight is to quantify the ecological benefit data into a weight parameter that can be used for layout optimization, which reflects the importance of environmental protection in the overall system. In terms of specific implementation details, the calculation of the ecological benefit weight is based on the weighted summation of various indicators of ecological benefits (such as vegetation restoration, soil conservation and wind and sand suppression). This method makes the ecological benefit weight adapt to different environmental needs. Alternative implementation methods include using a multi-objective optimization algorithm to automatically generate the optimal ecological benefit weight distribution by setting ecological protection goals. The ecological benefit weight setting unit provides ecological benefit data support for layout optimization, making the layout of photovoltaic power stations in ecologically sensitive areas more reasonable.

[0075] The comprehensive optimization scheme generation unit is used to further optimize the layout structure of photovoltaic modules based on the power generation income weight, ecological benefit weight and eco-friendly layout strategy to generate a photovoltaic power station design based on ecological synergistic optimization. The core of the comprehensive optimization scheme generation unit is to ensure that the layout design achieves the best synergistic effect by balancing power generation and ecological benefits. The principle is to comprehensively consider the power generation income and ecological benefits through a multi-objective optimization model to achieve the best balance between the overall income of the power station and ecological protection. In terms of specific implementation details, the comprehensive optimization scheme generation unit uses a weighted multi-objective optimization algorithm to take the power generation income weight and the ecological benefit weight as coefficients of the optimization target and construct the objective function: comprehensive optimization target = power generation income × power generation income weight + ecological benefit × ecological benefit weight. The optimal photovoltaic module layout structure is generated through iterative calculation. Alternative implementation methods include using genetic algorithms or deep learning models to automatically generate the optimal layout plan through a large amount of training data. In summary, the comprehensive optimization scheme generation unit provides a layout design for the synergistic optimization of power generation and ecological protection, laying the foundation for the efficient application of photovoltaic power stations in different ecological environments.

[0076] In some embodiments, the comprehensive optimization solution generation unit includes a weight matrix generation subunit, a multi-objective optimization function subunit, an optimal solution solving subunit and an optimization data output subunit. Specifically: The weight matrix generation subunit can be used to construct an optimized weight matrix based on the power generation income weight and the ecological benefit weight. , the optimization weight matrix is ​​expressed as: in, represents the power generation revenue weight, Represents the ecological benefit weight, which is used to balance the optimization objectives of power generation and ecological benefits.

[0077] The multi-objective optimization function subunit can be used to optimize the weight matrix based on the Construct a multi-objective optimization function with the eco-friendly layout strategy , the multi-objective optimization function is expressed as: in, represents the layout parameter vector, is the balance coefficient, represents the power generation benefit function, represents the ecological benefit function, Represents a layout area.

[0078] The optimal solution solving subunit can be used to solve the multi-objective optimization function to obtain the optimal solution of the photovoltaic assembly layout structure.

[0079] The optimization data output subunit can be used to generate an optimization design data matrix based on the optimal solution of the photovoltaic assembly layout structure, and the optimization design data matrix is ​​expressed as: in, represents the optimization design data matrix, and Respectively represent the spatial position of the component, Indicates the bracket height, Indicates the inclination angle of the PV panel.

[0080] The photovoltaic power station design system based on ecological collaborative optimization in the above embodiment achieves the technical effects of power generation efficiency, cost control and ecological protection through multi-module collaborative design. The initial configuration module generates the preliminary layout structure of the photovoltaic components, and optimizes the arrangement of the photovoltaic components based on the equipment data and environmental data, so that the system takes into account the power generation efficiency and energy saving and consumption reduction goals in the initial layout stage. In addition, through the light resource analysis, layout design, power generation calculation and energy saving analysis in the initial configuration module, it is ensured that the photovoltaic system obtains a reasonable layout and power generation performance in the early stage, providing accurate support for energy saving and consumption reduction and economic analysis. The preliminary layout design unit optimizes the series-parallel configuration, plane layout, bracket height and system loss of the components, so that the layout structure can capture solar energy more efficiently, reduce energy loss and improve the overall power generation efficiency. The secondary optimization module refines the component parameters, improves the accuracy of the power generation optimization data, and ensures that the photovoltaic power station achieves the optimal balance in power generation efficiency and economic benefits. The power generation optimization unit improves the overall power generation efficiency of the system through precise optimization of the inclination angle and component spacing, and ensures that the component layout meets the economic requirements. The ecological assessment module enables the design of photovoltaic power stations to effectively reduce wind and sand migration and resource damage in ecologically sensitive areas through wind and sand fixation, ecological economic benefit calculation and ecological service value assessment, taking into account both ecological protection and power generation benefits. The ecological service value assessment unit improves the photovoltaic power station's ability to regulate regional microclimate through quantitative analysis of soil moisture, surface temperature and vegetation coverage, enabling the system to achieve higher value in ecological services. The collaborative optimization module optimizes the component layout in an eco-friendly manner by setting power generation income and ecological benefit weights to ensure that the system strikes a balance between power generation and ecological protection and adapts to complex environments. The comprehensive optimization solution generation unit generates the optimal layout plan through multi-objective optimization functions and balance coefficients, achieves comprehensive optimization of power generation benefits and ecological benefits, and provides support for the sustainable development of photovoltaic power stations.

[0081] Next, in the embodiment of the present disclosure, a photovoltaic power station design method based on ecological collaborative optimization is also provided. Figure 6 The following schematically shows a flow chart of a photovoltaic power station design method based on ecological collaborative optimization according to some embodiments of the present disclosure. Figure 6 As shown, the photovoltaic power station design method based on ecological collaborative optimization may include the following steps: Step S610, generating a preliminary layout structure of photovoltaic modules based on equipment data and environmental data of the photovoltaic power station, determining power generation data of the photovoltaic power station in combination with photovoltaic module parameters, performing energy saving and consumption reduction calculation and economic analysis based on the power generation data, and obtaining preliminary energy saving and consumption reduction data and preliminary economic analysis data; Step S620, optimizing the photovoltaic module parameters based on the economic analysis data, generating photovoltaic module layout structure and power generation optimization data according to the optimized photovoltaic module parameters, and determining energy saving and consumption reduction data and economic analysis data through the power generation optimization data; Step S630, calculating ecological impact parameters based on the photovoltaic assembly layout structure, and determining ecological benefit data of the photovoltaic power station according to the ecological impact parameters; Step S640, setting the power generation income weight and the ecological benefit weight based on the ecological benefit data, the energy-saving and consumption-reduction data and the economic analysis data, so as to optimize the photovoltaic component layout structure and generate a photovoltaic power station design plan based on ecological collaborative optimization.

[0082] It should be noted that, although the steps of the method in the present disclosure are described in a specific order in the drawings, this does not require or imply that the steps must be performed in this specific order, or that all the steps shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps, etc.

[0083] In addition, in an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above-mentioned photovoltaic power station design method based on ecological collaborative optimization is also provided.

[0084] Those skilled in the art will appreciate that various aspects of the present disclosure may be implemented as systems, methods or program products. Therefore, various aspects of the present disclosure may be specifically implemented in the following forms, namely: complete hardware embodiments, complete software embodiments (including firmware, microcode, etc.), or embodiments combining hardware and software aspects, which may be collectively referred to herein as "circuits", "modules" or "systems".

[0085] Refer to the following Figure 7 Detailed description of the electronic device 700 provided according to an embodiment of the present disclosure. Figure 7 The electronic device 700 shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0086] like Figure 7As shown, the electronic device 700 is in the form of a general computing device. The components of the electronic device 700 may include but are not limited to: the at least one processing unit 710, the at least one storage unit 720, a bus 730 connecting different system components (including the storage unit 720 and the processing unit 710), and a display unit 740.

[0087] The storage unit stores program codes, which can be executed by the processing unit 710, so that the processing unit 710 executes the steps according to various exemplary embodiments of the present disclosure described in the above “Exemplary Method” section of this specification.

[0088] The storage unit 720 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 721 and / or a cache memory unit 722 , and may further include a read-only memory unit (ROM) 723 .

[0089] The storage unit 720 may also include a program / utility 724 having a set (at least one) of program modules 725, such program modules 725 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0090] Bus 730 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0091] The electronic device 700 may also communicate with one or more external devices 770 (e.g., keyboards, pointing devices, Bluetooth devices, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 700, and / or communicate with any device that enables the electronic device 700 to communicate with one or more other computing devices (e.g., routers, modems, etc.). This communication may be performed through an input / output (I / O) interface 750. In addition, the electronic device 700 may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) through a network adapter 760. As shown, the network adapter 760 communicates with other modules of the electronic device 700 through a bus 730. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 700, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0092] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the example embodiments described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the embodiment of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes a number of instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiment of the present disclosure.

[0093] In an exemplary embodiment of the present disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the above method of the present specification is stored. In some possible embodiments, various aspects of the present disclosure can also be implemented in the form of a program product, which includes a program code. When the program product is run on a terminal device, the program code is used to enable the terminal device to execute the steps according to various exemplary embodiments of the present disclosure described in the above "Exemplary Method" section of the present specification.

[0094] refer to Figure 8 As shown, a program product 800 for implementing the above-mentioned photovoltaic power station design method based on ecological collaborative optimization according to an embodiment of the present disclosure is described, which can adopt a portable compact disk read-only memory (CD-ROM) and include program code, and can be run on a terminal device, such as a personal computer. However, the program product of the present disclosure is not limited thereto. In this document, a readable storage medium can be any tangible medium containing or storing a program, which can be used by or in combination with an instruction execution system, an apparatus, or a device.

[0095] The program product may adopt any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination thereof. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0096] Computer readable signal media may include data signals propagated in baseband or as part of a carrier wave, in which readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Readable signal media may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0097] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A photovoltaic power station design system based on ecological collaborative optimization, characterized in that: include: An initial configuration module is used to generate a preliminary layout structure of photovoltaic modules based on equipment data and environmental data of the photovoltaic power station, and determine the power generation data of the photovoltaic power station in combination with photovoltaic module parameters, perform energy saving and consumption reduction calculation and economic analysis based on the power generation data, and obtain preliminary energy saving and consumption reduction data and preliminary economic analysis data; A secondary optimization module, used for optimizing the photovoltaic module parameters based on the economic analysis data, generating photovoltaic module layout structure and power generation optimization data according to the optimized photovoltaic module parameters, and determining energy saving and consumption reduction data and economic analysis data through the power generation optimization data; An ecological assessment module, used to calculate ecological impact parameters based on the photovoltaic assembly layout structure, and determine ecological benefit data of the photovoltaic power station according to the ecological impact parameters; The collaborative optimization module is used to set the power generation income weight and the ecological benefit weight based on the ecological benefit data, the energy-saving and consumption-reduction data and the economic analysis data, so as to optimize the layout structure of the photovoltaic components and generate a photovoltaic power station design plan based on ecological collaborative optimization.

2. The photovoltaic power station design system according to claim 1, characterized in that: The initial configuration module includes: A light resource processing unit, used to analyze light resource data based on environmental data of the photovoltaic power station and determine sunshine condition parameters of the photovoltaic power station; A preliminary layout design unit, used to generate the preliminary layout structure of the photovoltaic components based on the sunshine condition parameters, including the series-parallel configuration of the components, the plane layout, the bracket system settings and the system loss settings; A power generation calculation unit, used to calculate power generation data of the photovoltaic power station based on the preliminary layout structure of the photovoltaic components; an energy-saving and consumption-reduction calculation unit, configured to perform energy-saving and consumption-reduction calculation based on the power generation data to generate the preliminary energy-saving and consumption-reduction data; An economic analysis unit is used to perform economic analysis based on the preliminary energy-saving and consumption-reduction data and the power generation data to generate the economic analysis data.

3. The photovoltaic power station design system according to claim 2, characterized in that: The preliminary layout design unit includes: A series-parallel configuration subunit, used to calculate the series-parallel configuration matrix of the photovoltaic components based on the sunshine condition parameters , the matrix elements Indicates The series and The current and voltage characteristics of the PV modules in parallel configuration satisfy the relationship: in, and Respectively represent the current and voltage of a single photovoltaic module, and Represents the number of components in series and in parallel respectively; A plane layout calculation subunit is used to calculate the solar radiation condition parameters and the series-parallel configuration matrix. Determining the optimal spacing between PV panels , the optimal spacing is determined by the integral equation to minimize the shadow projection area between components , satisfying the relationship: in, Indicates the coverage area of ​​PV panels, Indicates the location coordinates of the photovoltaic module, is the inclination angle, A function representing the inclination angle and position; The bracket system configures the subunits for optimal spacing based on the and the configuration matrix Calculate the optimal height of the bracket and angle , the height and angle are determined by optimizing the matrix formula: in, represents the bracket height and angle vector, represents a multidimensional optimization function that depends on the PV module configuration and layout spacing; System loss setting subunit for configuring the matrix based on the , optimal spacing and bracket parameters Determine the overall loss function of the system , the overall loss function is expressed as: in, and is the loss coefficient, Indicates the coverage area of ​​PV panels, Represents the shaded area function.

4. The photovoltaic power station design system according to claim 1, characterized in that: The secondary optimization module includes: A power generation optimization unit, used for adjusting the inclination angle and the spacing of the photovoltaic modules based on the preliminary economic analysis data, wherein the adjustment includes secondary optimization of the inclination angle and optimization of the spacing of the modules, so as to generate optimized photovoltaic module parameters; A cable calculation unit, used to perform cable calculation based on the optimized photovoltaic module parameters, wherein the cable calculation includes length calculation, cross-section selection and voltage drop calculation of string and distributed cables, and generates cable optimization data; A bracket calculation unit, used to perform bracket calculation based on the cable optimization data and the optimized photovoltaic module parameters, wherein the bracket calculation includes bracket height calculation and steel consumption statistics, and generates bracket optimization data; A layout generating unit, configured to generate the photovoltaic assembly layout structure based on the optimized photovoltaic assembly parameters, the cable optimization data and the bracket optimization data; The secondary calculation unit is used to calculate the power generation optimization data based on the photovoltaic assembly layout structure, and determine the energy-saving and consumption-reduction data and economic analysis data through the power generation optimization data.

5. The photovoltaic power station design system according to claim 4, characterized in that: The power generation optimization unit comprises: The inclination angle optimization calculation subunit is used to establish an inclination angle optimization function based on the preliminary economic analysis data. , and determine the optimal inclination angle through the inclination optimization function : in, Indicates at location The photovoltaic module is at an inclination angle The power generation efficiency under Indicates the inclination angle of the photovoltaic module, Indicates the tilt angle of the photovoltaic module The cost function under Indicates the coverage area of ​​PV panels; The spacing optimization calculation subunit is used to establish a spacing optimization model based on the tilt optimization function and the shielding effect between components, and according to: Determine the optimal spacing ,in, Indicates the optimal inclination and spacing The power generated by photovoltaic modules under Indicates that due to the spacing The occlusion loss function caused by The component parameter matrix generation subunit is used to generate a component parameter matrix based on the optimal inclination angle. and optimal spacing Constructing the PV module parameter matrix : in, and Represent the component current and voltage at the optimal tilt angle and optimal spacing, respectively. and Respectively represent the number of PV panels connected in series and in parallel.

6. The photovoltaic power station design system according to claim 1, characterized in that: The ecological assessment module includes: A wind and sand fixing unit, used to calculate wind and sand impact parameters based on the photovoltaic module layout structure and generate corresponding wind and sand fixing data; An ecological and economic benefit calculation unit, used to calculate ecological and economic benefit parameters based on the windbreak and sand fixation data, wherein the ecological and economic benefit parameters include potential income data of agricultural planting and animal husbandry in the photovoltaic power station area; An ecological service value assessment unit, used to calculate ecological service value parameters based on the photovoltaic module layout structure, the ecological service value parameters including quantitative parameters of soil moisture regulation, surface temperature change and vegetation coverage, and generate ecological service value data for ecological benefit analysis; The ecological benefit determination unit is used to determine the ecological benefit data based on the windbreak and sand fixation data, the ecological economic benefit parameters and the ecological service value data.

7. The photovoltaic power station design system according to claim 6, characterized in that: The ecological service value assessment unit includes: The soil moisture adjustment calculation subunit is used to determine the soil moisture adjustment parameter based on the photovoltaic module layout structure. The calculation formula of the soil moisture adjustment parameter is: in, Indicates soil moisture changes. For photovoltaic modules in position The shading effect of It represents the rate of change of soil moisture per unit time. Indicates the coverage area of ​​PV panels; The ground surface temperature change calculation subunit is used to calculate the ground surface temperature change parameter based on the photovoltaic module layout structure. The calculation formula of the ground surface temperature change parameter is: in, Represents the change in surface temperature, Indicates location The temperature Laplace operator at , is the thermal diffusion coefficient, The regulating function representing the shading effect of the components on the thermal radiation in the area; The vegetation coverage rate calculation subunit is used to calculate the vegetation coverage rate change parameter based on the photovoltaic module layout structure, and the vegetation coverage rate parameter is expressed as: in, represents the vegetation coverage vector, represents the growth function matrix, represents the photovoltaic module layout position matrix, represents the matrix of vegetation growth rates associated with the PV panel layout; The ecological service value data generating subunit is used to generate ecological service value data based on the soil moisture adjustment parameter, the surface temperature change parameter and the vegetation coverage change parameter. The calculation formula of the ecological service value data is: in, Represents the ecological service value data.

8. The photovoltaic power station design system according to claim 1, characterized in that: The collaborative optimization module includes: An eco-friendly layout unit, configured to adjust the layout structure of the photovoltaic components based on the eco-efficiency data, wherein the adjustment includes optimizing the arrangement of the photovoltaic components and the configuration of the support system to generate an eco-friendly layout strategy; A power generation income weight setting unit, used to set the power generation income weight based on the energy-saving and consumption-reduction data and the economic analysis data; An ecological benefit weight setting unit, used to set an ecological benefit weight based on the ecological benefit data; A comprehensive optimization scheme generating unit is used to optimize the photovoltaic component layout structure based on the power generation income weight, the ecological benefit weight and the eco-friendly layout strategy to generate the photovoltaic power station design based on ecological collaborative optimization.

9. The photovoltaic power station design system according to claim 8, characterized in that: The comprehensive optimization scheme generating unit comprises: A weight matrix generation subunit is used to construct an optimized weight matrix based on the power generation income weight and the ecological benefit weight. , the optimization weight matrix is ​​expressed as: in, represents the power generation revenue weight, Represents the ecological benefit weight, which is used to balance the optimization goals of power generation and ecological benefits; A multi-objective optimization function subunit is used to optimize the weight matrix based on the Construct a multi-objective optimization function with the eco-friendly layout strategy , the multi-objective optimization function is expressed as: in, represents the layout parameter vector, is the balance coefficient, represents the power generation benefit function, represents the ecological benefit function, Indicates the layout area; An optimal solution solving subunit, used to solve the multi-objective optimization function to obtain an optimal solution for the photovoltaic module layout structure; The optimization data output subunit is used to generate an optimization design data matrix based on the optimal solution of the photovoltaic module layout structure, and the optimization design data matrix is ​​expressed as: in, represents the optimization design data matrix, and Respectively represent the spatial position of the component, Indicates the bracket height, Indicates the inclination angle of the PV panel.

10. A photovoltaic power station design method based on ecological collaborative optimization, characterized in that: include: Generate a preliminary layout structure of photovoltaic modules based on equipment data and environmental data of the photovoltaic power station, determine power generation data of the photovoltaic power station in combination with photovoltaic module parameters, perform energy saving and consumption reduction calculation and economic analysis based on the power generation data, and obtain preliminary energy saving and consumption reduction data and preliminary economic analysis data; Optimizing the photovoltaic module parameters based on the economic analysis data, generating photovoltaic module layout structure and power generation optimization data according to the optimized photovoltaic module parameters, and determining energy saving and consumption reduction data and economic analysis data through the power generation optimization data; Calculating ecological impact parameters based on the photovoltaic assembly layout structure, and determining ecological benefit data of the photovoltaic power station according to the ecological impact parameters; The power generation income weight and the ecological benefit weight are set based on the ecological benefit data, the energy-saving and consumption-reduction data and the economic analysis data to optimize the layout structure of the photovoltaic components and generate a photovoltaic power station design plan based on ecological collaborative optimization.

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