Design methods and related products for distributed photovoltaic power generation projects

Abstract

The present invention provides a design method and related products for a distributed photovoltaic power generation project. The design method for a distributed photovoltaic power generation project includes: obtaining a construction evaluation criterion system for a distributed photovoltaic power generation project, the evaluation criterion system includes multiple evaluation levels, and the bottom layer of the evaluation level is configured with multiple project construction influencing factors; assigning values ​​to the bottom layer of the evaluation level according to the design scheme of the distributed photovoltaic power generation project to be built, and obtaining the relationship of influencing factors; calculating the relationship of influencing factors according to the factor weights corresponding to each project construction influencing factor, and obtaining multiple criterion parameters of the middle layer in the evaluation level; comprehensively evaluating multiple criterion parameters, and obtaining the decision-making evaluation results of the distributed photovoltaic power generation project to be built; and adjusting the design scheme according to the decision-making evaluation results. The scheme of the present invention can fully match the needs of construction owners and greatly improve the satisfaction of construction owners.

Description

Technical Field

[0001] The present invention relates to the field of photovoltaic design, and in particular to a design method for a distributed photovoltaic power generation project. Background Art

[0002] As a new type of clean energy, the photovoltaic industry has been supported and developed by countries around the world due to its clean and renewable characteristics. Distributed photovoltaic power generation has also become an important part of the photovoltaic industry due to its advantages of adapting to local conditions, nearby power generation and grid connection, and low transmission loss. For residents, especially rural residents with more abundant land and space resources, the combination of household distributed photovoltaic power generation and household energy storage is more advantageous. The household distributed photovoltaic power generation and energy storage system not only has the advantages of adapting to local conditions, generating electricity for self-use, and surplus storage, but also improves energy utilization efficiency, reduces peak power demand, and overcomes grid losses. The development of household distributed photovoltaic power generation and household energy storage systems has an important impact on promoting the development of the photovoltaic industry.

[0003] However, the popularity of household distributed photovoltaic power generation and household energy storage in my country is still in its early stages, and the market still has huge room for growth. How to promote the further popularization of distributed photovoltaic power generation and promote the transformation and upgrading of energy consumption structure has become an important topic in the research of distributed photovoltaic power generation projects.

[0004] Design work is an important work in the early stage of household distributed photovoltaic power generation projects. The existing distributed photovoltaic power generation design work still requires a lot of manpower. Designers design according to the survey data of the construction area and the construction needs of the owner to form a design plan. Such a design process has high repetitiveness, low design efficiency, long design cycle time and high design cost, which seriously affects the construction progress and promotion of distributed photovoltaic power generation systems.

[0005] Based on this problem, some automatic design methods for distributed photovoltaic power generation projects have also emerged in the existing technology. These methods preset a certain number of design templates, match them with the characteristics of the construction area, and apply the design templates to form a design plan. However, this automatic design method has poor flexibility and cannot meet the special requirements of the construction area. In addition, there is a lack of verification methods to determine whether the design plan obtained using the design template matches the construction needs of the project owner, which leads to a decrease in the satisfaction of construction users. Summary of the invention

[0006] An object of the present invention is to improve the owner satisfaction of distributed photovoltaic power generation projects.

[0007] Another object of the present invention is to fully evaluate the design of distributed photovoltaic power generation projects.

[0008] Another object of the present invention is to improve the accuracy and precision of surveying the area to be designed.

[0009] In particular, the present invention provides a design method for a distributed photovoltaic power generation project. The method comprises:

[0010] Obtain a construction evaluation criteria system for distributed photovoltaic power generation projects, the evaluation criteria system includes multiple evaluation levels, and the bottom layer of the evaluation level is configured with multiple project construction influencing factors;

[0011] According to the design plan of the distributed photovoltaic power generation project to be built, the lowest evaluation level is assigned a value to obtain the influencing factor relationship;

[0012] The relationship between the influencing factors is calculated according to the factor weights corresponding to each project construction influencing factor, and multiple criterion parameters of the middle layer in the evaluation hierarchy are obtained;

[0013] Comprehensively evaluate multiple criteria parameters to obtain decision-making evaluation results for the distributed photovoltaic power generation project to be built;

[0014] Adjust the design plan based on the decision evaluation results.

[0015] Optionally, the middle layer criteria include: equipment criteria, resource and environment criteria, ownership criteria, income criteria, and risk criteria;

[0016] The lower-level project construction influencing factors of the equipment criteria include: photovoltaic unit indicators, energy storage unit indicators, and grid equipment indicators;

[0017] The factors affecting project construction at the lower level of resource and environmental criteria include: climate impact, construction impact;

[0018] The factors affecting project construction at the lower level of the tenure criterion include: electricity price impact, neighboring impact;

[0019] The factors affecting project construction at the lower level of the revenue criterion include: cost impact, profit impact;

[0020] The factors affecting the construction of lower-level projects include: weather risks and building safety risks.

[0021] Optionally, the step of assigning a value to the lowest evaluation level according to the design plan of the distributed photovoltaic power generation project to be built includes:

[0022] Establish a set of evaluation object factors based on the construction evaluation criteria system;

[0023] Determine the level of the evaluation object according to the evaluation object factor set;

[0024] Obtaining quantitative indicators obtained by grading the lowest level of evaluation according to the level of the evaluation object;

[0025] Establish a fuzzy relationship matrix based on quantitative indicators.

[0026] Optionally, the step of calculating the relationship between the influencing factors according to the factor weight corresponding to each of the project construction influencing factors includes:

[0027] Obtain a factor weight vector pre-constructed for the project construction influencing factors, the factor weight vector having the factor weight corresponding to each project construction influencing factor as an element;

[0028] The fuzzy relationship matrix is ​​multiplied by the factor weight vector to obtain multiple criterion parameters of the middle layer.

[0029] Optionally, the step of comprehensively evaluating multiple criterion parameters includes:

[0030] The evaluation level with the largest statistical probability value among multiple criterion parameters is taken as the decision evaluation result;

[0031] When the evaluation level is lower than the preset level, it is determined that the design solution needs to be adjusted.

[0032] Optionally, the step of comprehensively evaluating multiple criterion parameters includes:

[0033] Perform weighted calculation on multiple criterion parameters and use the result of the weighted calculation as the decision evaluation result;

[0034] When the result of the weighted calculation is less than a preset threshold, it is determined that the design solution needs to be adjusted.

[0035] Optionally, before the step of assigning a value to the lowest evaluation level according to the design plan of the distributed photovoltaic power generation project to be built, the step further includes:

[0036] Obtain basic information on the construction area of ​​the distributed photovoltaic power generation project to be built;

[0037] Control the drone to take photos of the construction area based on the basic information to obtain survey images;

[0038] Generate a 3D model of the construction area based on the survey images;

[0039] Analyze the three-dimensional model to obtain survey characteristic data of the photovoltaic panel laying area;

[0040] The photovoltaic panel laying area is simulated and designed according to the survey characteristic data to obtain one or more design solutions.

[0041] Optionally, the basic information includes: location information, terrain information, and grid access equipment information; and

[0042] The step of obtaining the location information and the terrain information includes: reading the location information and the terrain information from the location of the construction area selected in the preset map;

[0043] The step of acquiring the information of the grid-connected device includes: sending a query request to the grid management device according to the location information, and acquiring the information of the grid-connected device in response to the query request from the grid management device.

[0044] Optionally, the step of controlling the drone to photograph the construction area according to the basic information includes:

[0045] Control the drone to conduct initial survey and photography of the construction area to obtain the initial image;

[0046] Setting marker points on the initial image, dividing the initial image into objects based on the marker points, so as to at least determine the installation object and surrounding environment objects, and estimate the area and terrain characteristics of the installation object;

[0047] Design an aerial photography plan based on the area and terrain characteristics of the installation object. The aerial photography plan includes the flight parameters and shooting parameters of the drone.

[0048] Controlling the UAV to perform a first survey and photography around the installation object according to the aerial photography plan to obtain a survey image of the installation object;

[0049] Controlling the UAV to perform a second survey and shooting of the surrounding environment objects to obtain a survey image of the surrounding environment objects;

[0050] The survey image of the installation object and the survey image of the surrounding environment objects are spliced ​​to obtain a survey image of the construction area.

[0051] Optionally, the step of generating a three-dimensional model of the construction area according to the survey image includes:

[0052] Discretize the survey image using set grid points to generate point cloud data of the construction area;

[0053] Use point cloud data to construct the surface and obtain the surface model;

[0054] Perform object recognition on survey images to determine object boundaries;

[0055] Compare the object boundary with the surface model and perform contour segmentation on the surface model;

[0056] The surface model after contour segmentation is subjected to object entity processing to obtain contour surfaces of multiple objects;

[0057] Collect color and pattern features of multiple objects in survey images;

[0058] Perform appearance processing on the contour surfaces of multiple objects according to color and pattern features to obtain a three-dimensional model of the construction area;

[0059] Data statistics are performed on the three-dimensional model to obtain data information of the three-dimensional model, and attribute information is assigned to multiple objects of the three-dimensional model.

[0060] According to another aspect of the present invention, there is also provided a computer program product, comprising a computer program, which implements the steps of any of the above-mentioned methods for designing a distributed photovoltaic power generation project when executed by a processor.

[0061] According to another aspect of the present invention, there is also provided a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of any of the above-mentioned methods for designing a distributed photovoltaic power generation project are implemented.

[0062] According to another aspect of the present invention, a computer device is provided, which includes a memory, a processor and a computer program stored in the memory, and the processor executes the computer program to implement the steps of any of the above-mentioned methods for designing a distributed photovoltaic power generation project.

[0063] The design method of the distributed photovoltaic power generation project of the present invention establishes a construction evaluation criterion system for the distributed photovoltaic power generation project. The evaluation criterion system includes multiple evaluation levels, and the bottom layer of the evaluation level is configured with multiple project construction influencing factors. The design scheme of the distributed photovoltaic power generation project to be built is evaluated through the evaluation criterion system, so as to determine that the design scheme fully matches the needs of the construction owner, thereby greatly improving the satisfaction of the construction owner.

[0064] Furthermore, the design method of the distributed photovoltaic power generation project of the present invention optimizes the evaluation criteria system and the process of using the evaluation criteria system to conduct decision-making evaluation of the distributed photovoltaic power generation project to be built, wherein the intermediate layer criteria include equipment criteria, resource and environmental criteria, ownership criteria, income criteria, and risk criteria, which fully consider the influencing factors that affect the design scheme of the distributed photovoltaic power generation project.

[0065] Furthermore, the design method of the distributed photovoltaic power generation project of the present invention uses drones to photograph the design area and its surrounding environment. With the help of the drone's flexibility and low cost, it solves the problems of increased survey difficulty and inaccurate survey data caused by harsh on-site environment, improves planning efficiency, and reduces the workload of surveyors.

[0066] Based on the following detailed description of specific embodiments of the present invention in conjunction with the accompanying drawings, those skilled in the art will become more aware of the above and other objects, advantages and features of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Hereinafter, some specific embodiments of the present invention will be described in detail in an exemplary and non-limiting manner with reference to the accompanying drawings. The same reference numerals in the accompanying drawings indicate the same or similar components or parts. It should be understood by those skilled in the art that these drawings are not necessarily drawn to scale. In the accompanying drawings:

[0068] Figure 1 is a schematic diagram of a design method for a distributed photovoltaic power generation project according to an embodiment of the present invention;

[0069] Figure 2 is a schematic diagram of a process for assigning values ​​to evaluation levels in a design method for a distributed photovoltaic power generation project according to an embodiment of the present invention;

[0070] Figure 3 It is a schematic diagram of a flow chart for calculating the relationship between influencing factors in a design method for a distributed photovoltaic power generation project according to an embodiment of the present invention;

[0071] Figure 4 is a flow chart for determining a design scheme to be evaluated in a design method for a distributed photovoltaic power generation project according to an embodiment of the present invention;

[0072] Figure 5 This is a schematic diagram of a process of aerial photography by a drone in a design method for a distributed photovoltaic power generation project according to an embodiment of the present invention;

[0073] Figure 6 is a schematic diagram of a process for generating a three-dimensional model in a design method for a distributed photovoltaic power generation project according to an embodiment of the present invention;

[0074] Figure 7 It is a schematic diagram of the system architecture of UAV survey and design in a design method for a distributed photovoltaic power generation project using an embodiment of the present invention;

[0075] Figure 8 is a schematic diagram of a computer program product according to an embodiment of the present invention;

[0076] Fig. 9 is a schematic diagram of a computer-readable storage medium according to an embodiment of the present invention; and

[0077] Fig.10 is a schematic block diagram of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0078] It should be understood by those skilled in the art that the embodiments described below are only some embodiments of the present invention, rather than all embodiments of the present invention, and these embodiments are intended to explain the technical principles of the present invention, rather than to limit the protection scope of the present invention. Based on the embodiments provided by the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should still fall within the protection scope of the present invention.

[0079] This embodiment first provides a design method for a distributed photovoltaic power generation project. By constructing a construction evaluation criterion system for distributed photovoltaic power generation projects, combined with the construction and application characteristics of distributed photovoltaic power generation projects and the characteristics of the applications, a decision-making evaluation is performed on the design scheme of the distributed photovoltaic power generation project to be built, and the design scheme is adjusted in a targeted manner.

[0080] Figure 1 Schematic diagram of a design method for a distributed photovoltaic power generation project according to an embodiment of the present invention. The design method for a distributed photovoltaic power generation project may generally include:

[0081] Step S101, obtaining a construction evaluation criterion system for a distributed photovoltaic power generation project, the evaluation criterion system including multiple evaluation levels, the bottom layer of the evaluation level being configured with multiple project construction influencing factors;

[0082] Step S102, assigning values ​​to the lowest evaluation level according to the design scheme of the distributed photovoltaic power generation project to be built, and obtaining an influencing factor relationship;

[0083] Step S103, calculating the relationship between the influencing factors according to the factor weights corresponding to each project construction influencing factor, and obtaining a plurality of criterion parameters of the middle layer in the evaluation hierarchy;

[0084] Step S104, comprehensively evaluating multiple criterion parameters to obtain a decision evaluation result of the distributed photovoltaic power generation project to be built;

[0085] Step S105: adjusting the design solution according to the decision evaluation result.

[0086] In some optional embodiments, the evaluation criteria system includes three evaluation levels. Table 1 shows the construction evaluation criteria system of the three evaluation levels applied in the design method of the distributed photovoltaic power generation project of this embodiment.

[0087] Table 1

[0088]

[0089] The construction assessment criteria system for distributed photovoltaic power generation projects in this embodiment selects construction influencing factors based on the principles of scientific rationality, relative comprehensiveness, and feasibility. As shown in Table 1, the middle-layer criteria include: equipment criteria, resource and environmental criteria, ownership criteria, income criteria, and risk criteria. Among them, the lower-level project construction influencing factors of the equipment criteria include: photovoltaic unit indicators, energy storage unit indicators, and power grid equipment indicators; the lower-level project construction influencing factors of the resource and environmental criteria include: climate impacts and construction impacts; the lower-level project construction influencing factors of the ownership criteria include: electricity price impacts and adjacent impacts; the lower-level project construction influencing factors of the income criteria include: cost impacts and profit impacts; the lower-level project construction influencing factors of the risk criteria include: weather risks and building safety risks.

[0090] The photovoltaic unit index reflects the performance of the photovoltaic units used in distributed photovoltaic power generation projects, which may include the photovoltaic power conversion efficiency (IPCE). There will be differences in IPCE between different types of photovoltaic units (monocrystalline silicon, polycrystalline silicon, etc.) and between different specifications of the same photovoltaic units.

[0091] The energy storage unit index reflects the performance of the energy storage batteries used in distributed photovoltaic power generation projects, which may include battery energy density and battery attenuation value.

[0092] The grid equipment indicators reflect the equipment performance and capacity of distributed photovoltaic power generation projects connected to the grid, which may include access capacity, power transmission loss, shock resistance, etc.

[0093] Climate impact reflects the situation of solar energy resources, which can include the average annual sunshine hours and the average annual solar radiation.

[0094] Construction impact reflects the convenience of construction, which may include building structure conditions, material transportation conditions, and the impact on people's living and work.

[0095] Electricity prices directly affect the economic benefits of distributed photovoltaic power generation projects, which may include grid-connected electricity prices, electricity prices, electricity price subsidies, and electricity price time periods.

[0096] Neighboring impacts reflect the rights and interests of stakeholders in distributed photovoltaic power generation projects, which may include: the complexity of property rights of the construction object, the degree of community support, the degree of support from neighboring units, etc.

[0097] Cost impact reflects the construction and operation costs of distributed photovoltaic power generation projects, which may include capital costs, construction costs, operation and maintenance costs, etc.

[0098] Profit impact reflects the benefits of distributed photovoltaic power generation projects, which can be economic benefits, social benefits, environmental benefits, etc.

[0099] Weather risk reflects the impact of extreme weather on distributed photovoltaic power generation projects, which may include earthquake risk, strong wind risk, hail risk, etc.

[0100] Building safety risks reflect the risks of building load, water leakage and electric leakage, etc.

[0101] The above-mentioned design method of distributed photovoltaic power generation projects has established a construction evaluation criteria system for distributed photovoltaic power generation projects. The evaluation criteria system includes multiple evaluation levels, and the bottom layer of the evaluation level is configured with multiple project construction influencing factors. The evaluation criteria system is used to make decision-making evaluations on the design schemes of the distributed photovoltaic power generation projects to be built, thereby determining whether the design schemes fully match the needs of the construction owners, greatly improving the satisfaction of the construction owners.

[0102] Figure 2 The following is a flow chart of assigning values ​​to the evaluation levels in the design method of a distributed photovoltaic power generation project according to an embodiment of the present invention. The step of assigning values ​​to the lowest evaluation level according to the design scheme of the distributed photovoltaic power generation project to be built may include:

[0103] Step S201, establish an evaluation object factor set according to the construction evaluation criteria system. The evaluation object factor set can be n evaluation object factors from X1, X2, X3, ... to Xn for evaluation, which can be expressed as X = {X1, X2, X3, ..., Xn}, where n is the number of evaluation object factors.

[0104] Step S202, determining the evaluation object grade according to the evaluation object factor set. The evaluation object grade can be, for example, a grade description method of excellent, good, medium, poor, or none. It can be expressed as Y={Y1, Y2, Y3, ..., Ym}, where m is the number of evaluation object grades. The evaluation object grade can be described and scored by relevant experts, for example, an excellent score of 81-100, a good score of 61-80, a medium score of 41-60, a poor score of 21-40, and a no score of 0-20. The proportion of the above-mentioned grade description method can confirm the fuzzy relationship matrix corresponding to the evaluation object grade in the fuzzy evaluation.

[0105] For example, for climate impact, the annual average radiation G satisfies G ≥ 1750 kWh / m 2 In the case of G, it is rated as excellent; 1750kWh / m2>G≥1400kWh / m 2 In the case of 1400kWh / m 2 >G≥1050kWh / m 2 In the case of 2 >G, it is rated as poor.

[0106] Step S203, obtain the quantitative index obtained by grading the lowest evaluation level according to the evaluation object level. Each factor in the evaluation object factor set X has a corresponding relationship with each level in the evaluation object level Y. The corresponding relationship is recorded as Rn, and the corresponding relationship from X to Y is R = {R1, R2, R3, ..., Rn}.

[0107] Step S204: Establish a fuzzy relationship matrix based on the quantitative index. The fuzzy relationship matrix finally obtained can be identified as:

[0108]

[0109] Through the above process, qualitative indicators can be converted into quantifiable quantitative indicators.

[0110] Figure 3 The figure is a flow chart of calculating the relationship of influencing factors in a design method for a distributed photovoltaic power generation project according to an embodiment of the present invention. The step of calculating the relationship of influencing factors according to the factor weights corresponding to each project construction influencing factor includes:

[0111] Step S301 : obtaining a factor weight vector pre-constructed for project construction influencing factors, wherein the factor weight vector has the factor weight corresponding to each project construction influencing factor as an element.

[0112] Step S302, performing a dot product calculation on the fuzzy relationship matrix and the factor weight vector to obtain a plurality of criterion parameters of the middle layer.

[0113] The process of constructing the factor weight vector may include: selecting any two project construction influencing factors from the construction influencing factors to judge their importance; forming a judgment matrix based on the results of the importance judgment; and performing a consistency check on the judgment matrix. One execution process of the step of performing a consistency check on the judgment matrix may include: calculating the maximum eigenvector of the judgment matrix; calculating the inconsistency index based on the maximum eigenvector; calculating the ratio of the inconsistency index to the preset random consistency index, and if the ratio is less than the preset threshold, the consistency check result is judged to be qualified; normalizing the judgment matrix with a qualified consistency check result to obtain the factor weight vector.

[0114] The judgment matrix is ​​generated by comparing the factors affecting the construction of two types of projects. The importance of factors can be determined by comparing and analyzing the degree of influence. Two factors xi and xj are randomly selected, and aij is used to represent the ratio of the importance of xi to xj to construct a judgment matrix. Assuming there is a judgment matrix A with n elements, then for each element Ai, there is a corresponding judgment value ai, which indicates the importance of the element relative to another element. The judgment matrix A can be represented as an n×n matrix, in which each row and column corresponds to an element, and the position (i, j) of each element indicates the importance of the element Ai relative to Aj. In some embodiments, the 9-scaling method is used to determine the weight of the indicator. The judgment matrix scale is generally represented by 1-9 and their reciprocals. The specific meanings of the numbers are shown in Table 2.

[0115] Table 2

[0116] Calibration definition 1 Factor i is equally important as factor j. 3 Compared with factor i, factor j is slightly more important than factor i. 5 Compared with factor i, factor j is more important than factor i. 7 Factor i is more important than factor j. 9 Factor i is equally important as factor j.

[0117] In Table 2, the larger the calibration score, the greater the importance of factor i relative to factor j. When taking values, 2, 4, 6, and 8 indicate that the importance is between the importance corresponding to the values ​​in the table. Correspondingly, if the calibration score of factor i relative to factor j is n, then the calibration score of factor j relative to factor i is 1 / n, that is, the importance represented by the reciprocal is opposite to that of the integer.

[0118] Then compare the indicators one by one, fill the importance results into the table below, and get the judgment matrix of the hierarchical analysis method. The judgment matrix can be expressed as:

[0119]

[0120] Among them, the element aij represents the relative importance of factor i and factor j.

[0121] The above importance assignment can be obtained by analyzing the previous data, or it can be scored by experts in related fields. After the judgment matrix is ​​constructed, a consistency test is required. After the judgment matrix is ​​constructed, a consistency test is required. Let λmax(A) be the maximum eigenvector in matrix A, then the inconsistency index CI can be set as: The meaning of CI is CI=0, A is completely consistent; the larger the CI, the more serious the inconsistency of A.

[0122] The random consistency index RI is set to a preset value. For an n-order judgment matrix, the setting of the RI value can be shown in Table 3.

[0123] Table 3

[0124] n 1 2 3 4 5 6 7 8 9 10 11 RI 0 0 0.58 0.9 1.12 1.24 1.32 1.41 1.45 1.49 1.51

[0125] Calculate the ratio of the inconsistency index to the preset random consistency index CR = CI / RI. When CR < 0.1, the judgment matrix is ​​judged to meet the consistency (the consistency test result is qualified); if not, the judgment matrix can be modified, and the importance of factors xi and xj can be re-set until the judgment matrix meets the consistency. The above preset ratio threshold of 0.1 can be adjusted according to the evaluation requirements.

[0126] After obtaining a judgment matrix with a qualified consistency test result, the judgment matrix is ​​normalized to obtain the final factor weight vector. The normalization process can be: first normalize the column vector of the matrix, that is, the sum of the values ​​of the elements in each column is 1 (the proportional relationship of each element remains unchanged), then sum each row and normalize again, that is, add up the elements of each row separately, take the accumulated sum as the value of each row, and then normalize so that the sum of the values ​​of each row is 1 (the proportional relationship of the elements in each row remains unchanged). The final factor weight vector is obtained.

[0127] Similarly, the comprehensive weight vector can also be constructed using the above process. First, by comparing the influence of the factors affecting the construction of each project, a judgment matrix is ​​constructed, and after a consistency check, a normalization process is performed to obtain a comprehensive weight vector. Since the construction process of the comprehensive weight vector is similar to the construction process of the factor weight vector, those skilled in the art can realize the construction of the comprehensive weight vector according to the construction method of the factor weight vector.

[0128] Table 4 shows example data of importance judgment of each criterion in the middle layer:

[0129] Table 4

[0130]

[0131] After normalization and a flower test, the weight vector of the weight factors of each criterion in the middle layer is finally obtained:

[0132] ω={1.7227, 0.2709, 2.4770, 0.7369, 0.2353} T

[0133] The above-mentioned weight factor weight vectors are only for illustration purposes, and those skilled in the art can configure them accordingly according to the construction goals and requirements of different projects. Similarly, those skilled in the art can set the weight factor weight vectors for the project construction influencing factors of each intermediate layer criterion accordingly. In combination with the model of the installation environment and the operating characteristics of the photovoltaic components, the optimal distributed photovoltaic power generation design can be determined according to different requirements. In some embodiments, the method of this embodiment can pre-configure a variety of weight factor weight vectors according to different construction requirements, such as the minimum configuration cost requirement, the maximum laying area requirement, the best photovoltaic conversion efficiency requirement, the best economic performance requirement, the minimum installation difficulty requirement, and other different weight vectors.

[0134] The process of comprehensively evaluating multiple criterion parameters can use the maximum membership method or the weighted average method. When the maximum membership method is used, the step of comprehensively evaluating multiple criterion parameters includes: taking the evaluation level with the largest statistical probability value among the multiple criterion parameters as the decision evaluation result; when the evaluation level is lower than the preset level, it is determined that the design scheme needs to be adjusted.

[0135] For example, one fuzzy comprehensive evaluation result is: S = (0.4, 0.25, 0.15, 0.1, 0.1), where the evaluation level with the largest statistical probability value is excellent, and its maximum statistical probability value is 0.4. At this time, the decision evaluation result is considered to be excellent, and the design solution is evaluated to pass. For another example, the fuzzy comprehensive evaluation result is: S = (0.10, 0.40, 0.30, 0.1, 0.1), where the evaluation level with the largest statistical probability value is good, and its maximum statistical probability value is 0.40. At this time, the decision evaluation result is considered to be good. If the preset level is excellent, the design solution needs to be adjusted.

[0136] When the weighted average method is used, the step of comprehensively evaluating multiple criterion parameters includes: performing weighted calculation on the multiple criterion parameters, and using the result of the weighted calculation as the decision evaluation result; when the result of the weighted calculation is less than a preset threshold, determining that the design solution needs to be adjusted.

[0137] For example, a fuzzy comprehensive evaluation result is: S = (0.4, 0.25, 0.15, 0.1, 0.1), the weights are set to (5, 4, 3, 2, 1), and the weighted average is calculated to be: 0.75, which is higher than the preset threshold of 0.7, and the design scheme is evaluated as passed. For another example, the fuzzy comprehensive evaluation result is: S = (0.10, 0.40, 0.30, 0.1, 0.1), and the weighted average is calculated to be: 0.66, which is lower than the preset threshold of 0.7, and the design scheme needs to be adjusted.

[0138] The design scheme in the method of this embodiment can be automatically generated through drone survey. Figure 4 The present invention is a flow chart of determining a design scheme to be evaluated in a design method for a distributed photovoltaic power generation project according to an embodiment of the present invention. Before assigning a value to the lowest evaluation level according to the design scheme of the distributed photovoltaic power generation project to be built, the following steps may also be included:

[0139] Step S401, obtain the basic information of the construction area of ​​the distributed photovoltaic power generation project to be built. The basic information may include: location information, terrain information, and grid access equipment information. The location information includes the geographical coordinates (latitude and longitude) of the construction area, the administrative area address (administrative divisions, road house numbers), and the distance to surrounding markers. The terrain information includes the altitude, slope and slope direction (the degree of inclination and inclination direction of the ground), the type of foundation layout (roof, wall, ground, other supports), landform type, and infrastructure information (foundation surface flatness, foundation surface covering type). The grid access equipment information includes the access transformer capacity, inverter type, PCS specifications, etc.

[0140] The step of obtaining the position information and terrain information may include: reading the position information and terrain information from the position of the construction area selected in the preset map. The map may be a digital map, which is obtained by digitally processing geographic information using computer technology, and in addition to graphics, may also include terrain data, vector data, description information and other related data. In actual application, the method of this embodiment can determine the position of the construction area on the digital map through the selection operation of the surveyor on the map or according to the input selection information, and read the corresponding position information and terrain information. The position information and terrain information are used as positioning information for surveying on the one hand, and can also be used as basic data for surveying on the other hand.

[0141] The step of obtaining the information of the equipment connected to the grid includes: sending a query request to the grid management device according to the location information, and obtaining the information of the equipment connected to the grid in response to the query request from the grid management device. The grid management device can find the corresponding equipment information connected to the grid according to the grid deployment data of the construction area. The equipment information connected to the grid can be used to limit the technical indicators and economic indicators of the photovoltaic system, such as providing the capacity limit parameters of the photovoltaic system, the consumable cost of the photovoltaic equipment connected to the grid (cable specifications and quantity, transformer and PCS expansion cost, etc.), and the grid's restriction conditions for absorbing microgrid power transmission (whether to operate reverse transmission to the grid, and the grid electricity price).

[0142] Step S402: Control the drone to take photos of the construction area according to the basic information to obtain a survey image. The survey image can be multiple images at different angles, reflecting the conditions of the construction area at different angles.

[0143] Step S403: Generate a three-dimensional model of the construction area based on the survey image.

[0144] Step S404: Analyze the three-dimensional model to obtain survey feature data of the photovoltaic panel laying area. The survey feature data includes: shape, area, inclination, orientation, height, etc. of the photovoltaic panel laying area.

[0145] Step S405, performing simulation design on the photovoltaic panel laying area according to the survey characteristic data to obtain one or more design solutions.

[0146] The above process uses drones to take pictures of the construction area to obtain survey images. With the help of the drone's flexibility and low cost, the field survey results can be obtained quickly and efficiently. A three-dimensional model of the construction area is further generated based on the survey image; the three-dimensional model is analyzed to obtain the survey feature data of the photovoltaic panel laying area. The survey process is fast and efficient, reducing the workload of survey personnel and solving the problems of increased survey difficulty and inaccurate survey data caused by the harsh on-site environment.

[0147] The obtained design schemes can be used as the targets of the above decision-making evaluation in turn. The design schemes include the project construction influencing factors required for the evaluation.

[0148] Figure 5 The figure is a flow chart of drone aerial photography in a design method for a distributed photovoltaic power generation project according to an embodiment of the present invention. The steps of controlling the drone to photograph the construction area according to basic information include:

[0149] Step S501, control the drone to perform initial survey and photography of the construction area to obtain an initial image. The initial survey and photography can be performed using the drone's default cruise mode, for example, the drone photographs the construction area at a certain height in a preset scanning photography mode (such as reciprocating along a straight line). The initial image obtained is used to gain a general understanding of the construction area.

[0150] Step S502, set marker points for the initial image, and divide the initial image into objects based on the marker points to at least determine the installation object and the surrounding environment objects, and estimate the regional area and terrain characteristics of the installation object. The marker points can be obtained by analyzing the initial image, for example, by finding obvious marker points using pixel threshold segmentation, edge detection, regional growth clustering, machine learning model classification, etc. The marker points may include points such as demarcation points, edge points, feature intensity change points, cluster centers or representative points. In addition to the installation objects (installation roofs, installation walls, vacant ground, etc.), the objects obtained by object division may also include the basic objects of the installation objects (installed building objects, walls, supports, etc.). The estimated regional area and terrain characteristics of the installation object are used for the formulation of the aerial photography plan, not the final survey results.

[0151] Step S503, design an aerial photography plan according to the area and terrain characteristics of the installation object. The aerial photography plan includes the flight parameters and shooting parameters of the drone. The flight parameters may include calculating the navigation altitude, speed, route length, flight time and other data. To ensure the accuracy of the measurement, the same target position can be photographed from at least three directions. The aerial photography plan requires that the captured images have a certain degree of overlap to facilitate subsequent stitching. The aerial photography plan can shoot in multiple directions and at multiple heights for the installation object.

[0152] Step S504, control the drone to perform a first survey and shooting around the installation object according to the aerial photography plan to obtain a survey image of the installation object. The shooting point can be arranged in an open, unobstructed location with a large shooting range. After the first survey and shooting is completed, the shooting quality of the survey image (such as clarity, overlap, occlusion status, etc.) can be checked. If an image that does not meet the requirements appears, repeat the shooting. The survey image of the installation object may include images taken from multiple directions and multiple heights from multiple shooting points.

[0153] Step S505, control the drone to perform a second survey and photography of the surrounding environment objects to obtain a survey image of the surrounding environment objects. The second survey and photography photographs the periphery of the installation object to obtain an image reflecting the overall state of the construction area.

[0154] Step S506, stitching the survey image of the installation object and the survey image of the surrounding environment object to obtain the survey image of the construction area. An optional survey image stitching method includes: performing angle matching on the survey image of the installation object and the survey image of the surrounding environment object to find multiple pairs of matching images; performing grayscale histogram equalization processing and geometric distortion elimination on the multiple pairs of matching images to obtain multiple groups of images to be stitched; extracting feature information from the multiple groups of images to be stitched, stitching and fusing the images according to the feature information, and obtaining survey images of the construction area from multiple angles.

[0155] Angle matching can be done by searching for images with similar shooting directions and shooting ranges through the flight records of drones. The matching images found have similar angles, which can reduce the image calculations (including image translation, scaling, and twisting) in the stitching process and improve processing efficiency. Grayscale histogram equalization and geometric distortion elimination can eliminate the problems caused by geometric distortion and color brightness differences in image processing.

[0156] Feature information is extracted from multiple groups of images to be spliced, and an image transformation model can be established based on the matched features, and finally transformation mapping is performed. The transformation mapping of the method of this embodiment first uses point, line and angle features to estimate the homography matrix of the global transformation, and pre-aligns the spliced ​​images; then the image is gridded, and the grid deformation is constrained by the energy function to achieve grid refinement alignment. Since the shooting angle is matched in advance, the complexity of the image transformation model can be reduced. The image alignment process can use a feature-based image registration method. Alignment is performed by adding feature line segments and feature points of the shooting angle, which greatly reduces the amount of calculation. For example, the scale-invariant feature transformation algorithm (ScaleInvariant Feature Transform, referred to as SIFT) can be used to determine the feature points of the image and the angle information of the feature points; for example, the line segment detector (LSD) can be used to extract the straight line characteristics of the image.

[0157] Image stitching and fusion are performed based on feature information to convert each pixel of the transformed image into the same image, and then the image fusion method is used to perform pixel fusion on the transition area of ​​the stitched image to optimize the image stitching quality.

[0158] The survey images of the construction area obtained in the above steps reflect the characteristics of the installation object and the surrounding environment objects from different angles. Compared with the prior art in which surveyors manually set up markers and aerial photography points for the construction area, the method of this embodiment uses three aerial photography to complete the entire survey task, designs the aerial photography plan with the help of the initial images obtained by the initial survey, and automatically completes the aerial photography task, which has a higher accuracy rate and reduces the dependence on the operation of the surveyors.

[0159] Figure 6 The present invention is a schematic diagram of a process for generating a three-dimensional model in a design method for a distributed photovoltaic power generation project according to an embodiment of the present invention. The steps of generating a three-dimensional model of a construction area according to a survey image include:

[0160] Step S601, discretize the survey image using set grid points to generate point cloud data of the construction area. One discretization method is: discretize using three-dimensional space grid points, and then sample a point in each grid point. Each small grid contains several points, and the point closest to the center point of the grid is taken as the discrete sampling point.

[0161] Step S602, using the point cloud data to construct a surface to obtain a surface model. The data captured by the drone can be processed to obtain sufficient point cloud data. Through surface construction, a surface model in the form of a point cloud can be obtained.

[0162] Step S603: perform object recognition on the survey image to determine the object boundary. The object recognition results include: installation objects (installation roofs, installation walls, vacant ground, etc.), basic objects of installation objects (installed building objects, walls, supports, etc.), surrounding environment objects, etc.

[0163] Step S604: compare the object boundary with the surface model and perform contour segmentation on the surface model.

[0164] Step S605 , performing object entity processing on the surface model after contour segmentation to obtain contour surfaces of multiple objects.

[0165] Step S606: collecting color and pattern features of multiple objects in the survey image.

[0166] Step S607, performing appearance processing on the contour surfaces of the multiple objects according to the color and pattern features to obtain a three-dimensional model of the construction area.

[0167] Step S608, perform data statistics on the three-dimensional model to obtain data information of the three-dimensional model, and assign attribute information to multiple objects of the three-dimensional model. The data information of the three-dimensional model includes: coordinates, elevation data, area, length, height, slope, direction, etc., which can be read from the three-dimensional model.

[0168] The final three-dimensional model of the construction area is similar to the actual visual state of the construction area, which is convenient for the owners of the photovoltaic system to intuitively understand the situation of the construction area. By performing data statistics on the three-dimensional model, the data information of the three-dimensional model can be obtained, thereby conveniently assigning values ​​to the lowest evaluation level, obtaining the relationship between influencing factors, and conducting subsequent decision-making evaluations.

[0169] When the drone survey automatically designs multiple schemes, after evaluating the multiple design schemes, the design scheme with the best evaluation result can be selected. Another way is to eliminate unqualified design schemes, and the owner or relevant personnel of the construction unit will select from the qualified design schemes and give the final decision to the owner and relevant personnel.

[0170] If the drone survey automatically designs a single design plan, if the design plan passes the evaluation, it is confirmed that the design plan is feasible; if the design plan passes the evaluation, some design data can be manually modified and re-evaluated.

[0171] Figure 7 The system architecture diagram of the UAV survey design in the design method of the distributed photovoltaic power generation project according to an embodiment of the present invention is shown in FIG. The system may include: a UAV 10, a wireless communication device 20, a data processing device 30, and an interactive terminal 40.

[0172] The drone 10 may include: a flight control system, a positioning system, an aerial photography system, and a measurement system. The flight control system is used to adjust the flight attitude (including altitude, speed, and direction) of the drone, and the positioning system is used to obtain the location information of the drone 10, which may use positioning devices such as GPS and Beidou. The aerial photography system is used to photograph the target during flight. In order to realize the functions of the method of this embodiment, the aerial photography system uses a camera with adjustable focal length and shooting parameters that meet the design requirements. The measurement system is used to record the flight process of the drone 10 and collect status data such as flight altitude, flight attitude, and shooting parameters.

[0173] The drone 10 exchanges data with the data processing device 30 through the wireless communication device 20, and transmits its own flight data and the data of the airborne equipment (positioning system, aerial photography system, and measurement system) to the data processing device 30. The data processing device 30 collects and processes the data provided by the drone 10 to complete the flight control of the drone 10. With the characteristics of the drone's flexibility and low cost, it completes the functions that cannot be achieved by traditional manual surveys, greatly improving the processing efficiency.

[0174] The wireless communication device 20 can select a communication method according to actual communication conditions, such as 5G, Wi-Fi, Bluetooth, etc. The interactive terminal 40 is data-connected to the drone 10 and the data processing device 30, respectively, and can display the interface generated by the drone 10 and the data processing device 30, and serve as an interactive device with survey and design personnel to provide manual instructions to the drone 10 and the data processing device 30, and adjust the operating status and processing results of the drone 10 and the data processing device 30. The interactive terminal 40 may include a personal computer, a smart phone, a tablet computer, or other dedicated electronic client devices with a survey application installed.

[0175] This embodiment also provides a computer program product 112 , a computer readable storage medium 113 , and a computer device 114 . Figure 8 is a schematic diagram of a computer program product 112 according to one embodiment of the present invention, Fig. 9 is a schematic diagram of a computer-readable storage medium 113 according to an embodiment of the present invention, Fig.10 is a schematic block diagram of a computer device 114 according to one embodiment of the present invention.

[0176] The computer program product 112 includes a computer program 111, which implements the steps of any of the above-mentioned methods for designing distributed photovoltaic power generation projects when executed by the processor 310. The computer-readable storage medium 113 stores the above-mentioned computer program 111, which implements the steps of any of the above-mentioned methods for designing distributed photovoltaic power generation projects when executed by the processor 310. The computer device 114 may include a memory 320, a processor 310, and a computer program 111 stored in the memory 320 and running on the processor 310.

[0177] The computer program 111 used to perform the operations of the present invention can be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, configuration data of an integrated circuit, or source code or object code written in any combination of one or more programming languages ​​and procedural programming languages.

[0178] The computer program 111 may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the latter case, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, in order to perform various aspects of the present invention, electronic circuits including, for example, programmable logic circuits, field programmable gate arrays (FPGAs), or programmable logic arrays (PLAs) may execute computer-readable program instructions by utilizing state information of the computer-readable program instructions to personalize the electronic circuits.

[0179] In the description of this embodiment, the computer program product 112 is a related product including the computer program 111 .

[0180] For the purposes of the description of this embodiment, the computer-readable storage medium 113 is a tangible device capable of retaining and storing the computer program 111, which may be any device that can contain, store, communicate, propagate or transmit the program 111 for use with or in conjunction with an instruction execution system, device or apparatus. More specific examples (a non-exhaustive list) of the computer-readable storage medium 113 include the following: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, and any suitable combination of the foregoing.

[0181] At this point, those skilled in the art should recognize that, although multiple exemplary embodiments of the present invention have been shown and described in detail herein, many other variations or modifications that conform to the principles of the present invention can still be directly determined or derived based on the content disclosed in the present invention without departing from the spirit and scope of the present invention. Therefore, the scope of the present invention should be understood and recognized as covering all these other variations or modifications.

Claims

1. A design method for a distributed photovoltaic power generation project, characterized in that include: Obtaining a construction evaluation criteria system for a distributed photovoltaic power generation project, wherein the evaluation criteria system includes multiple evaluation levels, and the bottom layer of the evaluation level is configured with multiple project construction influencing factors; Assigning values ​​to the bottom evaluation level according to the design plan of the distributed photovoltaic power generation project to be built, and obtaining the influencing factor relationship; Calculating the relationship between the influencing factors according to the factor weight corresponding to each of the project construction influencing factors to obtain a plurality of criterion parameters of the middle layer in the evaluation hierarchy; Comprehensively evaluating the multiple criterion parameters to obtain a decision-making evaluation result of the distributed photovoltaic power generation project to be built; The design solution is adjusted according to the decision evaluation result.

2. The design method of a distributed photovoltaic power generation project according to claim 1, wherein The middle-level criteria include: Equipment criteria, resource and environment criteria, ownership criteria, income criteria, and risk criteria; The lower-level project construction influencing factors of the equipment criteria include: photovoltaic unit indicators, energy storage unit indicators, and power grid equipment indicators; The factors affecting project construction at the lower level of the resource and environmental criteria include: climate impact, construction impact; The factors affecting the construction of the lower level projects of the said tenure criterion include: electricity price impact, neighboring impact; The factors affecting the construction of lower-level projects under the revenue criterion include: cost impact, profit impact; The lower-level project construction influencing factors of the risk criteria include: weather risk and building safety risk.

3. The design method of a distributed photovoltaic power generation project according to claim 2, wherein: The step of assigning a value to the lowest evaluation level according to the design plan of the distributed photovoltaic power generation project to be built comprises: Establishing an evaluation object factor set according to the construction evaluation criteria system; Determining the level of the evaluation object according to the evaluation object factor set; Obtaining quantitative indicators obtained by grading the bottom evaluation level according to the level of the evaluation object; A fuzzy relationship matrix is ​​established according to the quantitative indicators.

4. The design method of a distributed photovoltaic power generation project according to claim 3, wherein: The step of calculating the relationship between the influencing factors according to the factor weight corresponding to each of the project construction influencing factors comprises: Obtaining a factor weight vector pre-constructed for the project construction influencing factor, wherein the factor weight vector has the factor weight corresponding to each of the project construction influencing factors as an element; The fuzzy relationship matrix is ​​multiplied by the factor weight vector to obtain a plurality of criterion parameters of the middle layer.

5. The design method of a distributed photovoltaic power generation project according to claim 2, wherein: The step of comprehensively evaluating the multiple criterion parameters comprises: Taking the evaluation level with the largest statistical probability value among the multiple criterion parameters as the decision evaluation result; When the evaluation level is lower than a preset level, it is determined that the design solution needs to be adjusted.

6. The design method of a distributed photovoltaic power generation project according to claim 2, wherein: The step of comprehensively evaluating the multiple criterion parameters comprises: Performing weighted calculation on the multiple criterion parameters, and using the result of the weighted calculation as the decision evaluation result; When the result of the weighted calculation is less than a preset threshold, it is determined that the design solution needs to be adjusted.

7. The design method of a distributed photovoltaic power generation project according to any one of claims 1 to 6, wherein: Before the step of assigning a value to the lowest evaluation level according to the design scheme of the distributed photovoltaic power generation project to be built, the method further includes: Obtain basic information on the construction area of ​​the distributed photovoltaic power generation project to be built; Controlling the drone to photograph the construction area according to the basic information to obtain a survey image; generating a three-dimensional model of the construction area according to the survey image; Analyzing the three-dimensional model to obtain survey characteristic data of the photovoltaic panel laying area; The photovoltaic panel laying area is simulated and designed according to the survey feature data to obtain one or more design solutions.

8. The design method of a distributed photovoltaic power generation project according to claim 7, wherein: The basic information includes: location information, terrain information, and grid access equipment information; and The step of acquiring the position information and the terrain information comprises: reading the position information and the terrain information from the position of the construction area selected in a preset map; The step of acquiring the grid access device information includes: sending a query request to a grid management device according to the location information, and acquiring the grid access device information from the grid management device in response to the query request.

9. The design method of a distributed photovoltaic power generation project according to claim 8, wherein: The step of controlling the drone to photograph the construction area according to the basic information includes: Controlling the UAV to perform initial survey and photography of the construction area to obtain an initial image; Setting marker points on the initial image, and dividing the initial image into objects based on the marker points to at least determine the installation object and surrounding environment objects, and estimating the area and terrain characteristics of the installation object; Designing an aerial photography plan according to the area and terrain characteristics of the installation object, wherein the aerial photography plan includes flight parameters and shooting parameters of the drone; Controlling the unmanned aerial vehicle to perform a first survey and photography around the installation object according to the aerial photography plan to obtain a survey image of the installation object; Controlling the UAV to perform a second survey and photography of the surrounding environment object to obtain a survey image of the surrounding environment object; The survey image of the installation object and the survey image of the surrounding environment object are spliced ​​to obtain a survey image of the construction area.

10. The design method of a distributed photovoltaic power generation project according to any one of claims 7 to 9, characterized in that: The step of generating the three-dimensional model of the construction area according to the survey image comprises: discretize the survey image using set grid points to generate point cloud data of the construction area; Using the point cloud data to construct a surface to obtain a surface model; Performing object recognition on the survey image to determine the object boundary; Comparing the object boundary with the surface model, and performing contour segmentation on the surface model; Performing object entity processing on the surface model after the contour segmentation to obtain contour surfaces of multiple objects; collecting color and pattern features of the plurality of objects in the survey image; Performing appearance processing on the contour surfaces of the plurality of objects according to the color and pattern features to obtain a three-dimensional model of the construction area; Data statistics are performed on the three-dimensional model to obtain data information of the three-dimensional model, and attribute information is assigned to multiple objects of the three-dimensional model.

11. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the design method of a distributed photovoltaic power generation project described in any one of claims 1 to 10 are implemented.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that When the computer program is executed by a processor, the steps of the method for designing a distributed photovoltaic power generation project according to any one of claims 1 to 10 are implemented.

13. A computer device comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the steps of the method for designing a distributed photovoltaic power generation project according to any one of claims 1 to 10.

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