Solar energy resource development potential assessment method, system, device and storage medium

Abstract

An embodiment of the present invention provides a method, system, device, and storage medium for evaluating solar energy resource development potential. The method includes: using a preset comprehensive analysis model to calculate solar energy resource data, permitted area data, and surrounding environment data for each candidate area to obtain development data for each candidate area; screening out to-be-developed areas from each candidate area based on the development data; performing a multi-layer overlay analysis operation on the development data of the to-be-developed areas based on the spatial coordinates of the to-be-developed areas using a preset GIS spatial analysis algorithm to obtain spatial image data for each to-be-developed area, wherein there is a one-to-one correspondence between the spatial image data and the to-be-developed areas; and calculating a solar energy resource development potential score for each to-be-developed area based on the spatial image data using a preset entropy weight algorithm. This demonstrates that the present invention achieves the purpose of improving the accuracy of evaluating solar energy resource development potential.

Description

Technical Field

[0001] The present invention relates to the field of data processing, and in particular to a method, system, device and storage medium for evaluating solar energy resource development potential. Background Art

[0002] Solar energy, a renewable, clean energy source, is gaining increasing attention. Currently, when evaluating the development of a region's solar resources, the typical approach is to divide candidate areas into overall development zones and then calculate their potential value. However, existing technologies fail to objectively analyze the economic viability, buildability, and timeliness of candidate areas. Furthermore, when calculating the value of potential development zones, experts assign weights based on their subjective perceptions. Consequently, existing technologies suffer from low accuracy when assessing the development potential of solar resources. Summary of the Invention

[0003] The purpose of the embodiments of the present invention is to provide a method, system, device, and storage medium for evaluating solar resource development potential, thereby achieving the invention's purpose of improving the accuracy of evaluating solar resource development potential. The specific technical solution is as follows:

[0004] A method for evaluating solar energy resource development potential, comprising:

[0005] Calculate solar energy resource data, permitted area data, and surrounding environment data of each candidate area using a preset comprehensive analysis model to obtain development data of each candidate area, and select areas to be developed from each candidate area based on the development data;

[0006] Based on the spatial coordinates of the areas to be developed, a preset GIS spatial analysis algorithm is used to perform a multi-layer overlay analysis operation on the development data of the areas to be developed to obtain spatial image data of each area to be developed, wherein the spatial image data has a one-to-one correspondence with the areas to be developed;

[0007] Based on the spatial image data, a preset entropy weight algorithm is used to calculate the solar energy resource development potential score of each area to be developed.

[0008] Optionally, the development data includes solar energy utilization rate, terrain suitability, and economic suitability; the preset comprehensive analysis model includes a preset solar energy resource assessment model, a preset terrain analysis model, and a preset surrounding feature analysis model; the preset comprehensive analysis model is used to calculate the solar energy resource data, permitted area data, and surrounding environment data of each candidate area to obtain development data for each candidate area; and the areas to be developed are screened from each candidate area based on the development data, including:

[0009] Using the preset solar resource evaluation model, the solar resource data of the candidate area is evaluated to obtain the solar energy utilization rate of the candidate area; using the preset terrain analysis model, the permitted area data of the candidate area is analyzed to obtain the terrain suitability of the candidate area; using the preset surrounding feature analysis model, the surrounding environment data of the candidate area is analyzed to obtain the economic suitability of the candidate area;

[0010] The area to be developed is screened out from various candidate areas based on the solar energy utilization rate, the terrain suitability and the economic suitability.

[0011] Optionally, based on the spatial coordinates of the area to be developed, a preset GIS spatial analysis algorithm is used to perform a multi-layer overlay analysis operation on the development data of the area to be developed to obtain spatial image data of each area to be developed, including:

[0012] For each of the areas to be developed:

[0013] According to the spatial coordinates of the area to be developed, a digital map of the area to be developed is obtained using the preset GIS spatial analysis algorithm;

[0014] Using the preset GIS spatial analysis algorithm, the digital map of the area to be developed and the development data are subjected to a multi-layer overlay analysis operation according to the land parcel correspondence relationship to obtain the spatial image data of the area to be developed, wherein the spatial image data is image data composed of multiple land parcels, and the land parcel correspondence relationship is the relationship between each land parcel and the development data that has a spatial correspondence relationship with the land parcel.

[0015] Optionally, the step of calculating the solar energy resource development potential score of each area to be developed based on the spatial image data using a preset entropy weight algorithm includes:

[0016] For each of the areas to be developed: performing data preprocessing on each plot in the spatial image data of the area to be developed;

[0017] For each land parcel that has undergone data preprocessing: calculating the proportion of the data value of each data type in the development data corresponding to the land parcel to the sum of the data values ​​of each data type in the development data corresponding to the land parcel, wherein the proportion has a one-to-one correspondence with the data type;

[0018] Calculating the information entropy of data of each data type according to the proportion;

[0019] Calculate, based on the information entropy, a weight value of the information entropy value of each data type in the development data corresponding to the land parcel, as a percentage of the sum of the information entropy values ​​of each data type in the development data corresponding to the land parcel, wherein the weight value has a one-to-one correspondence with the data type;

[0020] Multiply the data value of each data type by the weight value of the data type to obtain the first score of the data type;

[0021] Summing up the first scores of each data type in the development data corresponding to the land parcel to obtain a second score of the land parcel;

[0022] The second scores of the blocks in the area to be developed are summed to obtain the solar energy resource development potential score of the area to be developed.

[0023] Optionally, the method further includes:

[0024] For each area to be developed:

[0025] Mapping the solar resource development potential score of the area to be developed to a preset solar resource development potential table through data mapping, and determining the development time series type of the area to be developed according to the block to which the solar resource development potential score belongs in the preset solar resource development potential table;

[0026] The color code corresponding to the development time sequence type is added to the spatial image data of the area to be developed.

[0027] A solar energy resource development potential assessment system, comprising:

[0028] The regional screening module uses a preset comprehensive analysis model to calculate the solar energy resource data, permitted area data and surrounding environment data of each candidate area to obtain the development data of each candidate area, and screens the areas to be developed from each candidate area based on the development data;

[0029] A data acquisition module, based on the spatial coordinates of the to-be-developed area and using a preset GIS spatial analysis algorithm, performs a multi-layer overlay analysis operation on the development data of the to-be-developed area to obtain spatial image data of each to-be-developed area, wherein the spatial image data has a one-to-one correspondence with the to-be-developed area;

[0030] The scoring acquisition module calculates the solar energy resource development potential score of each area to be developed based on the spatial image data using a preset entropy weight algorithm.

[0031] Optionally, the development data includes solar energy utilization rate, terrain suitability, and economic suitability; the preset comprehensive analysis model includes a preset solar resource assessment model, a preset terrain analysis model, and a preset surrounding feature analysis model; and the regional screening module is configured to:

[0032] Using a preset solar resource evaluation model, the solar resource data of the candidate area is evaluated to obtain the solar energy utilization rate of the candidate area; using a preset terrain analysis model, the permitted area data of the candidate area is analyzed to obtain the terrain suitability of the candidate area; using a preset surrounding feature analysis model, the surrounding environment data of the candidate area is analyzed to obtain the economic suitability of the candidate area;

[0033] The area to be developed is screened out from various candidate areas based on the solar energy utilization rate, the terrain suitability and the economic suitability.

[0034] Optionally, the data acquisition module is configured to:

[0035] For each of the areas to be developed:

[0036] According to the spatial coordinates of the area to be developed, a digital map of the area to be developed is obtained using the preset GIS spatial analysis algorithm;

[0037] Using the preset GIS spatial analysis algorithm, the digital map of the area to be developed and the development data are subjected to a multi-layer overlay analysis operation according to the land parcel correspondence relationship to obtain the spatial image data of the area to be developed, wherein the spatial image data is image data composed of multiple land parcels, and the land parcel correspondence relationship is the relationship between each land parcel and the development data that has a spatial correspondence relationship with the land parcel.

[0038] Optionally, the score acquisition module is configured to:

[0039] For each of the areas to be developed: performing data preprocessing on each plot in the spatial image data of the area to be developed;

[0040] For each land parcel that has undergone data preprocessing: calculating the proportion of the data value of each data type in the development data corresponding to the land parcel to the sum of the data values ​​of each data type in the development data corresponding to the land parcel, wherein the proportion has a one-to-one correspondence with the data type;

[0041] Calculating the information entropy of data of each data type according to the proportion;

[0042] Calculate, based on the information entropy, a weight value of the information entropy value of each data type in the development data corresponding to the land parcel, as a percentage of the sum of the information entropy values ​​of each data type in the development data corresponding to the land parcel, wherein the weight value has a one-to-one correspondence with the data type;

[0043] Multiply the data value of each data type by the weight value of the data type to obtain the first score of the data type;

[0044] Summing up the first scores of each data type in the development data corresponding to the land parcel to obtain a second score of the land parcel;

[0045] The second scores of the blocks in the area to be developed are summed to obtain the solar energy resource development potential score of the area to be developed.

[0046] Optionally, the system further includes:

[0047] The data mapping module is used to:

[0048] Mapping the solar resource development potential score of the area to be developed to a preset solar resource development potential table through data mapping, and determining the development time series type of the area to be developed according to the block to which the solar resource development potential score belongs in the preset solar resource development potential table;

[0049] The color code corresponding to the development time sequence type is added to the spatial image data of the area to be developed.

[0050] A solar energy resource development potential assessment device, comprising:

[0051] processor;

[0052] a memory for storing instructions executable by the processor;

[0053] The processor is configured to execute the instructions to implement any of the above-mentioned methods for assessing solar energy resource development potential.

[0054] A computer-readable storage medium, when instructions in the computer-readable storage medium are executed by a processor of a solar energy resource development potential assessment device, enables the solar energy resource development potential assessment device to perform any of the above-mentioned solar energy resource development potential assessment methods.

[0055] Embodiments of the present invention provide a solar resource development potential assessment method, system, device, and storage medium. By incorporating a pre-set GIS spatial analysis algorithm, the method combines acquired development data with spatial images of the undeveloped area through multi-layer overlay analysis to establish a correspondence between the scope of the undeveloped area and the development data for that area. Compared to the prior art, the present invention uses an expert's subjective knowledge to assign relevant data values, thereby establishing a correspondence between development data and undeveloped areas, thereby ensuring the accuracy of calculating the solar resource development potential score for each undeveloped area. Furthermore, by introducing an entropy weighting method, the present invention transforms the prior art's manual subjective data assessment into an objective method based on mathematical calculations. This improves data utilization while enhancing the objectivity and accuracy of the final analysis results. Finally, the present invention analyzes and screens undeveloped areas from multiple perspectives: solar resource data, permitted area data, and surrounding environmental data. Compared to the prior art's overall development area division method, the present invention improves the accuracy of the data used to calculate the solar resource development potential score while maintaining computational efficiency. Thus, the present invention achieves the inventive goal of improving the accuracy of solar resource development potential assessments.

[0056] Of course, it is not necessary to achieve all of the advantages described above simultaneously in order to implement any product or method of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0058] Figure 1 A flow chart of a method for evaluating solar energy resource development potential provided by an embodiment of the present invention;

[0059] Figure 2 A schematic diagram of a preset comprehensive analysis model provided for an optional embodiment of the present invention;

[0060] Figure 3 A flowchart for screening areas to be developed is provided in a specific embodiment of the present invention;

[0061] Figure 4 A block diagram of a solar energy resource development potential assessment system provided by an embodiment of the present invention;

[0062] Figure 5A block diagram of a solar energy resource development potential assessment device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0063] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0064] The embodiment of the present invention provides a method for evaluating the development potential of solar energy resources. Figure 1 As shown, the solar energy resource development potential assessment method includes:

[0065] S101. Calculate the solar energy resource data, permitted area data, and surrounding environment data of each candidate area using a preset comprehensive analysis model to obtain development data of each candidate area, and select areas to be developed from each candidate area based on the development data.

[0066] Optionally, in an optional embodiment of the present invention, the solar energy resource data may include: horizontal plane irradiation, annual sunshine hours, and annual effective sunshine days, etc. The permitted area data may include: terrain data and prohibited construction area data, etc. The surrounding environment data may include: data on existing power stations, power grid data, and traffic data, etc. The present invention analyzes and screens the areas to be developed from multiple perspectives, including solar energy resource data, permitted area data, and surrounding environment data. Compared to the prior art method of dividing the overall development area, the present invention improves the accuracy of the data used to calculate the solar energy resource development potential score while ensuring calculation efficiency.

[0067] S102. Based on the spatial coordinates of the areas to be developed, a preset GIS spatial analysis algorithm is used to perform a multi-layer overlay analysis operation on the development data of the areas to be developed to obtain spatial image data of each area to be developed, wherein there is a one-to-one correspondence between the spatial image data and the areas to be developed.

[0068] Optionally, in an optional embodiment of the present invention, the above-mentioned preset GIS spatial analysis algorithm can be an analysis method based on a geographic information system (GIS). The preset GIS spatial analysis algorithm can generate an image containing complex data such as geographic spatial information and implicit information based on the spatial location data and indicator data of the geographic object. This is to assist in relevant decision-making. The present invention introduces a preset GIS spatial analysis algorithm to establish a correspondence between the scope of the to-be-developed area and the development data of the to-be-developed area by combining the acquired development data with the spatial image of the to-be-developed area through multi-layer overlay analysis. Compared with the existing technology, the present invention can establish a correspondence between development data and the to-be-developed area by assigning relevant data based on the subjective cognition of experts, thereby ensuring the accuracy of calculating the solar energy resource development potential score of each to-be-developed area.

[0069] Optionally, in another optional embodiment of the present invention, the above-mentioned spatial coordinates may be the longitude and latitude coordinates of the area to be developed.

[0070] Optionally, in another optional embodiment of the present invention, the above-mentioned spatial image data may be a digital map of the area to be developed carrying development data.

[0071] S103. Based on the spatial image data, a preset entropy weight algorithm is used to calculate the solar energy resource development potential score of each area to be developed.

[0072] Optionally, in an optional embodiment of the present invention, the aforementioned preset entropy weighting algorithm (The Entropy Method) is used to determine the degree of dispersion of a certain indicator in an event. The greater the degree of dispersion of the indicator, the greater the impact of the indicator on the event. This degree of dispersion can be reflected by the entropy value. By introducing the entropy weighting method, the present invention transforms the prior art method of subjective manual judgment of data into an objective method based on mathematical calculations of the data. This improves data utilization while enhancing the objectivity and accuracy of the final analysis results.

[0073] This invention introduces a pre-set GIS spatial analysis algorithm to combine acquired development data with spatial images of the undeveloped area through a multi-layer overlay analysis method, establishing a correspondence between the scope of the undeveloped area and the development data for that area. Compared to the prior art, this invention uses an expert's subjective knowledge to assign relevant data values, thereby establishing a correspondence between development data and undeveloped areas, thereby ensuring the accuracy of calculating the solar resource development potential score for each undeveloped area. Furthermore, by introducing the entropy weight method, this invention transforms the prior art's manual and subjective data assessment method into an objective method based on mathematical calculations based on the data. This improves data utilization while enhancing the objectivity and accuracy of the final analysis results. Finally, this invention analyzes and screens undeveloped areas from multiple perspectives: solar resource data, permitted area data, and surrounding environmental data. Compared to the prior art's method of dividing development areas into entire areas, this invention improves the accuracy of the data used to calculate the solar resource development potential score while maintaining computational efficiency. Thus, this invention achieves the inventive goal of improving the accuracy of solar resource development potential assessments.

[0074] Optionally, the development data includes solar energy utilization rate, terrain suitability, and economic suitability. The preset comprehensive analysis model includes a preset solar energy resource assessment model, a preset terrain analysis model, and a preset surrounding feature analysis model. The preset comprehensive analysis model is used to calculate the solar energy resource data, permitted area data, and surrounding environment data of each candidate area to obtain development data for each candidate area. Based on the development data, areas to be developed are screened from each candidate area, including:

[0075] The solar resource data of the candidate area is evaluated using a preset solar resource assessment model to obtain the solar energy utilization rate of the candidate area. The permitted area data of the candidate area is analyzed using a preset terrain analysis model to obtain the terrain suitability of the candidate area. The surrounding environment data of the candidate area is analyzed using a preset surrounding feature analysis model to obtain the economic suitability of the candidate area.

[0076] Alternatively, in an optional embodiment of the present invention, the data type of the solar energy utilization rate may be a solar energy exploitation coefficient. The data type of the terrain suitability may include: aspect, slope, and land exploitation rate. The data type of the economic suitability may include: distance to the transportation network, distance to existing power stations, photovoltaic power station electricity cost, and annual carbon emissions of the power station.

[0077] Optionally, in another optional embodiment of the present invention, the above-mentioned preset comprehensive analysis model is as follows: Figure 2As shown, it can include a solar resource assessment model, a terrain analysis model, a power plant annual carbon emission reduction model, a road network distance estimation model, and a kilowatt-hour cost estimation model. The specific model type can be determined according to the actual application scenario and is not limited in this invention.

[0078] Based on solar energy utilization, terrain suitability and economic suitability, areas to be developed are selected from various alternative areas.

[0079] In order to illustrate the process of screening out the areas to be developed, Figure 3 A specific embodiment of the present invention is shown for explanation:

[0080] Step S301 , using a preset comprehensive analysis model, calculates the solar energy utilization rate, terrain suitability and economic suitability of the candidate area, and triggers step S302 .

[0081] Step S302: Determine whether the solar energy utilization rate of the candidate area is greater than a first preset threshold. If yes, step S303 is triggered; if no, step S306 is triggered.

[0082] Step S303: Determine whether the terrain suitability of the candidate area is greater than a second preset threshold. If yes, step S304 is triggered; if no, step S306 is triggered.

[0083] Step S304: Determine whether the economic suitability of the candidate area is greater than a third preset threshold. If yes, step S305 is triggered; if no, step S306 is triggered.

[0084] Step S305: determine the candidate area as the area to be developed, and end the process.

[0085] Step S306: Delete the candidate area.

[0086] It should be noted that if Figure 3 The execution order of step S302, step S303 and step S304 shown is only for the convenience of description, and the present invention does not impose excessive restrictions on the specific execution order.

[0087] Optionally, based on the spatial coordinates of the area to be developed, a preset GIS spatial analysis algorithm is used to perform a multi-layer overlay analysis operation on the development data of the area to be developed to obtain spatial image data of each area to be developed, including:

[0088] For each area to be developed:

[0089] According to the spatial coordinates of the area to be developed, a digital map of the area to be developed is obtained using a preset GIS spatial analysis algorithm.

[0090] Using a preset GIS spatial analysis algorithm, the digital map and development data of the area to be developed are subjected to a multi-layer overlay analysis operation according to the corresponding relationship between the plots to obtain the spatial image data of the area to be developed, wherein the spatial image data is image data composed of multiple plots, and the corresponding relationship between the plots is the relationship between each plot and the development data that has a spatial corresponding relationship with the plot.

[0091] Optionally, in an optional embodiment of the present invention, the land parcel refers to the basic unit for assigning values ​​to planned land, and can be determined by the smallest grid data grid point in the digital map.

[0092] Optionally, based on the spatial image data, a preset entropy weight algorithm is used to calculate the solar energy resource development potential score of each undeveloped area, including:

[0093] For each area to be developed: perform data preprocessing on each plot in the spatial image data of the area to be developed.

[0094] For each plot that has undergone data preprocessing: calculate the proportion of the data value of each data type in the development data corresponding to the plot to the sum of the data values ​​of each data type in the development data corresponding to the plot, and there is a one-to-one correspondence between the proportion and the data type.

[0095] Calculate the information entropy of data of each data type based on the proportion.

[0096] According to the information entropy, the information entropy value of each data type in the development data corresponding to the plot is calculated, and its weight value is the sum of the information entropy values ​​of each data type in the development data corresponding to the plot, wherein the weight value has a one-to-one correspondence with the data type.

[0097] The data value of each data type is multiplied by the weight value of the data type to obtain the first score of the data type.

[0098] The first scores of various data types in the development data corresponding to the land parcel are summed to obtain the second score of the land parcel.

[0099] The second scores of the blocks in the area to be developed are summed to obtain the solar energy resource development potential score of the area to be developed.

[0100] Optionally, in an optional embodiment of the present invention, the types of data preprocessing operations include, but are not limited to, forward data normalization, reverse data normalization, and index shifting. Forward data normalization refers to the operation of removing dimensions from data that promotes the development potential of solar energy resources in the region. Reverse data normalization refers to the operation of removing dimensions from data that retards the development potential of solar energy resources in the region. The purpose of index shifting is to avoid the risk of calculation logic errors caused by taking the value of 0 when the development data of the plot is logarithmic.

[0101] Optional, as above Figure 1 The solar resource development potential assessment method shown also includes:

[0102] For each area to be developed:

[0103] The solar energy resource development potential score of the area to be developed is mapped to a preset solar energy resource development potential table through data mapping, and the development time series type of the area to be developed is determined according to the block to which the solar energy resource development potential score belongs in the preset solar energy resource development potential table.

[0104] The color code corresponding to the development time series type is added to the spatial image data of the area to be developed.

[0105] Optionally, in an optional embodiment of the present invention, when the spatial image data of the area to be developed is loaded, the area to be developed on the digital map will be filled with color according to the above color coding to facilitate display and distinction.

[0106] Corresponding to the above method embodiment, the embodiment of the present invention also provides a solar energy resource development potential assessment system, such as Figure 4 As shown, the solar energy resource development potential assessment system includes:

[0107] The region screening module 401 calculates the solar energy resource data, permitted area data and surrounding environment data of each candidate region using a preset comprehensive analysis model to obtain development data of each candidate region, and screens out the areas to be developed from each candidate region based on the development data.

[0108] The data acquisition module 402 performs a multi-layer overlay analysis on the development data of the to-be-developed areas based on the spatial coordinates of the to-be-developed areas using a preset GIS spatial analysis algorithm to obtain spatial image data of each to-be-developed area, wherein the spatial image data has a one-to-one correspondence with the to-be-developed areas.

[0109] The score acquisition module 403 calculates the solar energy resource development potential score of each area to be developed based on the spatial image data using a preset entropy weight algorithm.

[0110] Optionally, the development data includes solar energy utilization rate, terrain suitability, and economic suitability; the preset comprehensive analysis model includes a preset solar energy resource assessment model, a preset terrain analysis model, and a preset surrounding feature analysis model; and the region screening module 401 is configured as follows:

[0111] The solar resource data of the candidate area is evaluated using a preset solar resource assessment model to obtain the solar energy utilization rate of the candidate area. The permitted area data of the candidate area is analyzed using a preset terrain analysis model to obtain the terrain suitability of the candidate area. The surrounding environment data of the candidate area is analyzed using a preset surrounding feature analysis model to obtain the economic suitability of the candidate area.

[0112] Based on solar energy utilization, terrain suitability and economic suitability, areas to be developed are selected from various alternative areas.

[0113] Optionally, the data acquisition module 402 is configured to:

[0114] For each area to be developed:

[0115] According to the spatial coordinates of the area to be developed, a digital map of the area to be developed is obtained using a preset GIS spatial analysis algorithm.

[0116] Using a preset GIS spatial analysis algorithm, the digital map and development data of the area to be developed are subjected to a multi-layer overlay analysis operation according to the corresponding relationship between the plots to obtain the spatial image data of the area to be developed, wherein the spatial image data is image data composed of multiple plots, and the corresponding relationship between the plots is the relationship between each plot and the development data that has a spatial corresponding relationship with the plot.

[0117] Optionally, the score acquisition module 403 is configured to:

[0118] For each area to be developed: perform data preprocessing on each plot in the spatial image data of the area to be developed.

[0119] For each plot that has undergone data preprocessing: calculate the proportion of the data value of each data type in the development data corresponding to the plot to the sum of the data values ​​of each data type in the development data corresponding to the plot, and there is a one-to-one correspondence between the proportion and the data type.

[0120] Calculate the information entropy of data of each data type based on the proportion.

[0121] According to the information entropy, the information entropy value of each data type in the development data corresponding to the plot is calculated, and its weight value is the sum of the information entropy values ​​of each data type in the development data corresponding to the plot, wherein the weight value has a one-to-one correspondence with the data type.

[0122] The data value of each data type is multiplied by the weight value of the data type to obtain the first score of the data type.

[0123] The first scores of various data types in the development data corresponding to the land parcel are summed to obtain the second score of the land parcel.

[0124] The second scores of the blocks in the area to be developed are summed to obtain the solar energy resource development potential score of the area to be developed.

[0125] Optional, as above Figure 4 The solar energy resource development potential assessment system shown also includes:

[0126] The data mapping module is used to:

[0127] The solar energy resource development potential score of the area to be developed is mapped to a preset solar energy resource development potential table through data mapping, and the development time series type of the area to be developed is determined according to the block to which the solar energy resource development potential score belongs in the preset solar energy resource development potential table.

[0128] The color code corresponding to the development time series type is added to the spatial image data of the area to be developed.

[0129] The embodiment of the present invention provides a solar energy resource development potential assessment device, such as Figure 5 As shown, the equipment includes:

[0130] Processor 501;

[0131] The memory 502 is used to store instructions executable by the processor 501 .

[0132] The processor 501 is configured to execute instructions to implement any of the above-mentioned solar energy resource development potential assessment methods.

[0133] An embodiment of the present invention provides a computer-readable storage medium. When instructions in the computer-readable storage medium are executed by a processor of a solar energy resource development potential assessment device, the solar energy resource development potential assessment device can perform any of the above-mentioned solar energy resource development potential assessment methods.

[0134] Memory may include non-permanent memory in a computer-readable medium, random access memory (RAM), and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory includes at least one memory chip. Memory is an example of a computer-readable medium.

[0135] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can be implemented using any method or technology to store information. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change RAM (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media such as modulated data signals and carrier waves.

[0136] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0137] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. It should also be noted that the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, commodity, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, commodity, or device comprising the element.

[0138] Each embodiment in this specification is described in a related manner. Similar parts between the various embodiments can be referred to in conjunction with each other. Each embodiment focuses on the differences between the other embodiments. In particular, the system embodiment is generally similar to the method embodiment, so the description is relatively simple. For related parts, refer to the description of the method embodiment.

[0139] The above are merely embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. A method for evaluating the development potential of solar energy resources, characterized in that: The method comprises: Using a preset solar resource assessment model, the solar resource data of the candidate area is evaluated to obtain the solar energy utilization rate of the candidate area; using a preset terrain analysis model, the permitted area data of the candidate area is analyzed to obtain the terrain suitability of the candidate area; using a preset surrounding feature analysis model, the surrounding environment data of the candidate area is analyzed to obtain the economic suitability of the candidate area; based on the development data including the solar energy utilization rate, the terrain suitability and the economic suitability, the area to be developed is screened out from each candidate area; Based on the spatial coordinates of the areas to be developed, a preset GIS spatial analysis algorithm is used to perform a multi-layer overlay analysis operation on the development data of the areas to be developed to obtain spatial image data of each area to be developed, wherein the spatial image data has a one-to-one correspondence with the areas to be developed; For each of the areas to be developed: data preprocessing is performed on each plot in the spatial image data of the area to be developed; for each plot that has undergone the data preprocessing: the proportion of the data value of each data type in the development data corresponding to the plot to the sum of the data values ​​of each data type in the development data corresponding to the plot is calculated, wherein the proportion has a one-to-one correspondence with the data type; based on the proportion, the information entropy of the data of each data type is calculated; based on the information entropy, a weight value of the information entropy value of each data type in the development data corresponding to the plot to the sum of the information entropy values ​​of each data type in the development data corresponding to the plot is calculated, wherein the weight value has a one-to-one correspondence with the data type; the data value of each data type is multiplied by the weight value of the data type to obtain a first score of the data type; the first scores of each data type in the development data corresponding to the plot are summed to obtain a second score of the plot; the second scores of each plot in the area to be developed are summed to obtain a solar energy resource development potential score of the area to be developed.

2. The method according to claim 1, characterized in that The method of performing a multi-layer overlay analysis on the development data of the to-be-developed area based on the spatial coordinates of the to-be-developed area by using a preset GIS spatial analysis algorithm to obtain spatial image data of each to-be-developed area includes: For each of the areas to be developed: According to the spatial coordinates of the area to be developed, a digital map of the area to be developed is obtained using the preset GIS spatial analysis algorithm; Using the preset GIS spatial analysis algorithm, the digital map of the area to be developed and the development data are subjected to a multi-layer overlay analysis operation according to the land parcel correspondence relationship to obtain the spatial image data of the area to be developed, wherein the spatial image data is image data composed of multiple land parcels, and the land parcel correspondence relationship is the relationship between each land parcel and the development data that has a spatial correspondence relationship with the land parcel.

3. The method according to claim 1, characterized in that The method further comprises: For each area to be developed: Mapping the solar resource development potential score of the area to be developed to a preset solar resource development potential table through data mapping, and determining the development time series type of the area to be developed according to the block to which the solar resource development potential score belongs in the preset solar resource development potential table; The color code corresponding to the development time sequence type is added to the spatial image data of the area to be developed.

4. A solar energy resource development potential assessment system, characterized in that: The system comprises: The regional screening module uses a preset solar resource assessment model to evaluate solar resource data of a candidate region to obtain the solar energy utilization rate of the candidate region; uses a preset terrain analysis model to analyze the permitted area data of the candidate region to obtain the terrain suitability of the candidate region; uses a preset surrounding feature analysis model to analyze the surrounding environment data of the candidate region to obtain the economic suitability of the candidate region; and based on the development data including the solar energy utilization rate, the terrain suitability, and the economic suitability, screens out the area to be developed from each candidate region; A data acquisition module, based on the spatial coordinates of the to-be-developed area and using a preset GIS spatial analysis algorithm, performs a multi-layer overlay analysis operation on the development data of the to-be-developed area to obtain spatial image data of each to-be-developed area, wherein the spatial image data has a one-to-one correspondence with the to-be-developed area; The scoring acquisition module performs data preprocessing on each plot in the spatial image data of the area to be developed; for each plot that has undergone the data preprocessing, calculates the proportion of the data value of each data type in the development data corresponding to the plot to the sum of the data values ​​of each data type in the development data corresponding to the plot, wherein the proportion has a one-to-one correspondence with the data type; calculates the information entropy of the data of each data type based on the proportion; calculates the weight value of the information entropy of each data type in the development data corresponding to the plot based on the information entropy as a percentage of the sum of the information entropy values ​​of each data type in the development data corresponding to the plot, wherein the weight value has a one-to-one correspondence with the data type; multiplies the data value of each data type by the weight value of the data type to obtain a first score for the data type; sums the first scores of each data type in the development data corresponding to the plot to obtain a second score for the plot; and sums the second scores of each plot in the area to be developed to obtain a solar energy resource development potential score for the area to be developed.

5. The system according to claim 4, characterized in that The data acquisition module is configured to: For each of the areas to be developed: According to the spatial coordinates of the area to be developed, a digital map of the area to be developed is obtained using the preset GIS spatial analysis algorithm; Using the preset GIS spatial analysis algorithm, the digital map of the area to be developed and the development data are subjected to a multi-layer overlay analysis operation according to the land parcel correspondence relationship to obtain the spatial image data of the area to be developed, wherein the spatial image data is image data composed of multiple land parcels, and the land parcel correspondence relationship is the relationship between each land parcel and the development data that has a spatial correspondence relationship with the land parcel.

6. The system according to claim 4, characterized in that The system further comprises: The data mapping module is used to: Mapping the solar resource development potential score of the area to be developed to a preset solar resource development potential table through data mapping, and determining the development time series type of the area to be developed according to the block to which the solar resource development potential score belongs in the preset solar resource development potential table; The color code corresponding to the development time sequence type is added to the spatial image data of the area to be developed.

7. A solar energy resource development potential assessment device, characterized in that: The device comprises: processor; a memory for storing instructions executable by the processor; The processor is configured to execute the instructions to implement the solar energy resource development potential assessment method according to any one of claims 1 to 3.

8. A computer-readable storage medium, characterized in that When the instructions in the computer-readable storage medium are executed by a processor of a solar energy resource development potential assessment device, the solar energy resource development potential assessment device is enabled to perform the solar energy resource development potential assessment method according to any one of claims 1 to 3.

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