Light resource evaluation method and system based on GIS spatial analysis technology

Abstract

The invention discloses an optical resource evaluation method and system based on a GIS spatial analysis technology, and relates to the technical field of optical resource evaluation and optimized site selection, and the method comprises the steps: collecting data, and carrying out the data fusion; constructing a light resource evaluation system through basic radiation calculation, terrain correction and dynamic meteorological correction; and carrying out analysis and site selection on the light resource partitions. According to the light resource evaluation method based on the GIS spatial analysis technology, a light resource evaluation system is constructed through basic radiation calculation, terrain correction and dynamic meteorological correction, change characteristics of solar radiation in one day and different seasons are captured, and the defects of a traditional static evaluation method are overcome. Terrain and dynamic meteorological correction is introduced, evaluation errors caused by complex terrain shielding and cloud cover coverage are overcome, and the space resolution and the time resolution of radiation data are remarkably improved. The method has better effects in the aspects of precision, dynamic adaptability and site selection rationality.

Description

Technical Field

[0001] The present invention relates to the technical field of optical resource evaluation and optimal site selection, and in particular to an optical resource evaluation method and system based on GIS spatial analysis technology. Background Art

[0002] In recent years, with the deepening of global energy transformation, solar energy, as a renewable and clean energy, has received widespread attention. The evaluation methods of solar energy resources have also developed rapidly. With the support of geographic information system (GIS) technology, researchers have constructed multiple light resource evaluation models using remote sensing images, elevation models (DEM) and meteorological data. These methods provide important technical means for the quantitative analysis of solar energy resources by comprehensively considering the dynamics and regional characteristics of spatial data. At the same time, the introduction of terrain correction and dynamic meteorological factors makes the evaluation results closer to actual conditions. However, the application of light resource evaluation technology is currently more concentrated in flat areas, and its accuracy and adaptability are still insufficient for light resource evaluation under complex terrain and dynamic meteorological conditions. In addition, light resource zoning and site optimization rely more on experience judgment in traditional technologies, and lack systematic quantitative analysis.

[0003] Although existing optical resource assessment technologies have achieved certain results in basic radiation calculation and GIS spatial analysis, they still face the following major problems:

[0004] First, most basic radiation models are based on static conditions, ignoring the complexity of the dynamic changes of solar radiation over time and meteorological conditions. This method easily leads to insufficient accuracy in the temporal and spatial distribution of light resources, especially in areas with high humidity and high cloudiness, where the evaluation results deviate greatly from the actual situation. Secondly, the accuracy of the terrain correction model is limited under complex terrain conditions, and the currently commonly used slope and aspect correction methods cannot effectively deal with the shielding and reflection effects of mountainous and canyon terrains on solar radiation. Thirdly, existing evaluation technologies rarely make corrections based on dynamic meteorological factors (such as temperature, humidity, and cloudiness), making it difficult to accurately reflect the actual availability of light resources. In addition, in terms of light resource zoning and site optimization, traditional methods rely more on a single light resource indicator, and fail to systematically consider the multi-factor constraints of terrain, land use, and economic conditions, resulting in insufficient scientificity and practicality of site selection plans. Summary of the invention

[0005] In view of the above-mentioned problems, the present invention is proposed.

[0006] Therefore, the technical problems solved by the present invention are: the existing light resource assessment methods have insufficient consideration of dynamic meteorological conditions, the terrain correction model has limited accuracy, the light resource zoning and site optimization lack systematization and scientificity, and how to achieve high-precision light resource assessment and site optimization under complex terrain and dynamic meteorological conditions.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions: a method for evaluating light resources based on GIS spatial analysis technology, including collecting data and performing data fusion; constructing a light resource evaluation system through basic radiation calculation, terrain correction and dynamic meteorological correction; analyzing and selecting locations for light resource partitions;

[0008] As a preferred solution of the optical resource evaluation method based on GIS spatial analysis technology described in the present invention, wherein: the data collection and data fusion includes obtaining a data source;

[0009] Data sources include geographic data, meteorological data, and land use data;

[0010] Unify multi-source data formats and coordinates into the same geographic coordinates;

[0011] Perform radiation and geometric correction on remote sensing images, clean missing meteorological data, and use time series regression analysis to supplement missing values;

[0012] Eliminate noise in remote sensing images by moving window method or median filtering method;

[0013] Perform space completion on the data.

[0014] As a preferred solution of the light resource evaluation method based on GIS spatial analysis technology described in the present invention, wherein: the light resource evaluation system constructed by basic radiation calculation, terrain correction and dynamic meteorological correction includes describing the time distribution of solar radiation in a day based on the solar zenith angle and solar azimuth angle, decomposing solar radiation into direct radiation, scattered radiation and surface reflected radiation, dynamically outputting the total amount of solar radiation in the area, capturing the change of radiation over time in a day, and constructing a solar radiation dynamic calculation model represented as:

[0015]

[0016] f cloud =1-exp(-γ·C)

[0017] Among them, G t Represents the total solar radiation per unit time, t d represents the duration of sunshine, from sunrise to sunset, I0 represents the solar constant, T atm represents the atmospheric transmittance, k m represents the atmospheric scattering and absorption coefficient, m a Indicates the atmospheric mass, which is the ratio of the path length of light passing through the atmosphere to the vertical path length, cos(θ z ) represents the cosine value of the solar radiation angle, θ z represents the solar zenith angle, fcloud represents the cloud cover factor, C represents the cloud cover ratio, γ represents the cloud cover absorption coefficient, θ s represents the solar azimuth, β represents the scattering coefficient, k a represents the aerosol absorption coefficient;

[0018] Dynamically output the total amount of solar radiation, capturing changes in radiation over time during a day;

[0019] Provides radiation data, including components of direct radiation and diffuse radiation.

[0020] As a preferred solution of the light resource evaluation method based on GIS spatial analysis technology described in the present invention, wherein: the light resource evaluation system constructed by basic radiation calculation, terrain correction and dynamic meteorological correction includes terrain slope and slope direction determining the terrain's ability to receive solar radiation, when the slope faces the sun, the direct radiation received, when facing away from the sun, the radiation is blocked;

[0021] The steepness and reflectivity of the terrain affect the intensity of terrain reflected radiation. The angle between the solar azimuth and the terrain aspect angle determines the directionality of the terrain receiving radiation. The terrain correction model is expressed as:

[0022]

[0023] Among them, f terrain represents the terrain correction factor, θ z represents the solar zenith angle, cos(θ z ) represents the vertical component of sunlight, S represents the terrain slope, cos(S) represents the reception ratio of flat terrain, sin(θ z )·sin(S) represents the gain or shielding of the direct solar radiation by the terrain slope, cos(θ s -A) represents the effect of slope orientation on radiation, λ represents the terrain reflectivity parameter, and λ·tan(S) represents the effect of terrain steepness on reflected radiation;

[0024] The terrain correction factor ranges from 0 to 1;

[0025] The effective area is the terrain correction coefficient for each raster or vector unit, and the resolution is consistent with the DEM data.

[0026] As a preferred solution of the optical resource evaluation method based on GIS spatial analysis technology described in the present invention, the optical resource evaluation system constructed by basic radiation calculation, terrain correction and dynamic meteorological correction includes considering the weakening effect of temperature and humidity on solar radiation, the degree of weakening of radiation affected by cloud cover, introducing a nonlinear exponential function to simulate the weakening effect of clouds, and further superimposing a terrain correction factor on the basis of dynamic meteorological correction, outputting the final radiation result, and constructing an optical resource comprehensive correction model expressed as:

[0027]

[0028] Among them, G′ t Represents the total solar radiation after comprehensive correction, T max 、T min Indicates the daily maximum and minimum temperatures, T avg represents the daily average temperature, δ1 represents the temperature correction coefficient, T daily represents daily temperature change, H represents air humidity, k c represents the humidity absorption coefficient, C represents the cloud coverage ratio, δ2 represents the humidity correction coefficient, and f terrain represents the terrain correction factor;

[0029] The output is the comprehensively corrected solar radiation, the spatial resolution of which is consistent with the meteorological and topographic data, and the temporal resolution is at the minute or hour level.

[0030] As a preferred solution of the optical resource evaluation method based on GIS spatial analysis technology described in the present invention, the analysis and site selection of optical resource partitions include utilizing the radiation data output by the optical resource comprehensive correction model, combining with the GIS spatial analysis function, and spatially partitioning the optical resources in the study area into high optical resource areas, medium optical resource areas, and low optical resource areas;

[0031] Use overlay analysis techniques to combine land use data with light resource data;

[0032] Dynamically analyze the time series changes of light resource distribution and generate seasonal light resource distribution maps;

[0033] Identify the peak and trough periods of light resources and provide decision-making basis for light energy utilization in different time periods;

[0034] Construct light resource distribution maps, high and low resource zoning maps, and annual total radiation heat maps.

[0035] As a preferred solution of the optical resource evaluation method based on GIS spatial analysis technology described in the present invention, wherein: the analysis and site selection of optical resource partitions includes introducing land use, terrain slope, optical resource distribution and economic constraints to provide comprehensive restriction conditions for site selection;

[0036] Select the optimal area for photovoltaic power station based on light resource zoning and restriction conditions.

[0037] Another object of the present invention is to provide a light resource evaluation system based on GIS spatial analysis technology, which can construct a light resource evaluation system through basic radiation calculation, terrain correction and dynamic meteorological correction, solving the problem that the current light resource evaluation method contains light resource zoning and site optimization, which lacks systematization and scientificity.

[0038] As a preferred solution of the optical resource evaluation system based on GIS spatial analysis technology described in the present invention, it includes: an initialization module, a model building module, and an evaluation and site selection module; the initialization module is used to collect data sources for preprocessing; the model building module is used to construct a solar radiation dynamic calculation model, a terrain correction model and a comprehensive optical resource correction model; the evaluation and site selection module is used for optical resource zoning and dynamic time analysis, and to construct site selection restriction conditions.

[0039] A computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of an optical resource evaluation method based on GIS spatial analysis technology.

[0040] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of an optical resource evaluation method based on GIS spatial analysis technology.

[0041] Beneficial effects of the present invention: The light resource evaluation method based on GIS spatial analysis technology provided by the present invention constructs a light resource evaluation system through basic radiation calculation, terrain correction and dynamic meteorological correction, captures the changing characteristics of solar radiation within a day and in different seasons, and makes up for the shortcomings of traditional static evaluation methods. The introduction of terrain and dynamic meteorological correction overcomes the evaluation errors caused by complex terrain occlusion and cloud cover, and significantly improves the spatial and temporal resolution of radiation data. The system is not only applicable to flat areas, but also to complex terrain areas such as mountains and hills, providing scientific support for the site selection of photovoltaic power stations. Through light resource zoning and site selection analysis, the output results of the light resource comprehensive correction model are used, combined with the GIS spatial analysis function, the light resources in the study area are partitioned, and high-precision light resource distribution maps and regional division maps are generated. In addition, through the overlay analysis technology, land use data, economic constraints, etc. are combined with light resource distribution to select the preferred area of ​​the photovoltaic power station. Through the comprehensive and corrected radiation data, the time series changes of light resources are dynamically analyzed, and seasonal light resource distribution maps are generated, providing a reliable basis for the utilization of light energy in different periods. Taking into account the distribution of light resources, terrain conditions and economic constraints, the shortcomings of relying on experience in the traditional site selection process are overcome, and an optimized preferred area is provided. The generated light resource distribution map and heat map intuitively show the distribution of light resources in the region, providing decision makers with an efficient and convenient reference tool. The present invention achieves better results in terms of accuracy, dynamic adaptability and rationality of site selection. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0043] Figure 1 An overall flow chart of an optical resource evaluation method based on GIS spatial analysis technology provided in the first embodiment of the present invention.

[0044] Figure 2 An overall flow chart of an optical resource evaluation system based on GIS spatial analysis technology provided in the third embodiment of the present invention. DETAILED DESCRIPTION

[0045] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0046] Example 1, reference Figure 1 , as an embodiment of the present invention, provides a light resource evaluation method based on GIS spatial analysis technology, comprising:

[0047] S1: Collect data and perform data fusion.

[0048] Furthermore, data sources are acquired, including basic geographic data, meteorological data and land use data.

[0049] Basic geographic data:

[0050] High-resolution remote sensing images are obtained through remote sensing satellites (such as Landsat and Sentinel-2) to capture the surface feature information of the study area.

[0051] Use digital elevation model (DEM) data (such as SRTM or ASTER) to obtain the slope, aspect and elevation information of the terrain in the area, providing a basis for subsequent terrain correction.

[0052] Weather data:

[0053] Obtain historical and real-time weather data from weather observation stations, global weather data centers such as NOAA or ERA5, including solar radiation intensity, sunshine duration, cloud cover, temperature, humidity and wind speed.

[0054] The focus is on the trend of daily solar radiation changes in long time series (such as 10 years) to ensure that the results have climate statistical significance.

[0055] Land use data:

[0056] Collect regional land use classification data (such as cultivated land, construction land, forest land, wetland, etc.) through the Global Land Cover Database (GLC) or the National Resources Monitoring Data Platform to exclude undevelopable areas.

[0057] It should be noted that the multi-source data formats (raster, vector) and coordinate systems (WGS-84, CGCS2000, etc.) are unified into the same standard geographic coordinate system to ensure spatial consistency between different data. Radiometric and geometric corrections are performed on remote sensing images to eliminate atmospheric interference and spatial deformation.

[0058] Outliers (such as extreme cloud cover and missing meteorological data) are cleaned and missing values ​​are supplemented by time series regression analysis. Noise points in remote sensing images are eliminated by moving window method or median filtering method.

[0059] For areas where meteorological stations are sparsely distributed or insufficiently covered, inverse distance weighted (IDW) or Kriging interpolation methods are used to spatially complete point data. Time series interpolation methods are used to fill in the time gaps in meteorological data so that data continuity meets dynamic computing needs.

[0060] Using GIS spatial overlay methods, remote sensing images, DEM data, meteorological data, and land use data are integrated into a unified GIS analysis framework. A comprehensive data model containing geographic, meteorological, topographic, and land use information is constructed to provide high-quality basic data for subsequent optical resource analysis.

[0061] Evaluate the consistency between multi-source data through statistical analysis (such as the matching degree between DEM data and slope extraction). Compare remote sensing radiation data with the measured radiation values ​​of meteorological stations to verify the reliability of light resource data. Check the spatial coverage of the data to ensure that there is no obvious missing data in the target area.

[0062] Generate high-quality datasets with spatial and temporal continuity, including:

[0063] Remote sensing image raster data.

[0064] Slope, aspect and elevation data extracted from DEM.

[0065] Regional dynamic meteorological raster data (radiation, cloud cover, temperature and humidity).

[0066] Land use vector data.

[0067] S2: Construct a light resource assessment system through basic radiation calculation, terrain correction and dynamic meteorological correction.

[0068] Furthermore, the intensity of solar radiation varies with the position of the sun. Based on the solar zenith angle and solar azimuth angle, the temporal distribution of solar radiation in a day can be accurately described. When solar radiation passes through the atmosphere, it is affected by aerosols, cloud cover and atmospheric composition, resulting in energy attenuation. The model introduces atmospheric transmittance and aerosol absorption coefficient to describe these attenuation effects. Solar radiation is decomposed into direct radiation, scattered radiation and surface reflected radiation, and they are calculated separately to improve accuracy.

[0069] The dynamic calculation model of solar radiation is expressed as:

[0070]

[0071] f cloud=1-exp(-γ·C)

[0072] Among them, G t Represents the total solar radiation per unit time, t d represents the duration of sunshine, from sunrise to sunset, I0 represents the solar constant, T atm represents the atmospheric transmittance, k m represents the atmospheric scattering and absorption coefficient, m a Indicates the atmospheric mass, which is the ratio of the path length of light passing through the atmosphere to the vertical path length, cos(θ z ) represents the cosine value of the solar radiation angle, θ z represents the solar zenith angle, f cloud represents the cloud cover factor, C represents the cloud cover ratio, γ represents the cloud cover absorption coefficient, θ s represents the solar azimuth, β represents the scattering coefficient, k a represents the aerosol absorption coefficient.

[0073] Dynamically calculates the total solar radiation for an area, capturing how radiation changes over time throughout the day.

[0074] Provide basic radiation data for subsequent models, including direct radiation and diffuse radiation components.

[0075] Output data format: total solar radiation per unit time (GtG_tGt), unit is W / m 2 .

[0076] Time resolution: minutes or hours.

[0077] Spatial resolution: consistent with meteorological and topographic data (e.g. 30 m or 100 m).

[0078] It should be noted that the slope and aspect of the terrain determine the terrain's ability to receive solar radiation. When the slope faces the sun, the direct radiation received is enhanced; on the contrary, when it faces away from the sun, the radiation will be blocked. The steepness and reflectivity of the terrain affect the strength of the terrain's reflected radiation and need to be comprehensively considered in the model. The angle between the solar azimuth and the terrain aspect angle determines the directionality of the terrain's received radiation.

[0079] The terrain correction model is constructed as follows:

[0080]

[0081] Among them, f terrain represents the terrain correction factor, θ z represents the solar zenith angle, cos(θ z ) represents the vertical component of sunlight, S represents the terrain slope, cos(S) represents the reception ratio of flat terrain, sin(θz )·sin(S) represents the gain or shielding of the direct solar radiation by the terrain slope, cos(θ s -A) represents the effect of slope orientation on radiation, λ represents the terrain reflectivity parameter, and λ·tan(S) represents the effect of terrain steepness on reflected radiation.

[0082] Corrected base radiation to match actual terrain conditions.

[0083] Provide more accurate regional light resource distribution results, especially for areas with complex terrain.

[0084] Output data format: Terrain correction factor, unitless, range 0 to 1.

[0085] Area of ​​effect: Terrain correction factor per raster or vector cell.

[0086] Resolution: consistent with DEM data (e.g. 30 meters).

[0087] Furthermore, the weakening effect of temperature and humidity on solar radiation cannot be ignored. For example, when the humidity is high, water vapor in the atmosphere absorbs solar radiation, and the radiation amount needs to be dynamically adjusted through the correction coefficient. Cloud cover significantly affects the degree of radiation weakening, and a nonlinear exponential function is introduced to simulate the weakening effect of clouds. On the basis of dynamic meteorological correction, the terrain correction factor is further superimposed to generate the final radiation result.

[0088] The comprehensive correction model of optical resources is constructed as follows:

[0089]

[0090] Among them, G′ t Represents the total solar radiation after comprehensive correction, T max 、T min Indicates the daily maximum and minimum temperatures, T avg represents the daily average temperature, δ1 represents the temperature correction coefficient, T daily represents daily temperature change, H represents air humidity, k c represents the humidity absorption coefficient, C represents the cloud coverage ratio, δ2 represents the humidity correction coefficient, and f terrain Represents the terrain correction factor.

[0091] The solar radiation is comprehensively corrected to generate the final light resource distribution reflecting the dynamic meteorological conditions and terrain influences.

[0092] Realize multi-factor comprehensive optical resource evaluation in the region.

[0093] Output data format: Comprehensive corrected solar radiation, unit: W / m 2 .

[0094] Spatial resolution: consistent with meteorological and topographic data (e.g. 100 meters).

[0095] Temporal resolution: minutes or hours (depending on the resolution of input meteorological data).

[0096] S3: Analyze and select locations for optical resource partitions.

[0097] Furthermore, the radiation data output by the comprehensive correction model of light resources is used in combination with the spatial analysis function of GIS to spatially partition the light resources in the study area.

[0098] Partition by:

[0099] High light resource area: The annual total radiation per unit area is higher than the set threshold.

[0100] Medium light resource area: The annual total radiation per unit area fluctuates within a certain range.

[0101] Low light resource area: The annual total radiation per unit area is lower than the set threshold or the utilization rate is low due to terrain obstruction.

[0102] Using overlay analysis technology, land use data and light resource data are combined to exclude undevelopable areas (such as nature reserves and urban construction areas).

[0103] Dynamically analyze the time series changes of light resource distribution and generate seasonal light resource distribution maps.

[0104] Identify the peak and trough periods of light resources and provide a basis for decision-making on the utilization of light energy in different time periods.

[0105] Generate light resource distribution maps, high and low resource zoning maps, and annual total radiation heat maps to support understanding of regional light resource characteristics in an intuitive form.

[0106] It should be noted that the introduction of land use, terrain slope, light resource distribution and economic constraints provides comprehensive constraints for site selection:

[0107] Land use restrictions: exclude areas where development is prohibited, such as cultivated land, forest land, and wetlands.

[0108] Topographic restrictions: Priority is given to areas with moderate slopes and favorable orientations (south or south-biased).

[0109] Light resource limitation: The total annual radiation of the candidate area must be higher than the set threshold.

[0110] Economic constraints: Evaluation is based on the land development cost and the PV power station construction cost.

[0111] Based on the light resource zoning and restriction conditions, high light resource areas that meet economic and technical conditions are selected as the preferred areas for photovoltaic power stations.

[0112] Provide detailed light resource assessment results for each preferred area, including:

[0113] Average annual radiation and sunshine duration.

[0114] Land use type and area.

[0115] Regional comprehensive rating.

[0116] Example 2, an embodiment of the present invention, provides an optical resource evaluation method based on GIS spatial analysis technology. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0117] First, the experiment selected five areas with different terrain and climatic conditions as research objects, and recorded and processed geographic data, meteorological data and land use data respectively.

[0118] The experimental data sources include remote sensing images, elevation models (DEM) and meteorological observation station data. The remote sensing images have improved spectral and spatial resolution through radiation correction and geometric correction. The missing parts of meteorological data are supplemented by time series regression analysis, and the image noise is denoised by the moving window method. The processed data are integrated into a GIS analysis platform through a unified coordinate system.

[0119] Basic radiation calculations use a dynamic solar radiation model to decompose direct, scattered and reflected radiation components according to the solar zenith angle and azimuth, capturing regional daytime radiation changes.

[0120] Terrain correction is based on the characteristics of regional slope and aspect, assessing the effect of terrain on enhancing or blocking direct radiation, and applying a terrain correction factor to adjust the base radiation.

[0121] Dynamic meteorological correction comprehensively considers the weakening effects of temperature, humidity and cloud cover on radiation, and uses the corrected radiation model to output the total solar radiation for each study area.

[0122] The comprehensive correction results of light resources are applied to GIS analysis. 2 ), Zhongguang Resource Area (4-6kWh / m 2 ) and low light resource areas (<4kWh / m 2 ) is used for zoning, and the optimal location of the photovoltaic power station is recommended based on land use and economic constraints.

[0123] Table 1 Experimental data table

[0124] parameter Region A Region B Region C Region D Area E area A B C D E <![CDATA[Solar radiation (kWh / m 2 )]]> 5.8 4.5 6.2 3.9 6.5 Slope(°) 15 30 10 45 5 Slope aspect (°) 180 270 90 0 135 Cloud cover (%) 20 40 10 50 5 Temperature range (℃) 5 8 4 10 3 humidity(%) 60 70 55 80 50 <![CDATA[Corrected solar radiation amount (kWh / m 2 )]]> 5.2 3.6 6 2.8 6.3

[0125] By analyzing the table data, the following points can be observed:

[0126] In the case of high basic radiation, the corrected radiation of area A and area E is close to the basic radiation due to moderate slope and low cloud cover, which are 5.2 kWh / m 2 and 6.3kWh / m 2 .

[0127] Due to the steep slope (45°) and high cloud cover (50%), the corrected radiation in area D is significantly lower, to 2.8 kWh / m, even though the basic radiation is close to that in area A. 2 This indicates that topography and dynamic meteorology have a significant weakening effect on radiation.

[0128] Area E is identified as a high light resource area with the highest basic radiation (6.5 kWh / m 2 ), after correction, it still remains at 6.3kWh / m 2 , which is suitable as the preferred area for photovoltaic power stations.

[0129] Areas B and D are classified as low light resource areas, and the corrected radiation is 3.6 kWh / m 2 and 2.8kWh / m 2 , proved unsuitable for development.

[0130] Traditional methods cannot comprehensively consider the impact of multiple factors such as aspect, slope and dynamic meteorology, and may overestimate the amount of light resources at Location D. However, the comprehensive correction model of the present invention accurately evaluates the radiation weakening effect by superimposing terrain and dynamic meteorological factors, significantly improving the accuracy and reliability of the evaluation results.

[0131] In addition, the zoning and site selection methods avoid the uncertainty of empirical judgment through GIS spatial analysis and multi-factor superposition, further improving the scientific nature of site selection decisions.

[0132] In summary, this embodiment fully verifies the advantages of the present invention in light resource assessment under complex terrain and dynamic meteorological conditions. Through high-precision radiation correction and spatial partitioning, it solves the problems of insufficient accuracy and poor applicability in the prior art, and provides a reliable basis for the construction of photovoltaic power stations.

[0133] Example 3, reference Figure 2 , which is an embodiment of the present invention, provides an optical resource evaluation system based on GIS spatial analysis technology, including an initialization module, a model building module, and an evaluation and site selection module.

[0134] The initialization module is used to collect data sources for preprocessing; the model building module is used to build a solar radiation dynamic calculation model, a terrain correction model and a comprehensive light resource correction model; the evaluation and site selection module is used for light resource partitioning and dynamic time analysis to build site selection constraints.

[0135] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0136] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0137] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0138] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc. It should be noted that the above embodiments are only used to illustrate the technical solution of the present invention and are not limited. Although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

[0139] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A light resource evaluation method based on GIS spatial analysis technology, characterized in that: include: Collect data and perform data fusion; Construct a light resource evaluation system through basic radiation calculation, terrain correction and dynamic meteorological correction; Analyze and select locations for optical resource partitions.

2. The optical resource evaluation method based on GIS spatial analysis technology as claimed in claim 1, characterized in that: The data collection and data fusion comprises obtaining a data source; Data sources include geographic data, meteorological data, and land use data; Unify multi-source data formats and coordinates into the same geographic coordinates; Perform radiation and geometric correction on remote sensing images, clean missing meteorological data, and use time series regression analysis to supplement missing values; Eliminate noise in remote sensing images by moving window method or median filtering method; Perform space completion on the data.

3. The optical resource evaluation method based on GIS spatial analysis technology as claimed in claim 2, characterized in that: The light resource evaluation system constructed by basic radiation calculation, terrain correction and dynamic meteorological correction includes describing the time distribution of solar radiation in a day based on the solar zenith angle and solar azimuth angle, decomposing solar radiation into direct radiation, scattered radiation and surface reflected radiation, dynamically outputting the total amount of solar radiation in the area, capturing the change of radiation over time in a day, and constructing a solar radiation dynamic calculation model represented as follows: f cloud =1-exp(-γ·C) Among them, G t Represents the total solar radiation per unit time, t d represents the duration of sunshine, from sunrise to sunset, I0 represents the solar constant, T atm represents the atmospheric transmittance, k m represents the atmospheric scattering and absorption coefficient, m a Indicates the atmospheric mass, which is the ratio of the path length of light passing through the atmosphere to the vertical path length, cos(θ z ) represents the cosine value of the solar radiation angle, θ z represents the solar zenith angle, f cloud represents the cloud cover factor, C represents the cloud cover ratio, γ represents the cloud cover absorption coefficient, θ s represents the solar azimuth, β represents the scattering coefficient, k a represents the aerosol absorption coefficient; Dynamically output the total amount of solar radiation, capturing changes in radiation over time during a day; Provides radiation data, including components of direct radiation and diffuse radiation.

4. The optical resource evaluation method based on GIS spatial analysis technology as claimed in claim 3, characterized in that: The light resource evaluation system constructed by basic radiation calculation, terrain correction and dynamic meteorological correction includes that the terrain slope and slope direction determine the terrain's ability to receive solar radiation. When the slope faces the sun, it receives direct radiation, and when it faces away from the sun, the radiation is blocked; The steepness and reflectivity of the terrain affect the intensity of terrain reflected radiation. The angle between the solar azimuth and the terrain aspect angle determines the directionality of the terrain receiving radiation. The terrain correction model is expressed as: Among them, f terrain represents the terrain correction factor, θ z represents the solar zenith angle, cos(θ z ) represents the vertical component of sunlight, S represents the terrain slope, cos(S) represents the reception ratio of flat terrain, sin(θ z )·sin(S) represents the gain or shielding of the direct solar radiation by the terrain slope, cos(θ s -A) represents the effect of slope orientation on radiation, λ represents the terrain reflectivity parameter, and λ·tan(S) represents the effect of terrain steepness on reflected radiation; The terrain correction factor ranges from 0 to 1; The effective area is the terrain correction coefficient for each raster or vector unit, and the resolution is consistent with the DEM data.

5. The optical resource evaluation method based on GIS spatial analysis technology as claimed in claim 4, characterized in that: The light resource evaluation system constructed by basic radiation calculation, terrain correction and dynamic meteorological correction includes considering the weakening effect of temperature and humidity on solar radiation, the degree of radiation weakening affected by cloud cover, introducing a nonlinear exponential function to simulate the weakening effect of clouds, and further superimposing a terrain correction factor on the basis of dynamic meteorological correction to output the final radiation result. The light resource comprehensive correction model is constructed as follows: Among them, G′ t Represents the total solar radiation after comprehensive correction, T max , T min Indicates the daily maximum and minimum temperatures, T avg represents the daily average temperature, δ1 represents the temperature correction coefficient, T daily represents daily temperature change, H represents air humidity, k c represents the humidity absorption coefficient, C represents the cloud coverage ratio, δ2 represents the humidity correction coefficient, and f terrain represents the terrain correction factor; The output is the comprehensively corrected solar radiation, the spatial resolution of which is consistent with the meteorological and topographic data, and the temporal resolution is at the minute or hour level.

6. The optical resource evaluation method based on GIS spatial analysis technology as claimed in claim 5, characterized in that: The analysis and site selection of light resource zoning includes utilizing the radiation data output by the light resource comprehensive correction model, combined with the GIS spatial analysis function, to spatially zon the light resources in the study area, including high light resource areas, medium light resource areas, and low light resource areas; Use overlay analysis techniques to combine land use data with light resource data; Dynamically analyze the time series changes of light resource distribution and generate seasonal light resource distribution maps; Identify the peak and trough periods of light resources and provide decision-making basis for light energy utilization in different time periods; Construct light resource distribution maps, high and low resource zoning maps, and annual total radiation heat maps.

7. The optical resource evaluation method based on GIS spatial analysis technology as claimed in claim 6, characterized in that: The analysis and site selection of optical resource zoning includes introducing land use, terrain slope, optical resource distribution and economic constraints to provide comprehensive constraints for site selection; Select the optimal area for photovoltaic power station based on light resource zoning and restriction conditions.

8. A system using the optical resource evaluation method based on GIS spatial analysis technology as claimed in any one of claims 1 to 7, characterized in that: Includes initialization module, model building module, assessment and site selection module; The initialization module is used to collect data sources for preprocessing; The model building module is used to build a solar radiation dynamic calculation model, a terrain correction model and a light resource comprehensive correction model; The evaluation and site selection module is used for optical resource partitioning and dynamic time analysis to construct site selection constraints.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the optical resource evaluation method based on GIS spatial analysis technology described in any one of claims 1 to 7 are implemented.

10. 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 optical resource evaluation method based on GIS spatial analysis technology described in any one of claims 1 to 7 are implemented.

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