CN115841266A - Photovoltaic power generation potential evaluation method for photovoltaic power station site selection - Google Patents
Photovoltaic power generation potential evaluation method for photovoltaic power station site selection Download PDFInfo
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Abstract
The invention discloses a photovoltaic power generation potential evaluation method for photovoltaic power station site selection, which is based on geographic information and meteorological data with high space-time resolution, finely reflects the distribution difference of photovoltaic resources in an area, and simultaneously matches the photovoltaic space resources with the landform and features, thereby providing an important reference basis for the site selection of a photovoltaic power station. According to the assessment method, the planning construction area of the photovoltaic power station is divided into the plurality of earth surface grid units, the digital elevation data, the earth surface coverage type data, the illumination intensity and the earth surface temperature historical data are unified in spatial resolution, and the digital elevation data, the earth surface coverage type data, the illumination intensity and the earth surface temperature historical data under the resolution of the earth surface grid units are obtained.
Description
The technical field is as follows:
the invention belongs to the field of electrical engineering, and particularly relates to a photovoltaic power generation potential evaluation method for site selection of a photovoltaic power station.
Background art:
as fossil energy is non-renewable energy, along with the vigorous exploitation for nearly a century, the fossil energy is increasingly exhausted; and the use of fossil energy is accompanied by a large amount of greenhouse gas emissions, which is a major cause of global warming. At present, the demand of electric power is continuously increased due to the continuous increase of the economic level. In the face of increasingly severe energy crisis, the key to the bureau is the vigorous development of renewable energy sources such as photovoltaic energy sources.
China has abundant solar energy resources, the annual sunshine hours in regions with the total area of more than 2/3 of the whole country are more than 2200 hours, and the annual radiation quantity reaches 5000MJ/m 2 . According to data statistics, the total amount of solar radiation received by land areas in China per year is equivalent to 24 multiplied by 104 hundred million tons of standard coal, and the prospect of developing photovoltaic power generation is extremely considerable.
The existing photovoltaic power station site selection method usually focuses on meteorological information such as illumination intensity of a planned construction area on the evaluation of photovoltaic power generation potential, namely, the photovoltaic power generation potential of the planned construction area is evaluated according to the illumination intensity of the planned construction area and surface temperature historical data.
The invention content is as follows:
in order to solve the problems in the prior art, the invention provides a photovoltaic power generation potential evaluation method for photovoltaic power station site selection by combining geographic information and meteorological data.
The technical scheme of the invention is as follows:
a photovoltaic power generation potential evaluation method for photovoltaic power station site selection comprises the following steps:
dividing a planning construction area of the photovoltaic power station into a plurality of earth surface grid units, and screening alternative grid units suitable for constructing the photovoltaic power station according to the altitude data and the gradient data of each earth surface grid unit;
determining an effective development coefficient of each alternative grid unit according to the earth surface coverage type data of each alternative grid unit, and calculating the photovoltaic installed capacity of each alternative grid unit according to the area of each alternative grid unit, the effective development coefficient and the installed capacity of the unit area of typical photovoltaic equipment;
calculating the photovoltaic output of typical photovoltaic equipment in each alternative grid unit according to the illumination intensity and the surface temperature historical data of each alternative grid unit, the rated capacity of the typical photovoltaic panel and the temperature correction coefficient, and further calculating the photovoltaic resource capacity factor of each alternative grid unit;
selecting a plurality of alternative grid units with large photovoltaic resource capacity factors as pre-construction units of the photovoltaic power station, wherein the photovoltaic planning construction capacity of the pre-construction units is matched with the photovoltaic installed capacity of the construction units.
Further, the altitude data and the gradient data of each ground grid unit are obtained by the following method:
1) Acquiring digital elevation data of a planned area;
2) Performing resolution conversion on the acquired digital elevation data to obtain digital elevation data under the resolution of the earth surface grid unit;
3) And acquiring altitude data and gradient data of each land form grid unit.
Further, the data of the earth surface coverage type of each candidate grid unit is obtained by the following method:
1) Acquiring earth surface coverage type data of a planning area;
2) Performing resolution conversion on the acquired earth surface coverage type data to obtain earth surface coverage type data under the resolution of earth surface grid units;
3) And screening the ground surface coverage type data of each candidate grid cell.
Further, the historical data of the illumination intensity of each candidate grid cell is obtained by the following method:
1) Acquiring the illumination intensity and surface temperature historical data of a planning area;
2) Performing resolution conversion on the acquired historical data of the illumination intensity and the surface temperature to obtain historical data of the illumination intensity under the resolution of the surface grid unit;
3) And screening out the illumination intensity and the surface temperature historical data of each candidate grid unit.
Further, the resolution conversion method adopts an SVM algorithm.
Furthermore, the length range of the surface grid unit resolution is 0.005-0.05 degrees of latitude, and the width range is 0.005-0.05 degrees of longitude.
Further, the data of the surface coverage types of the alternative grid units comprise water bodies, evergreen coniferous forests, evergreen broad-leaved forests, deciduous coniferous forests, deciduous broad-leaved forests, mixed forests, closed shrubs, sparse shrubs, grasslands with forests, thin grasslands, permanent wetlands, farmlands, cities, towns and built-up areas, farmlands and natural vegetation inlays, ice, snow and wastelands.
Further, the calculation formula of the photovoltaic installed capacity of the alternative grid unit is as follows:
C i ＝AS i ρ i
in the formula, C i The installed photovoltaic capacity of the ith candidate grid unit; a is the installed capacity per unit area of a typical photovoltaic device; ρ is a unit of a gradient i For the active opening of the ith candidate grid cellA coefficient of variation; s i Is the area of the ith candidate grid cell; i is 1,2, \ 8230and the total number of alternative grid cells.
Further, the photovoltaic output of the typical photovoltaic device in each alternative grid cell is the maximum output power of the typical photovoltaic device in each alternative grid cell operating in the maximum power point tracking mode.
Compared with the prior art, the invention has the following beneficial effects
The invention provides a photovoltaic power generation potential evaluation method for photovoltaic power station site selection, which is based on geographic information and meteorological data with high space-time resolution, finely reflects the distribution difference of photovoltaic resources in an area, and simultaneously matches the photovoltaic space resources with the landform and features, thereby providing an important reference basis for the site selection of a photovoltaic power station.
According to the evaluation method, the planned construction area of the photovoltaic power station is divided into a plurality of earth surface grid units, the digital elevation data, the earth surface coverage type data, the illumination intensity and the earth surface temperature historical data are unified in spatial resolution, and the digital elevation data, the earth surface coverage type data, the illumination intensity and the earth surface temperature historical data under the resolution of the earth surface grid units are obtained.
Description of the drawings:
fig. 1 is a flow chart of photovoltaic resource evaluation.
The specific implementation mode is as follows:
the invention is further described with reference to specific embodiments and corresponding figures.
The first embodiment is as follows:
a photovoltaic power generation potential evaluation method for photovoltaic power station site selection comprises the following steps:
firstly, a planning and construction area of a photovoltaic power station is divided into a plurality of earth surface grid units, the length range of the resolution of the earth surface grid units is 0.005-0.05 degrees of latitude, the width range of the earth surface grid units is 0.005-0.05 degrees of longitude, and the resolution length and the resolution width can be selected by integrating the size of the planning and construction area of the photovoltaic power station and the spatial resolution of a data set for analysis.
Acquiring digital elevation data of a planning area from the SRTM30_ PLUS data set provided by the weather all website, and performing resolution conversion on the acquired digital elevation data to obtain digital elevation data under the resolution of the surface grid unit; and (4) screening out altitude data and gradient data from the obtained digital elevation data, and further obtaining the altitude data and the gradient data of each land grid unit. Screening alternative grid units suitable for building a photovoltaic power station according to the altitude data and the gradient data of each surface grid unit; in the embodiment, the construction requirements of the photovoltaic panels in the photovoltaic power station are considered, so that the earth surface grid units with the altitude less than or equal to 3000 meters and the gradient less than or equal to 10 degrees are selected.
Secondly, firstly, acquiring the earth surface coverage type data of a planning area from the MCD12Q1 earth surface coverage type data set; the surface coverage type data of the alternative grid units comprise water, evergreen coniferous forests, evergreen broad-leaved forests, deciduous coniferous forests, deciduous broad-leaved forests, mixed forests, closed shrubs, sparse shrubs, grasslands with forests, thin grasslands, permanent wetlands, farmlands, towns and built-up areas, farmlands and natural vegetation inlays, ice, snow and wastelands.
Then, performing resolution conversion on the acquired earth surface coverage type data to obtain earth surface coverage type data under the resolution of earth surface grid cells;
and then screening the ground surface coverage type data of each alternative grid unit, and determining the effective development coefficient of each alternative grid unit according to the screened ground surface coverage type data of each alternative grid unit. In the embodiment, for the farmland, the farmland and the natural vegetation mosaic, the effective development coefficient is 2%; for the canopy shrubbery, the effective development coefficient is 15%; for grasslands with forest, the effective development coefficient is 45%; for sparse shrubs, the effective development coefficient is 50%; for the sparse tree grassland, the effective development coefficient is 75 percent; for wasteland, the effective development coefficient is 80%; for grasslands, the effective development coefficient is 90%; for water, evergreen coniferous forests, evergreen broad-leaved forests and other ground surface coverage types, the effective development coefficient is 0%.
And calculating the photovoltaic installed capacity of each alternative grid unit according to the area, the effective development coefficient and the installed capacity per unit area of the typical photovoltaic equipment, wherein the calculation formula of the photovoltaic installed capacity of the alternative grid unit is as follows:
C i ＝AS i ρ i
in the formula, C i The installed photovoltaic capacity of the ith candidate grid unit; a is the installed capacity per unit area of a typical photovoltaic device; rho i Effective development coefficients for the ith candidate grid cell; s i Is the area of the ith candidate grid cell; i is 1,2, \ 8230, and the total number of the alternative grid cells.
Thirdly, acquiring historical data of illumination intensity and historical data of surface temperature of the planned area; then, performing resolution conversion on the acquired historical illumination intensity data and the historical earth surface temperature data by using an SVM algorithm to obtain historical illumination intensity data and historical earth surface temperature data under the resolution of earth surface grid units; and then screening out the historical data of the illumination intensity and the historical data of the surface temperature of each candidate grid unit. Calculating the Maximum output Power of the typical photovoltaic equipment in each alternative grid unit running under a Maximum Power Point Tracking (MPPT) mode according to the illumination intensity and surface temperature historical data of each alternative grid unit, the rated capacity of the typical photovoltaic panel and the temperature correction coefficient, and further calculating the photovoltaic resource capacity factor of each alternative grid unit; in the example, a typical photovoltaic device adopts a certain type of photovoltaic cell panel made of a polycrystalline silicon material, the historical data of the illumination intensity and the surface temperature adopt the historical data of the illumination intensity and the historical data of the surface temperature which are acquired by a European middle and long term forecasting center (ECMWF) and have the time resolution of 1 hour, the time span is 2011-2020 years, and the historical data of the illumination intensity is the historical data of the illumination intensity vertical to the horizontal plane.
Then the photovoltaic output calculation formula of a typical photovoltaic device within the alternative grid cell x at time t is as follows:
wherein C represents the rated capacity of the photovoltaic cell panel, and the rated capacity of the photovoltaic cell panel selected in this embodiment is 1MW; gamma represents the temperature correction coefficient of the photovoltaic cell panel, the photovoltaic cell panel is made of polysilicon material in the embodiment, and the temperature correction coefficient is-0.005691 DEG C -1 ；T x (t) surface temperature data for candidate grid cell x at time t; r x (t) is the illumination intensity data (W/m 2) of the surface of the photovoltaic cell plate vertically incident to the alternative grid cell x, and is represented by the illumination intensity data R vertical to the horizontal plane s (t) decomposition to give:
R x (t)＝R s (t)·sin(β x +φ x -δ)
wherein, beta x Arranging the inclination angle of the photovoltaic cell panel in the alternative grid unit x; phi is a x The latitude of the alternative grid unit x; delta is the solar declination angle, and the solar declination angle calculation formula of the m day at the time t is as follows:
the calculation formula of the photovoltaic resource capacity factor is as follows:
and obtaining the photovoltaic resource capacity factor of each alternative grid unit through the calculation.
And fourthly, selecting a plurality of alternative grid units with larger photovoltaic resource capacity factors as pre-construction units of the photovoltaic power station, wherein the photovoltaic planning construction capacity of the pre-construction units is matched with the photovoltaic installed capacity of the construction units.
Specifically, the alternative grid cells are sorted according to the size of the photovoltaic resource capacity factor, then the alternative grid cells with larger photovoltaic resource capacity and 5 lambda N in total are selected from the planning and construction area to serve as the pre-construction cells of the photovoltaic power station, and N is the number of the earth surface grid cells of the planning and construction area. Lambda is the rated installed capacity C of the planned photovoltaic power station e Sum C of installed photovoltaic capacity of earth surface grid unit of planned construction area sum The ratio of (a) to (b).
The pre-construction unit of the photovoltaic power station output by the invention can be used as a primary screening scheme for site selection of the photovoltaic power station, and further site selection planning is carried out according to factors such as the matching degree of the pre-construction unit and the voltage grade, the wiring distance of the transformer substation, the local load demand degree and the like.
Example two:
the embodiment is further designed on the basis of the first embodiment, and the resolution conversion method in the evaluation method of the embodiment adopts an SVM algorithm, and comprises the following specific steps:
by using the SVM classifier based on the gaussian kernel function, the gaussian kernel function generally represents a monotonic function of the euclidean distance from a certain point to the central point in the space, and generally only works locally, specifically, when the distance between the two points is large, the value of the gaussian kernel function is often very small, and the calculation formula is as follows:
wherein y ' is the center of the kernel function, | y-y ' | | represents the Euclidean distance (L2 norm) of the vectors y and y ', and the Gaussian kernel function monotonically decreases with the maximum distance between the two vectors. σ is used to control the range of action of the gaussian kernel function, and a larger value indicates a larger local influence range of the gaussian kernel function. The value of σ has a large influence on the model overfitting.
Then, using longitude and latitude coordinates of the central point of each table grid unit as identifiers to mark categories;
taking longitude as an example, firstly numbering the earth surface grid units in the order of longitude from small to large, taking longitude and latitude coordinates and corresponding categories as training sets to train SVM classifiers, then inputting the longitude of the grid center point in a data set to be converted (a digital elevation data set/an earth surface coverage type data set/illumination intensity/earth surface temperature historical data set) into the trained SVM classifiers, and outputting the category to which the longitude of the grid center point in the data set to be converted belongs by the SVM classifiers. Similarly, the latitude of the central point of each grid is processed similarly to obtain the category to which the latitude belongs. After determining the latitude and longitude category of the central point of the grid in the data set to be converted, filling information data of the grid in the data set to be converted into earth surface grid units to which the corresponding latitude and longitude category belongs, and for a digital elevation data set, filling altitude data and gradient data; filling the earth surface coverage type data into the earth surface coverage type data set; for the historical data set of the illumination intensity, filling the historical data of the illumination intensity; for the surface temperature historical data set, the surface temperature historical data is filled in, and the data set to be converted is converted into the resolution consistent with the surface grid unit.
Example three:
in the embodiment, a land area in China is used as a planning and construction area of the photovoltaic power station, and the method of the second embodiment is adopted to evaluate the photovoltaic power generation potential. Wherein the divided ground grid unit resolution has a length of 0.05 degree latitude and a width of 0.05 degree longitude, and is divided into 1.23 × 10 6 And (4) earth surface grid units. In this example, the SRTM30_ PLUS data set is used as the digital elevation data, the MCD12Q1 data set is used as the surface coverage type data, and the meteorological data set of the European middle and long-term forecasting center is used as the historical data of the illumination intensity and the surface temperature. The typical photovoltaic device selected in this example was a photovoltaic panel of a certain type having a rated capacity of 1MW and a temperature correction coefficient of-0.005691 deg.C -1 The installed capacity per unit area is 50MW/km 2 ，
The method obtains a distribution map of installed photovoltaic capacity (MW/km 2) of a terrestrial region in China and a distribution map of photovoltaic resource capacity factors of a terrestrial region photovoltaic machine-installable region in China.
The obtained distribution diagram shows that the photovoltaic resources are mainly concentrated in the western region in China as a whole, but the installed photovoltaic capacity is mainly distributed in inner Mongolia and Xinjiang. The installed photovoltaic capacity distribution in the regions of Monwest, moneast and northern Xinjiang is most abundant, and the capacity factor of photovoltaic resources is also higher. The photovoltaic installed capacity distribution of Fujian, guangdong coastal areas and Guangxi southern areas is rich, but the photovoltaic resource capacity factor of Guangxi is low, and specific analysis is carried out by taking Jiangsu province as an example.
The potential of photovoltaic installation in Jiangsu province is large, the total installed capacity of a photovoltaic power station is 11276 kilowatts, meanwhile, solar energy resources are rich, and the annual sunshine hours of areas in Jiangsu province are distributed within the range of 1000 hours to 2600 hours based on photovoltaic resource capacity factors calculated based on 2010-2020 illuminance data, the calculated annual theoretical storage capacity of the photovoltaic resources is 930 kilowatts to 1330 kilowatts per square meter, and the annual photovoltaic solar energy absorbed by the earth surface per square meter is equivalent to 115 kg to 170 kg of standard coal heat.
And further analyzing the distribution condition of the solar energy resources in Jiangsu province through a photovoltaic resource capacity factor distribution map of a photovoltaic machinable region, wherein the photovoltaic resources in Jiangsu province are in the trend of Beifeng south poverty. Relatively speaking, the photovoltaic resource capacity factors of areas in the continental harbor region, the north of salt city, the northeast of xu state and the north of dormitory are higher, the photovoltaic resources are relatively rich, the annual average sunshine hours are more than 2000h, and the areas belong to regions with rich resources; the photovoltaic resources in the south-Su area and the middle area are slightly deficient, the sunshine hours are 1400-2000 h, and the solar photovoltaic solar energy-saving system belongs to a resource-deficient area. According to simulation calculation results, the average annual utilization hours of Jiangsu photovoltaic power stations is 1226 hours, the annual photovoltaic power generation amount under the condition of all photovoltaic power generation resources are developed can reach 0.39 billion of kilowatts, and the annual photovoltaic power generation amount is about 39% of the electricity consumption of the whole society in Jiangsu province in 2020.
Claims (9)
1. A photovoltaic power generation potential evaluation method for photovoltaic power station site selection is characterized by comprising the following steps: the method comprises the following steps:
dividing a planning construction area of the photovoltaic power station into a plurality of earth surface grid units, and screening alternative grid units suitable for constructing the photovoltaic power station according to the altitude data and the gradient data of each earth surface grid unit;
determining an effective development coefficient of each alternative grid unit according to the earth surface coverage type data of each alternative grid unit, and calculating the photovoltaic installed capacity of each alternative grid unit according to the area of each alternative grid unit, the effective development coefficient and the installed capacity of the unit area of typical photovoltaic equipment;
calculating the photovoltaic output of typical photovoltaic equipment in each alternative grid unit according to the illumination intensity and the surface temperature historical data of each alternative grid unit, the rated capacity of the typical photovoltaic panel and the temperature correction coefficient, and further calculating the photovoltaic resource capacity factor of each alternative grid unit;
selecting a plurality of alternative grid units with large photovoltaic resource capacity factors as pre-construction units of the photovoltaic power station, wherein the photovoltaic planning construction capacity of the pre-construction units is matched with the photovoltaic installed capacity of the construction units.
2. The method of claim 1 for assessing photovoltaic power generation potential for siting a photovoltaic power plant, wherein: the altitude data and the gradient data of each land grid unit are obtained by the following method:
1) Acquiring digital elevation data of a planned area;
2) Performing resolution conversion on the acquired digital elevation data to obtain digital elevation data under the resolution of the earth surface grid unit;
3) And acquiring altitude data and gradient data of each land form grid unit.
3. The method of claim 1 for assessing photovoltaic power generation potential for siting a photovoltaic power plant, wherein: the earth surface coverage type data of each candidate grid unit is obtained by the following method:
1) Acquiring earth surface coverage type data of a planning area;
2) Performing resolution conversion on the acquired earth surface coverage type data to obtain earth surface coverage type data under the resolution of earth surface grid units;
3) And screening the ground surface coverage type data of each candidate grid cell.
4. The method of claim 1 for assessing photovoltaic power generation potential for siting a photovoltaic power plant, characterized in that: the illumination intensity historical data of each alternative grid unit is obtained by the following method:
1) Acquiring the illumination intensity and surface temperature historical data of a planned area;
2) Performing resolution conversion on the acquired historical data of the illumination intensity and the surface temperature to obtain historical data of the illumination intensity under the resolution of the surface grid unit;
3) And screening out the illumination intensity and the surface temperature historical data of each alternative grid unit.
5. The method for assessing the photovoltaic power generation potential of a photovoltaic power plant site selection according to any one of claims 1 to 4, characterized in that: the resolution conversion method adopts SVM algorithm.
6. The method of claim 5 for assessing photovoltaic power generation potential for siting a photovoltaic power plant, wherein: the length range of the surface grid unit resolution is 0.005-0.05 degrees of latitude, and the width range is 0.005-0.05 degrees of longitude.
7. The method of claim 6 for assessing photovoltaic power generation potential for siting a photovoltaic power plant, wherein: the surface coverage type data of the alternative grid units comprise water, evergreen coniferous forests, evergreen broadleaf forests, deciduous coniferous forests, deciduous broadleaf forests, mixed forests, closed shrub forests, sparse shrub forests, forested grasslands, sparse grasslands, permanent wetlands, farmlands, cities and towns, built-up areas, farmlands and natural vegetation inlays, ice, snow and wastelands.
8. The method of claim 7 for assessing photovoltaic power generation potential at a site of a photovoltaic power plant, wherein: the calculation formula of the photovoltaic installed capacity of the alternative grid unit is as follows:
C i ＝AS i ρ i
in the formula, C i The installed photovoltaic capacity of the ith candidate grid unit; a is the installed capacity per unit area of a typical photovoltaic device; rho i Effective development coefficients for the ith candidate grid cell; s i Is the area of the ith candidate grid cell; i is 1,2, \ 8230and the total number of alternative grid cells.
9. The method of claim 8 for assessing photovoltaic power generation potential for siting a photovoltaic power plant, wherein: and the photovoltaic output of the typical photovoltaic equipment in each alternative grid unit adopts the maximum output power of the typical photovoltaic equipment in each alternative grid unit which operates in the maximum power point tracking mode.
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| CN116452246B (en) * | 2023-06-19 | 2023-09-19 | 航天宏图信息技术股份有限公司 | Electromagnetic equipment performance and address selection evaluation method and device and electronic equipment |
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