A method and system for discretizing geographical space of wind-solar energy development potential

Abstract

The application discloses a kind of wind and light energy development potential geospatial discretization method and system, it is related to energy space layout technical field, including: establishing original grid layer;Eliminate the land area that cannot be constructed wind and light resource power station in original grid layer, obtain the grid layer after processing;The theoretical installation potential, power generation potential, development cost of photovoltaic and wind turbine set in each independent geographical unit are calculated;Establish optimization objective function, and the geographical space features in the grid layer after processing are successively optimized using optimization objective function;When the loadable wind and light energy installation potential of available geographical space area is not greater than renewable energy proposed construction installation capacity, stop optimization, complete the geospatial discretization of wind and light energy development potential.The present application not only effectively improves the scientificity of wind and light resource allocation, while ensuring the economy of wind and light resource development and utilization, provides data support and optimization scheme for energy geospatial layout decision.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of energy space layout, more particularly to a geographical space discretization method and system for wind-solar energy development potential. BACKGROUND

[0002] At present, problems such as the mismatched layout of wind-solar endowments and power demand restrict the development process of wind-solar energy to some extent. Compared with traditional fossil energy, clean energy production occupies a larger land area to produce the same amount of power, and land resources have gradually become a factor restricting the development and utilization of clean energy. Geographical environmental conditions are an important standard for judging the feasibility of renewable energy infrastructure construction, and many studies have established corresponding geographical environmental condition evaluation systems and evaluation systems for wind-solar energy development suitable regions. However, the geographical space discretization method for wind-solar energy development potential needs to be further deepened, and how to realize the geographical space discretization of wind-solar energy development potential is a key problem that needs to be solved by the technical personnel in the field. SUMMARY

[0003] Therefore, the present application provides a geographical space discretization method and system for wind-solar energy development potential to solve the problems in the background art.

[0004] In order to achieve the above-mentioned purpose, the present application adopts the following technical solution:

[0005] A geographical space discretization method for wind-solar energy development potential comprises:

[0006] Collecting original data to establish an original grid layer;

[0007] Removing the land area in the original grid layer that is not suitable for constructing wind-solar resource power stations to obtain a grid layer supporting wind-solar resource development and construction;

[0008] Calculating the theoretical installed capacity potential, power generation potential, and development cost of photovoltaic power generation and wind power generation in each independent geographical unit in the grid layer;

[0009] Based on the obtained theoretical installed capacity potential, power generation potential, and development cost, an optimization objective function is established, and the geographical space features in the grid layer are sequentially optimized using the optimization objective function;

[0010] When the loadable wind-solar energy installed capacity of the available geographical space area is not greater than the renewable energy proposed construction installed capacity potential, the optimization is stopped, and the geographical space discretization of the wind-solar energy development potential is completed.

[0011] Optionally, the geographical grid precision of the original raster layer is resampled to 1km*1km, and the original data includes wind power density, light radiation intensity, capacity factor, terrain slope, land use type, and energy infrastructure; the land use types to be excluded include land use types that cannot establish wind and light resource power stations, terrain slope, distance from urban area, distance from road, and natural reserve boundary.

[0012] Optionally, the onshore wind energy density ρ wind is estimated according to the wind turbine wind .

[0013] ρ turbine = P 2 ·(n turbine ·D 2 -1 .

[0014] In the formula, P turbine is the rated power of the onshore wind turbine; D turbine is the rotor diameter of the onshore wind turbine; and n is the ratio of the land occupation side length of the onshore wind turbine to the rotor diameter.

[0015] According to the wind power density and unit pixel area of different regions, the theoretical installation potential P wind of the onshore wind turbine is calculated according to the following formula:

[0016] P wind =S wind ·ρ wind .

[0017] In the formula, ρ wind represents the onshore wind power density; and S wind represents the installation pixel area of the onshore wind turbine.

[0018] Optionally, the theoretical power generation potential E wind of the wind turbine is calculated according to the following formula:

[0019] E wind =P wind ·T h ·C f .

[0020] In the formula, P wind is the theoretical installation potential of the wind turbine; T h is the annual hours; and C f is the capacity factor of the wind turbine, representing the ratio of the power generation of the wind turbine in a period of time to the maximum power generation under the rated power.

[0021] Optionally, the levelized cost of electricity (LCOE) is selected as the development cost index in the renewable energy development area, and the wind power development cost LCOE is calculated wind The calculation formula is as follows:

[0022]

[0023] In the formula, LCOE wind is the cost of electricity per point; P wind is the installed capacity potential of each point; μ fix is the total investment cost; R y is the ratio of operation and maintenance cost to investment cost; r d is the discount rate; E wind is the power generation potential of wind power; T is the operation period; μ line is the unit transmission line cost; d line is the length of the transmission line.

[0024] Optionally, the theoretical installed capacity potential P solar of the photovoltaic generator set is calculated as follows:

[0025] P solar = P w · Ω f · S solar ;

[0026] In the formula, P w is the rated power of the photovoltaic component per unit area; Ω f is the area factor, representing the proportion of the area of the photovoltaic panel covering the calculated land, which is inversely proportional to the latitude, and the higher the latitude, the smaller the area factor; S solar is the area suitable for laying photovoltaic components in each pixel.

[0027] Optionally, the theoretical power generation potential E solar of the photovoltaic generator set is calculated as follows:

[0028] E solar = R A · S solar · T h · η · k;

[0029] In the formula, R A is the intensity of solar radiation; T h is the annual hours; η is the conversion efficiency coefficient; and k is the correction coefficient.

[0030] Optionally, the calculation formula of the photovoltaic power development cost LCOE solar is as follows:

[0031]

[0032] LCOE solar is the cost per kWh of each point; P solar is the theoretical installed capacity potential of each point; μ fix is the total investment cost per unit installed capacity; R y is the ratio of operation and maintenance cost to investment cost; r d is the discount rate; E solar is the theoretical power generation potential of photovoltaic power generation; T is the operation cycle; μ linr is the cost per unit of transmission line; d line is the length of the transmission line.

[0033] Optionally, the objective function can be represented as:

[0034]

[0035] In the formula, min is the minimization objective function, max is the maximization objective function, P wind and P solar respectively represent the theoretical installed capacity potential of each suitable point; E wind and E solar respectively represent the theoretical power generation potential of each suitable point; LCOE wind and LCOE solar respectively represent the cost per kWh of each suitable point, S wind and S solar respectively represent the land area of each suitable point; ε is a floating coefficient; P T represents the proposed installed capacity. Among them, the suitable point means a suitable location for the construction of wind power and photovoltaic power generation. After the most suitable point is identified, the second suitable point is searched, and so on. When the loadable wind and light energy installed capacity of the available geographical space area is not greater than the non-hydropower renewable energy proposed installed capacity P T , stop optimization.

[0036] A geographical space discretization system for wind and light energy development potential, comprising:

[0037] A basic layer establishment module collects original data and establishes an original raster layer;

[0038] A raster layer elimination module eliminates land areas that cannot construct wind and light resource power stations in the original raster layer to obtain a raster layer supporting wind and light resource development and construction;

[0039] An installed capacity potential quantification module calculates the theoretical installed capacity potential, power generation potential and development cost of photovoltaic and wind turbine generator sets in each independent geographical unit in the raster layer;

[0040] An optimization function construction module is constructed based on the obtained theoretical installed capacity potential, power generation potential and development cost;

[0041] A geographic space identification module uses the optimization function to perform successive optimization on the geographic space, and stops the optimization when the loadable wind and light energy installed capacity potential of the available geographic space area is not greater than the renewable energy proposed installed capacity, thereby completing the geographic space discretization of the wind and light energy development potential.

[0042] Compared with the prior art, the method and system for geographic space discretization of wind and light energy development potential provided by the application comprises the following steps: collecting original data and establishing an original grid layer; removing the land area unsuitable for construction of wind and light generator sets in the original grid layer to obtain a grid layer supporting wind and light resource development and construction; calculating the theoretical installed capacity potential, power generation potential and development cost of photovoltaic and wind power generator sets in each independent geographic unit; constructing an optimization function based on the obtained theoretical installed capacity potential, power generation potential and development cost; using the optimization function to perform successive optimization on the geographic space features in the processed grid layer; and stopping the optimization when the loadable wind and light energy installed capacity potential of the available geographic space area is not greater than the renewable energy proposed installed capacity, thereby completing the geographic space discretization of the wind and light energy development potential. The application collects and analyzes original data systematically, removes the area unsuitable for construction of power stations, calculates the theoretical installed capacity potential, power generation potential and development cost, and uses the optimization function to perform step-by-step optimization, thereby effectively improving the scientificity of wind and light resource allocation, ensuring the economy of wind and light resource development and utilization, and providing data support and optimization scheme for energy geographic space layout decision. BRIEF DESCRIPTION OF DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings described below are only a part of the embodiments of the present application, and for those skilled in the art, other drawings can be obtained without creative labor based on the provided drawings.

[0044] Figure 1 The method flowchart provided by the present application. DETAILED DESCRIPTION

[0045] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the protection scope of the present application.

[0046] The embodiment of the present application discloses a geographical space discretization method for wind and light energy development potential, as shown in the formula (1), comprising: Figure 1

[0047] Collecting original data and establishing an original grid layer;

[0048] Removing the land area that cannot be used to build wind and light resource power stations in the original grid layer to obtain a grid layer supporting wind and light resource development and construction;

[0049] Calculating the theoretical installed potential, power generation potential, and development cost of wind and light generator sets in each independent geographical unit in the grid layer;

[0050] Based on the obtained theoretical installed potential, power generation potential, development cost, and land area, an optimization objective function is established, and the geographical space features in the grid layer are sequentially optimized by using the optimization objective function;

[0051] When the loadable wind and light energy installed potential of the available geographical space area is not greater than the renewable energy proposed installed capacity, the optimization is stopped, and the geographical space discretization of the wind and light energy development potential is completed.

[0052] In a specific embodiment, the geographical grid precision of the original grid layer is resampled to 1 km*1 km, the original data includes wind power density, light radiation intensity, capacity factor, terrain slope, land use type, energy infrastructure, and the like, and the proposed removed land types include land use types that cannot be used to build wind and light resource power stations, terrain slope, distance from the city, distance from the road, and natural reserve boundary.

[0053] In a specific embodiment, the reference wind turbine is used to estimate the onshore wind energy density ρ wind , and the calculation formula is as follows:

[0054] ρ wind =P turbine· (n 2 ·D turbine 2 ) -1 ;

[0055] In the formula, P turbine is the rated power of the onshore wind turbine, D turbine is the rotor diameter of the onshore wind turbine, and n is the ratio of the land occupation side length to the rotor diameter of the onshore wind turbine.

[0056] According to the wind power density and unit pixel area of different regions, the theoretical installed potential P wind of the onshore wind turbine is calculated according to the following formula:

[0057] P wind =S​wind ·p wind ;

[0058] wherein p wind represents the onshore wind power density; S wind represents the installation pixel area of the onshore wind turbine generator.

[0059] In one specific embodiment, the theoretical power generation potential E wind of the wind turbine generator is calculated according to the following formula:

[0060] E wind = P wind · T h · C f ;

[0061] wherein P wind is the theoretical installation potential of the wind turbine generator; T h is the annual hours; and C f is the capacity factor of the wind power generation, representing the ratio of the power generation of the wind turbine generator in a period of time to the maximum power generation at the rated power.

[0062] In one specific embodiment, the levelized cost of electricity (LCOE) is selected as the development cost indicator in the renewable energy development area, and the wind power development cost is calculated according to the following formula:

[0063]

[0064] wherein LCOE wind is the cost of electricity of each point; P wind is the theoretical installation potential of each point; μ fix is the total investment cost per unit installation; R y is the ratio of the operation and maintenance cost to the investment cost; r d is the discount rate; E wind is the theoretical power generation potential of the wind turbine generator; T is the operation period; μ line is the unit transmission line cost; and d line is the length of the transmission line.

[0065] In one specific embodiment, the theoretical installation potential P solar of the photovoltaic turbine generator is calculated according to the following formula:

[0066] P solar = P w · Ω f · S solar ;

[0067] wherein P w is the rated power of the photovoltaic component per unit area; Ω fis the area factor, representing the proportion of the area of the land that can be covered by the photovoltaic panel, which is inversely proportional to the latitude, i.e., the higher the latitude, the smaller the area factor; S solar is the area of the photovoltaic module that can be appropriately laid in each pixel.

[0068] In a specific embodiment, the theoretical power generation potential E solar of the photovoltaic power generator set is calculated according to the following formula:

[0069] E solar = R A · S solar · T h · η · k

[0070] wherein R A is the intensity of the light radiation; T h is the annual utilization hours; η is the conversion efficiency coefficient, including the conversion efficiency of the photovoltaic cell, the array efficiency of the photovoltaic module, the efficiency of the inverter, etc.; and k is the correction coefficient, including the attenuation coefficient, the shielding coefficient, the temperature reduction, the inclination angle correction coefficient, etc.

[0071] In a specific embodiment, the calculation formula of the photovoltaic power generation development cost LCOE solar is as follows:

[0072]

[0073] wherein LCOE solar is the cost per degree of electricity of each point; P solar is the theoretical installed potential of each point; μ fix is the total investment cost per unit of installed capacity; R y is the ratio of operation and maintenance cost to investment cost; r d is the discount rate; E solar is the theoretical power generation potential of the photovoltaic power generation; T is the operation period; μ line is the cost per unit of transmission line; and d line is the length of the transmission line.

[0074] In a specific embodiment, the objective function can be represented as:

[0075]

[0076] wherein min is the minimization objective function, max is the maximization objective function, P wind and P solar represent the theoretical installed potential of each suitable point, respectively; E wind and E solar represent the theoretical power generation potential of each suitable point, respectively; LCOE wind and LCOE solarrespectively represent the degree electricity cost of each suitable point, S wind and S solar respectively represent the land area of each suitable point; ε is a floating coefficient; P T represents the proposed installed capacity. Among them, the suitable point means a suitable location that can be used for the construction of wind power and photovoltaic power generation. After the most suitable point is identified, the second suitable point is found, and so on. When the available geographical space area can carry wind and light energy installation potential is less than the non-hydropower renewable energy proposed installed capacity P T , stop optimization.

[0077] Based on ArcGIS, the superposition, elimination and fusion between multi-dimensional layers are carried out, the wind and light resource endowments in different regions are comprehensively considered, the wind power density, solar radiation intensity, capacity factor, terrain slope, land use type, energy infrastructure and the like are superposed, the unusable land use type, terrain slope, distance from city, distance from road and natural protection area boundary and the like are eliminated, and the geographical space layout suitable for developing wind and light energy is identified. Combined with the calculation method of unit pixel wind and light power generation, the theoretical installed potential, power generation potential and development cost of wind and light generator set are quantified. The installed potential is used to reflect the maximum installed capacity that can be realized under the existing technical conditions, the power generation potential is used to reflect the maximum power generation that can be realized under the existing technical conditions, and the development cost involves the whole life cycle cost from equipment procurement, installation to operation and maintenance. Not only the scientificity of wind and light resource allocation is effectively improved, but also the economy of wind and light resource development and utilization is ensured, which provides data support and optimization scheme for energy geographical space layout decision.

[0078] A geographical space discretization system of wind and light energy development potential, comprising:

[0079] A basic layer establishment module collects original data and establishes an original raster layer;

[0080] A raster layer elimination module eliminates the land area that cannot construct wind and light resource power stations in the original raster layer, and obtains a raster layer supporting wind and light resource development and construction;

[0081] An installed potential quantification module calculates the theoretical installed potential, power generation potential and development cost of photovoltaic generator and wind turbine in each independent geographical unit in the raster layer;

[0082] An optimization function construction module establishes an optimization objective function based on the obtained theoretical installed potential, power generation potential, development cost and land area;

[0083] The geographic space identification module uses an optimization objective function to perform successive optimization of the geographic space. When the available loadable wind and light energy installation potential of the available geographic space area is not greater than the renewable energy installation capacity to be constructed, the optimization is stopped, and the geographic space discretization of the wind and light energy development potential is completed.

[0084] The various embodiments are described in the specification with progressive levels of formality in order to facilitate the reader's understanding of the various embodiments. Each embodiment focuses on the differences from other embodiments, and the same or similar parts among the various embodiments can be mutually referred to. For the apparatus disclosed by the embodiments, since it corresponds to the method disclosed by the embodiments, the description is relatively simple, and the relevant parts can be referred to the method part.

[0085] The above description of disclosed embodiments enables a person skilled in the art to implement or use the present application. Various modifications to the embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A geospatial discretization method for assessing the development potential of wind and solar energy, characterized in that, include: Collect raw data and create the original raster layer; Remove the land area in the original raster layer that is not suitable for building wind and solar power stations, and obtain the raster layer that supports the development and construction of wind and solar resources; Calculate the theoretical installed capacity potential, power generation potential, and development cost of photovoltaic and wind power generation in each independent geographic unit within the raster layer; Based on the obtained theoretical installed capacity potential, power generation potential, and development cost, an optimization objective function is established, and the geospatial features in the raster layer are successively optimized using the optimization objective function. When the potential for wind and solar energy installation in the available geographical space is not greater than the planned installed capacity of renewable energy, the optimization process is stopped, and the geographical space for wind and solar energy development potential is discretized. Estimating onshore wind power density using reference wind turbines The calculation formula is as follows: ； In the formula, This refers to the rated power of the onshore wind turbine. This refers to the rotor diameter of an onshore wind turbine. This is the ratio of the side length of the footprint of an onshore wind turbine to the rotor diameter. Theoretical installed capacity potential of onshore wind turbines The calculation formula is as follows: ； In the formula, Represents onshore wind power density; Represents the installed pixel area of ​​onshore wind turbine units; Theoretical power generation potential of wind turbine generators The calculation formula is as follows: ； In the formula, The theoretical installed capacity potential of wind turbine generators; Hours per year; The capacity factor of a wind turbine generator is the ratio of the power generated by the wind turbine generator over a period of time to its maximum power generation at rated power. In renewable energy development areas, the levelized cost of electricity (LCOE) is selected as the development cost indicator. The calculation process for wind power development costs is as follows: ； In the formula, Cost per kilowatt-hour for each location; The installation potential at each location; This represents the total investment cost. This is the ratio of operation and maintenance costs to investment costs. The discount rate; The power generation potential of wind power; For the operating cycle; Cost per unit of power transmission line; This refers to the length of the power transmission line; Theoretical installed capacity potential of photovoltaic power generation units The calculation formula is as follows: ； In the formula, Rated power of photovoltaic modules per unit area; The area factor represents the proportion of land area that can be covered by photovoltaic panels. It is inversely proportional to latitude; the higher the latitude, the smaller the area factor. The area suitable for laying photovoltaic modules within each pixel; Theoretical power generation potential of photovoltaic generator sets The calculation formula is as follows: ； In the formula, Intensity of light radiation; Hours per year; The conversion efficiency coefficient; This is a correction factor; Photovoltaic power generation development costs The calculation formula is as follows: ； In the formula, Cost per kilowatt-hour for each location; The theoretical installed capacity potential for each location; The total investment cost per unit of installed capacity; This is the ratio of operation and maintenance costs to investment costs. The discount rate; This represents the theoretical power generation potential of photovoltaic generator sets; For the operating cycle; Cost per unit of power transmission line; This refers to the length of the power transmission line; The objective function is expressed as: ； In the formula, min represents the minimization objective function, and max represents the maximization objective function. Each represents the theoretical installed capacity potential of a suitable location; Each represents the theoretical power generation potential of a suitable location; and These represent the cost per kilowatt-hour for each suitable location. and Each represents the area occupied by a suitable location; This is a floating coefficient; This represents the proposed installed capacity. Suitable locations refer to ideal sites for wind and solar power generation. Once the most suitable site is identified, the next most suitable sites are identified, and so on. The maximum usable geographical area that can support wind and solar power capacity is no greater than the proposed installed capacity of non-hydropower renewable energy. When that happens, stop the optimization process.

2. The geospatial discretization method for wind and solar energy development potential according to claim 1, characterized in that, The geographic grid precision of the original raster layer was resampled to 1 kilometer. The original data for the 1-kilometer area includes wind power density, solar radiation intensity, capacity factor, terrain slope, land use type, and energy infrastructure; land use types that cannot be used to build wind and solar power stations are to be excluded.

3. A geospatial discretization system for wind and solar energy development potential, characterized in that, The geospatial discretization method for wind and solar energy development potential according to any one of claims 1-2 includes: The basic layer creation module collects raw data and creates the original raster layer; The raster layer removal module removes land areas from the original raster layer that are unsuitable for the construction of wind and solar power plants, and obtains a raster layer that supports the development and construction of wind and solar resources. The module for quantifying installed capacity potential calculates the theoretical installed capacity potential, power generation potential, and development cost of photovoltaic and wind power generation in each independent geographic unit within the raster layer. The optimization function construction module establishes an optimization objective function based on the obtained theoretical installed capacity potential, power generation potential, and development cost. The geospatial identification module uses an optimization objective function to successively optimize the geospatial features in the raster layer. When the potential of the usable geospatial area to support wind and solar energy installations is not greater than the planned installed capacity of renewable energy, the optimization stops, thus completing the geospatial discretization of the wind and solar energy development potential.

Images