Traffic energy power generation potential calculation method based on meteorological information

Abstract

The invention relates to a traffic energy power generation potential calculation method based on meteorological information, belongs to the field of traffic energy potential quantification, and solves the problem of low accuracy of a traffic energy available power generation potential quantification result. Comprising the following steps: calculating a unit installed photovoltaic power generation sequence of each grid point based on meteorological information and photovoltaic array information of the grid point; calculating the traffic network roadside photovoltaic available mileage and the photovoltaic potential laying area of each grid point based on the OSM original road network data and the unit installation land area, and further obtaining the traffic network roadside photovoltaic potential installed capacity; based on the unit installed photovoltaic power generation sequence of each grid point and the potential photovoltaic installed capacity of the road side of the traffic network, matching the unit installed photovoltaic power generation sequence corresponding to the nearest grid point for the segmented land road, and calculating a photovoltaic power generation potential sequence of the road side of the segmented land road; and summarizing and calculating the photovoltaic power generation potential sequence of the road side of each subsection land road in each region in the to-be-measured range to obtain the total photovoltaic power generation potential of the road side of the land road in each region.

Description

Technical Field

[0001] The present invention relates to the technical field of quantification of transportation energy potential, and in particular to a method for calculating transportation energy power generation potential based on meteorological information. Background Art

[0002] Energy conservation and emission reduction in the transportation sector is one of the keys to the transformation and upgrading of the industry. Energy and transportation account for the highest proportion of carbon emissions in my country, at 43% and 26% respectively. Energy conservation and emission reduction in the transportation sector has become one of the key parts of the transformation and upgrading of the industry. In the terminal energy consumption structure, transportation energy accounts for about 17%. In the carbon emission structure, transportation accounts for about 10.4%, while in the transportation energy structure, electricity accounts for less than 5%, and green electricity accounts for less than 2%. Promoting the substitution of green electricity in typical application scenarios such as roads, ports, and railways can effectively play the role of reliable on-site substitution of new energy. Therefore, evaluating the energy potential of land transportation is of great significance to the development of transportation energy integration and green transportation energy in my country.

[0003] The entry point of existing technologies for transportation energy conversion for transportation networks is mostly electric vehicles on the load side, lacking consideration of the synergy of the supply side of the transportation network and ignoring the natural resource endowment of the road network. Most of the existing technologies for evaluating the natural endowment potential of transportation systems adopt the method of dividing by resource areas, lacking evaluation methods that take into account the refined meteorological data corresponding to different roads. In addition, existing technologies mostly focus on the analysis of the energy supply potential of renewable energy at a time resolution of days, months, and years. However, the hourly volatility and uncertainty of new energy require the configuration of corresponding hourly energy storage systems. Existing technologies cannot further carry out matching analysis of sources and loads on a more precise time scale, thus affecting the precise analysis and optimization of the power system. Summary of the invention

[0004] In view of the above analysis, an embodiment of the present invention aims to provide a method for calculating the power generation potential of transportation energy based on meteorological information, so as to solve the technical problem of low accuracy of the quantification results of the available power generation potential of transportation energy in the existing methods.

[0005] The purpose of the present invention is mainly achieved through the following technical solutions:

[0006] The present invention provides a method for calculating the power generation potential of transportation energy based on meteorological information, comprising the following steps:

[0007] Step S1, calculating the unit installed capacity photovoltaic power generation sequence of each grid point based on the meteorological information and photovoltaic array information of the grid point;

[0008] Step S2: Based on the original road network data of OSM and the unit installed land area, the available mileage and potential photovoltaic paving area of ​​the transportation network side of each grid point are calculated, and then the potential photovoltaic installed capacity of the transportation network side is obtained;

[0009] Step S3, based on the unit installed photovoltaic power generation sequence of each grid point and the potential photovoltaic installed capacity on the transportation network side, matching the unit installed photovoltaic power generation sequence corresponding to the nearest grid point for the segmented land road, and calculating the photovoltaic power generation potential sequence on the side of the segmented land road;

[0010] Step S4, summarizing and calculating the photovoltaic power generation potential sequence of each segmented land road side of each area within the range to be measured, and obtaining the total photovoltaic power generation potential of the land road side of each area;

[0011] Wherein, a region includes one or more grid points.

[0012] Furthermore, the step S1 comprises:

[0013] Divide the range to be measured into multiple grid points according to a predetermined spatial resolution;

[0014] Obtain meteorological information and photovoltaic array information for each grid point;

[0015] Based on the meteorological information of each grid point, the actual irradiance received by the photovoltaic panel at each grid point at time t is calculated as follows:

[0016] GHI t =DHI t +DNI t ×cosθ Z,t

[0017]

[0018] F t =1-(DHI t ÷GHI t ) 2

[0019] Among them, GHI t 、DNI t , DHI t are the global downward irradiance, direct irradiance component and diffuse irradiance component at time t respectively; θ Z,t is the solar zenith angle at time t; GTI t is the actual amount of radiation received by the photovoltaic panel at time t; β t 、f albedo,t are the photovoltaic array inclination angle and the surface albedo at time t; M t is the scattered radiation component coefficient at time t; F t is the intermediate variable; αt is the plane incident angle of the photovoltaic panel at time t;

[0020] The irradiance actually received by the photovoltaic panel at each grid point is sorted in time to form a sequence of irradiance actually received by the photovoltaic panel;

[0021] Based on the actual irradiation received by the photovoltaic panels at each grid point at time t, the unit installed photovoltaic power generation P at each grid point at time t is calculated. pvt,t ,as follows:

[0022]

[0023] Among them, f pv is the photovoltaic derating factor; I0 is the irradiance under the standard test environment; α p is the power temperature coefficient of the photovoltaic panel assembly; T0 is the temperature of the photovoltaic panel assembly under the standard test environment; T t is the actual temperature of the photovoltaic panel assembly;

[0024] The unit installed photovoltaic power generation of each grid point is arranged in time to form a unit installed photovoltaic power generation sequence.

[0025] Furthermore, the step S2 comprises:

[0026] Obtaining the original OSM road network data and screening and cleaning it to obtain segmented and usable road network data;

[0027] Each section of available road network data includes a plurality of latitude and longitude coordinate pairs arranged in order, and the geodesic distances between adjacent latitude and longitude coordinate pairs are calculated and summed to obtain the total geodesic distance of each section of land road as the available mileage of each section of land road;

[0028] Based on the available mileage of each land section, select the corresponding paving width on both sides of the road for different types of land roads based on the scenario, and multiply the available mileage of each land section by the corresponding paving width on both sides of the road to obtain the photovoltaic paving area of ​​each land section;

[0029] Summarize the photovoltaic paving area of ​​each section of land in each grid point to obtain the potential photovoltaic paving area on the transportation network side of each grid point;

[0030] Based on the potential photovoltaic laying area on the transportation network side of each grid point and the land area for building photovoltaic power stations, the potential photovoltaic installed capacity on the transportation network side is calculated.

[0031] Furthermore, the step S3 comprises:

[0032] According to the coordinates of the grid points and the coordinates of the representative points of each land section, the nearest grid points are matched for the land road representative points in the region;

[0033] For each land representative point r in the region j ∈A, perform the following matching calculation to obtain the nearest grid point g k(j) The index k(j) of:

[0034] k(j)=argmin i∈{1,2,...,n} d[(lat j ,lon j ),(lat i ,lon i )]

[0035]

[0036] in, is the set of representative land points in the region; r j is the representative point of the jth land route; n is the number of grid points; (lat i ,lon i ) is the radian longitude and latitude coordinates of the i-th grid point; (lat j ,lon j ) is the latitude and longitude coordinates of the jth land representative point in radians; d[(lat j ,lon j ),(lat i ,lon i )] is the spherical distance between two longitude and latitude coordinate pairs, and R is the approximate radius of the earth;

[0037] Based on the index k(j) of the nearest grid point matched to each land representative point, the unit installed capacity photovoltaic power generation sequence of the nearest grid point is obtained as the photovoltaic power generation potential sequence on the road side of each segmented land road;

[0038] The representative point of each land route segment is the first coordinate pair among the L coordinate pairs of each segmented land route, where L≥1.

[0039] Furthermore, in step S4, based on the photovoltaic potential installed capacity and the unit installed capacity power generation potential sequence on the land side of each segment of each region, the total photovoltaic power generation potential on the land side of the region is calculated as follows:

[0040]

[0041] Among them, W scen,T P is the total power generation potential of roadside photovoltaic power generation in the area within T time under the scenario scen; E,scen,j is the potential installed capacity of roadside photovoltaic power generation for the jth section of land under the scenario ScEN; k(j) (t) is the unit installed photovoltaic output of the roadside photovoltaic power generation of the jth land road at time t; m is the number of land road sections in the region.

[0042] Furthermore, the actual temperature T of the photovoltaic panel assembly t , calculated as follows:

[0043]

[0044] Among them, T a is the external environment temperature.

[0045] Furthermore, the plane incident angle α of the photovoltaic panel at time t is t , calculated as follows:

[0046] α t =arccos[cosβ t ×cosθ Z,t +sinβ t ×sinθ Z,t ×cos(θ A,t -λ t )]

[0047] Among them, θ A,t is the solar azimuth at time t; t is the azimuth angle of the photovoltaic array at time t.

[0048] Furthermore, the OSM original road network data includes highway network data and railway network data;

[0049] The available road network data includes the expressway, national highway, provincial highway data in the road network data and the railway data in the railway network;

[0050] The available road network data is a collection of segmented land roads.

[0051] Furthermore, the scenario scen includes three scenarios: conservative paving, general paving, and optimistic paving; the three scenarios correspond to three installation widths.

[0052] Further, the meteorological information includes weather data and sun position information;

[0053] The weather data includes radiation, surface albedo and external ambient temperature; wherein the radiation includes direct radiation component and scattered radiation component;

[0054] The solar position information includes the solar zenith angle and the solar azimuth angle.

[0055] The photovoltaic array information includes a photovoltaic panel tracking method and an optimal inclination angle of the photovoltaic panel at each grid point.

[0056] Compared with the prior art, the present invention can achieve at least one of the following beneficial effects:

[0057] 1. The present invention provides a refined evaluation method by combining meteorological information and traffic network data, which can more accurately quantify the available power generation potential of traffic energy, thereby improving the accuracy of the energy potential quantification results;

[0058] 2. The present invention adopts a method of dividing by grid points and combines refined meteorological data to provide a more accurate assessment method based on meteorological data, which helps to more accurately assess the energy potential corresponding to different roads;

[0059] 3. By evaluating the energy potential of land transportation, the present invention helps promote green electricity substitution in typical application scenarios such as roads and railways, effectively plays the role of local and reliable substitution of new energy, and is of great significance for achieving the dual carbon goals;

[0060] 4. By evaluating and quantifying the potential of transportation energy, the present invention helps to optimize the green development of transportation energy, promote energy conservation and emission reduction in the transportation field, have a positive impact on the integrated development of transportation and energy, and optimize the green development of transportation energy.

[0061] In the present invention, the above-mentioned technical solutions can also be combined with each other to achieve more preferred combination solutions. Other features and advantages of the present invention will be described in the subsequent description, and some advantages can become obvious from the description, or can be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained through the contents particularly pointed out in the description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] The drawings are only for the purpose of illustrating particular embodiments and are not to be considered limiting of the present invention. Like reference symbols denote like components throughout the drawings.

[0063] Figure 1 This is a flow chart of a method for calculating the power generation potential of transportation energy based on meteorological information in an embodiment of the present invention. DETAILED DESCRIPTION

[0064] The preferred embodiments of the present invention are described in detail below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not used to limit the scope of the present invention.

[0065] The present invention provides a method for calculating the potential of transportation energy generation based on meteorological information, which can consider refined meteorological data and road network data to quantify the energy photovoltaic power generation potential of a large-scale transportation network at a fine scale of time and space.

[0066] A specific embodiment of the present invention, as Figure 1 As shown, a method for calculating the power generation potential of transportation energy based on meteorological information is disclosed, comprising the following steps:

[0067] Step S1, calculating the unit installed photovoltaic power generation sequence of each grid point based on the meteorological information and photovoltaic array information of the grid point;

[0068] Step S2, based on the original road network data of OSM (Open Street Map) and the unit installed land area, the available mileage of photovoltaic power generation on the transportation network side and the potential photovoltaic paving area of ​​each grid point are calculated, and then the potential photovoltaic installed capacity on the transportation network side is obtained;

[0069] Step S3, based on the unit installed photovoltaic power generation sequence of each grid point and the potential photovoltaic installed capacity on the transportation network side, matching the unit installed photovoltaic power generation sequence corresponding to the nearest grid point for the segmented land road, and calculating the photovoltaic power generation potential sequence on the side of the segmented land road;

[0070] Step S4, summarizing and calculating the photovoltaic power generation potential sequence of each segmented land road side of each area within the range to be measured, and obtaining the total photovoltaic power generation potential of the land road side of each area;

[0071] Wherein, a region includes one or more grid points.

[0072] The step S1 comprises:

[0073] Divide the range to be measured into multiple grid points according to a predetermined spatial resolution;

[0074] Obtain meteorological information and photovoltaic array information for each grid point;

[0075] Based on the meteorological information of each grid point, the actual irradiance received by the photovoltaic panel at each grid point at time t is calculated as follows:

[0076] GHI t =DHI t +DNI t ×cosθ Z,t Formula (1)

[0077]

[0078] F t =1-(DHI t ÷GHI t ) 2

[0079] Formula (4)

[0080] Among them, GHI t 、DNI t , DHI t are the global downward irradiance, direct irradiance component and diffuse irradiance component at time t respectively; θ Z,tis the solar zenith angle at time t; GTI t is the actual amount of radiation received by the photovoltaic panel at time t; β t 、f albedo,t are the photovoltaic array inclination angle and the surface albedo at time t; M t is the scattered radiation component coefficient at time t; F t is the intermediate variable; α t is the plane incident angle of the photovoltaic panel at time t;

[0081] The irradiance actually received by the photovoltaic panel at each grid point is sorted in time to form a sequence of irradiance actually received by the photovoltaic panel;

[0082] Based on the actual irradiation received by the photovoltaic panels at each grid point at time t, the unit installed photovoltaic power generation P at each grid point at time t is calculated. pvt,t ,as follows:

[0083]

[0084] Among them, f pv is the photovoltaic derating factor; I0 is the irradiance under the standard test environment; α p is the power temperature coefficient of the photovoltaic panel assembly; T0 is the temperature of the photovoltaic panel assembly under the standard test environment; T t is the actual temperature of the photovoltaic panel assembly;

[0085] The unit installed photovoltaic power generation of each grid point is arranged in time to form a unit installed photovoltaic power generation sequence.

[0086] Among them, F t The intermediate variables used for the convenience of calculation have no special physical meaning.

[0087] For example, f pv Set to 0.9, which can be adjusted at any time according to actual needs; I0 is the standard value, which is 1000W / m 2 ; α p It is an empirical value, set to -0.0046, and can be adjusted at any time according to actual needs.

[0088] Unit installed photovoltaic power generation P pvt,t , in this embodiment, it is the hourly output sequence of the unit installed photovoltaic power for 8760h.

[0089] The actual temperature T of the photovoltaic panel assembly t , calculated as follows:

[0090]

[0091] Among them, T a is the external environment temperature.

[0092] Exemplarily, T0 is a standard value, set to 25°C.

[0093] T a is the external environment temperature (hourly temperature data); T0 is the temperature of the photovoltaic cell module under the standard test environment.

[0094] The plane incident angle α of the photovoltaic panel at time t t , calculated as follows:

[0095] α t =arccos[cosβ t ×cosθ Z,t +sinβ t ×sinθ Z,t ×cos(θ A,t -λ t )]

[0096] Formula (7)

[0097] Among them, θ A,t is the solar azimuth at time t; t is the azimuth angle of the photovoltaic array at time t.

[0098] Each area within the scope to be measured is divided into a plurality of grid points according to a predetermined spatial resolution; illustratively, 4158 grid points are evenly distributed across the country at a predetermined spatial allocation rate of 0.5°×0.5°.

[0099] The grid point refers to dividing the entire country into multiple grids, and the center point of the grid is the grid point. The present invention divides the grid points according to a predetermined spatial allocation rate of 0.5°×0.5°, and the predetermined spatial resolution can be selected according to specific needs.

[0100] The meteorological information includes weather data and sun position information;

[0101] The weather data includes radiation, surface albedo and external ambient temperature; wherein the radiation includes direct radiation component and scattered radiation component;

[0102] The solar position information includes the solar zenith angle and the solar azimuth angle.

[0103] The photovoltaic array information includes a photovoltaic panel tracking method and an optimal inclination angle of the photovoltaic panel at each grid point.

[0104] The photovoltaic array information is set by the present invention, including: photovoltaic panel tracking mode (taking inclined single axis as an example) and optimal inclination angle of photovoltaic panels.

[0105] The weather information comes from the NASA POWER project platform. The NASA POWER project platform is an open source platform and you can download the data yourself.

[0106] The optimal tilt angle of photovoltaic panels is the optimal tilt angle corresponding to each county and city downloaded (generally, the tilt angle with the largest received radiation is calculated based on historical data). The present invention does not strictly stipulate that the optimal tilt angle must be a certain degree, so local areas can adjust it according to their needs.

[0107] Exemplarily, meteorological information and photovoltaic array information of 4158 grid points are obtained; the meteorological information in the embodiment of the present invention includes weather data and solar position data of all grid points for 8760 hours a year; the unit installed photovoltaic output sequence is the photovoltaic power generation sequence of each grid point for 8760 hours a year; multi-year meteorological data can also be used according to specific needs.

[0108] In the present invention, the optimal inclination angle of the photovoltaic panel at each grid point is the optimal inclination angle of the photovoltaic panel of the nearest county or city obtained based on matching of 4158 grid points.

[0109] The function of step S1 is to use meteorological information and photovoltaic array information to calculate the actual irradiation received by the photovoltaic panels at each grid point at different times and the photovoltaic power generation per unit installed capacity, and generate a photovoltaic power generation sequence per unit installed capacity at each grid point. The photovoltaic power generation sequence per unit installed capacity of each grid point is calculated based on meteorological information to evaluate the natural resource endowment of the transportation network. This step involves dividing a specific geographical area into multiple grid points, obtaining detailed meteorological data and photovoltaic array parameters for each grid point, and then calculating the actual irradiation received and power generation efficiency of the photovoltaic panels based on these data, and finally forming a photovoltaic power generation sequence per unit installed capacity for each grid point that changes over time. This step is crucial for evaluating the potential for transportation energyization, and provides basic data for subsequent steps to calculate the potential capacity and efficiency of photovoltaic power generation in transportation networks.

[0110] The step S2 comprises:

[0111] Obtaining the original OSM road network data and screening and cleaning it to obtain segmented and usable road network data;

[0112] Each section of available road network data includes a plurality of latitude and longitude coordinate pairs arranged in order, and the geodesic distances between adjacent latitude and longitude coordinate pairs are calculated and summed to obtain the total geodesic distance of each section of land road as the available mileage of each section of land road;

[0113] Based on the available mileage of each land section, select the corresponding paving width on both sides of the road for different types of land roads based on the scenario, and multiply the available mileage of each land section by the corresponding paving width on both sides of the road to obtain the photovoltaic paving area of ​​each land section;

[0114] Summarize the photovoltaic paving area of ​​each section of land in each grid point to obtain the potential photovoltaic paving area on the transportation network side of each grid point;

[0115] Based on the potential photovoltaic laying area on the transportation network side of each grid point and the land area for building photovoltaic power stations, the potential photovoltaic installed capacity on the transportation network side is calculated.

[0116] In practical applications, the available mileage, paving area and corresponding potential installed capacity of photovoltaic power generation on the road side of the transportation network are calculated based on OSM road network data and land use index data, including:

[0117] The OSM original road network data includes highway network data and railway network data;

[0118] The available road network data includes the expressway, national highway, provincial highway data in the road network data and the railway data in the railway network;

[0119] The available road network data is a collection of segmented land roads.

[0120] (1) Obtain the original OSM road network data and filter and clean it to obtain usable road network data;

[0121] The original road network data includes all road types of highway network data and railway network data; the original data is cleaned and screened to retain the expressway, national highway, provincial highway data in the highway network data and the railway data in the railway network.

[0122] The available road network data includes the expressways, national roads, provincial roads in the highway network data and the railway data in the railway network. The available road network data is obtained after screening and cleaning the original road network data; the final available road network data is in the form of a collection of segmented land attributes.

[0123] Highway network data is shown in Table 1.

[0124] Table 1: Highway network data fields

[0125] Fields describe Osm_id Unique identifier of the road in the OpenStreetMap database Code Highway type code Fclass Functional categories of roads Name Name of the highway Ref Highway number Oneway One-way road Maxspeed Maximum speed limit on highways Layer The layer or height level where the road is located Bridge Is it a bridge? Tunnel Is it a tunnel? Fclass_cn Chinese functional categories of highways Type Types of roads Coodinates Latitude and longitude coordinates of the highway

[0126] Railway network data is shown in Table 2.

[0127] Table 2: Railway network data fields

[0128]

[0129]

[0130] (2) Calculating the available road network mileage: Calculating the available road network mileage based on the segmented available road network data, wherein the available road network data for each segment of land road includes a plurality of latitude and longitude coordinate pairs arranged in an orderly manner, calculating and summing the geodesic distances between adjacent longitude and latitude coordinate pairs, and obtaining the total geodesic distance of each segment of land road as the available length of the segment of land road; summing up the available lengths of the segmented land roads to obtain the total available land road mileage of each region;

[0131] (3) Calculate the roadside photovoltaic paving area under multiple scenarios. According to the available mileage of the above-mentioned segmented land roads, set the corresponding paving width on both sides of the road for different types of land roads, multiply the available mileage of each section of land road by the corresponding paving width to obtain the paving photovoltaic area of ​​the segmented land road; summarize the paving photovoltaic area of ​​the segmented land roads to obtain the total potential paving area of ​​land roads in each region; the paving width is set based on the road conditions of the scenario.

[0132] (4) Calculate the potential installed capacity of roadside photovoltaic power in each scenario. Based on the available paving area of ​​the above-mentioned segmented land roads, based on the formula Calculate the potential installed capacity of land by segment, where P E Indicates potential installed capacity, unit: megawatt, MW; S E Indicates the actual available area, unit: square meter, m 2 ; S represents the land area of ​​the construction unit megawatt photovoltaic power station, unit: square meters per megawatt, m 2 / MW; By summarizing the potential installed capacity of roadside PV in different land sections, the total potential installed capacity of land-based PV in each region can be obtained.

[0133] The available mileage, paved area and corresponding potential installed capacity of photovoltaic power on the road side of the transportation network are calculated based on OSM road network data and unit installed land area data; the OSM road network data includes highway network data and railway network data; the road network data includes the longitude and latitude coordinate pairs, names, road attributes and other data of segmented land roads.

[0134] The purpose of step 2 is to obtain available road network data by screening and cleaning the original OSM road network data, and then calculate the available mileage and potential photovoltaic paving area of ​​each section of the road network, and finally calculate the potential photovoltaic installed capacity on the road side of the transportation network based on these data. The available mileage and paving area are calculated based on the transportation network data to measure its land resource endowment. This step involves segmenting the road network data, calculating the geodesic distance of each section of the road network to determine the available mileage, estimating the photovoltaic paving area based on the paving width on both sides of the road set for different road types and scenarios, and finally combining the unit installed land area data to calculate the potential photovoltaic installed capacity on the road side of the transportation network in each grid point, providing key spatial and capacity data for evaluating the potential for transportation energy power generation.

[0135] The step S3 comprises:

[0136] According to the coordinates of the grid points and the coordinates of the representative points of each land section, the nearest grid points are matched for the land road representative points in the region;

[0137] For each land representative point r in the region j ∈A, perform the following matching calculation to obtain the nearest grid point g k(j) The index k(j) is as follows:

[0138] k(j)=argmin i∈{1,2,...,n} d[(lat j ,lon j ),(lat i ,lon i )]

[0139] Formula (8)

[0140]

[0141] in, is the set of representative land points in the region; r j is the representative point of the jth land route; n is the number of grid points; (lat i ,lon i ) is the radian longitude and latitude coordinates of the i-th grid point; (lat j ,lon j ) is the latitude and longitude coordinates of the jth land representative point in radians; d[(lat j ,lon j ),(lat i ,lon i )] is the spherical distance between two longitude and latitude coordinate pairs, and R is the approximate radius of the earth;

[0142] Based on the index k(j) of the nearest grid point matched to each land representative point, the unit installed capacity photovoltaic power generation sequence of the nearest grid point is obtained as the photovoltaic power generation potential sequence on the road side of each segmented land road;

[0143] The representative point of each land route segment is the first coordinate pair among the L coordinate pairs of each segmented land route, where L≥1.

[0144] In practical applications, according to the unit installed photovoltaic output sequence of each grid point and the roadside photovoltaic potential installed capacity, the unit installed photovoltaic output sequence corresponding to the nearest grid point is matched for the segmented land road, and the segmented land road side photovoltaic power generation potential sequence is calculated, which specifically includes:

[0145] According to the coordinates of the grid points and the coordinates of the representative points of the segmented land roads, the unit installed photovoltaic output sequence corresponding to the nearest grid point is matched for the land road representative point set in the region; the grid point set is defined as where g i represents the i-th grid point, and n is the total number of grid points;

[0146] The coordinates of the representative point of the segmented land route are defined as the first coordinate pair of L (L≥1) coordinate pairs of each segment of land route; the set of representative points of the land route in the region is defined as m represents the total number of all land representative points, where r j represents the representative point of the jth land route;

[0147] The matched nearest grid point is denoted as g k(j) , where k(j) represents the land point r j The index of the nearest grid point of ;

[0148] The unit installed photovoltaic output sequence of the i-th grid point is recorded as w i (t),t∈T, where T represents the total time size.

[0149] The index k(j) of the nearest grid point of each land section is obtained, and then the unit installed power generation sequence w of the roadside photovoltaic power generation of each land section is obtained. k(j) (t),t∈T.

[0150] According to the unit installed photovoltaic power generation sequence of each grid point and the roadside photovoltaic potential installed capacity, the unit installed photovoltaic power generation sequence corresponding to the nearest grid point is matched for the segmented land road, and the roadside photovoltaic power generation potential sequence of the segmented land road is calculated;

[0151] The function of step S3 is to match each segmented land route with the nearest grid point so that the unit installed photovoltaic power generation sequence of the grid point can be applied to the corresponding land route segment, thereby calculating the photovoltaic power generation potential sequence of each land route segment. This step involves finding the nearest grid point to each land route representative point based on the coordinates of the grid point and the land route representative point, and then using the photovoltaic power generation data of these grid points to estimate the photovoltaic power generation potential of each land route segment. This step is a key step in combining the photovoltaic power generation potential with the actual transportation network, and provides the photovoltaic power generation data of the segmented land route for the subsequent calculation of the transportation energy power generation potential. This step matches the segmented land route in step S2 with the unit installed photovoltaic power generation sequence obtained in step S1, spatially integrates the first two incomplete results, and realizes the integration of the photovoltaic resource network and the transportation network.

[0152] The step S4, specifically.

[0153] In step S3, based on the potential installed capacity of photovoltaic power generation on the road side of each segmented land road in each region and the unit installed capacity power generation potential sequence, the total photovoltaic power generation potential on the road side of the region is calculated as follows:

[0154]

[0155] Among them, W scen,T P is the total power generation potential of roadside photovoltaic power generation in the area within T time under the scenario scen; E,scen,j is the potential installed capacity of roadside photovoltaic power generation for the jth section of land under the scenario ScEN; k(j) (t) is the unit installed photovoltaic output of the roadside photovoltaic power generation of the jth land section at time t; m is the number of land segments in the region.

[0156] The scenario scenarios include conservative laying, general laying, and optimistic laying; the three scenarios correspond to three installation widths.

[0157] According to the segmented roadside photovoltaic power generation potential sequence, the total roadside photovoltaic power generation potential in each region is summarized to complete the transportation energy method power generation potential assessment of each region.

[0158] For the scene scen, different installation widths are selected during the calculation process of different scenes.

[0159] The function of step S4 is to summarize and calculate the roadside photovoltaic power generation potential of all segmented land roads in each region, and to estimate the total photovoltaic power generation potential of the roadside of the land roads in the region by combining the photovoltaic potential installed capacity and the unit installed photovoltaic power generation potential sequence of each segmented land road. This step takes into account the installed capacity width under different paving scenarios (conservative, general, optimistic), thereby providing a specific photovoltaic power generation potential assessment for each scenario, and finally completing a comprehensive assessment of the transportation energy power generation potential of each region.

[0160] In summary, the method for calculating the traffic energy generation potential based on meteorological information in the embodiment of the present invention has the following beneficial effects:

[0161] 1. The present invention provides a refined evaluation method by combining meteorological information and traffic network data, which can more accurately quantify the available power generation potential of traffic energy, thereby improving the accuracy of the energy potential quantification results;

[0162] 2. The present invention adopts a method of dividing by grid points and combines refined meteorological data to provide a more accurate assessment method based on meteorological data, which helps to more accurately assess the energy potential corresponding to different roads;

[0163] 3. By evaluating the energy potential of land transportation, the present invention helps to promote green electricity substitution in typical application scenarios such as roads and railways, and effectively play the role of local reliable substitution of new energy, which is of great significance for achieving the goal;

[0164] 4. By evaluating and quantifying the potential of transportation energy, the present invention helps to optimize the green development of transportation energy, promote energy conservation and emission reduction in the transportation field, have a positive impact on the integrated development of transportation and energy, and optimize the green development of transportation energy.

[0165] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by any technician familiar with the technical field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention.

Claims

1. A method for calculating the power generation potential of transportation energy based on meteorological information, characterized in that: The steps include: Step S1, calculating the unit installed capacity photovoltaic power generation sequence of each grid point based on the meteorological information and photovoltaic array information of the grid point; Step S2: Based on the original road network data of OSM and the unit installed land area, the available mileage and potential photovoltaic paving area of ​​the transportation network side of each grid point are calculated, and then the potential photovoltaic installed capacity of the transportation network side is obtained; Step S3, based on the unit installed photovoltaic power generation sequence of each grid point and the potential photovoltaic installed capacity on the transportation network side, matching the unit installed photovoltaic power generation sequence corresponding to the nearest grid point for the segmented land road, and calculating the photovoltaic power generation potential sequence on the side of the segmented land road; Step S4, summarizing and calculating the photovoltaic power generation potential sequence of each segmented land road side of each area within the range to be measured, and obtaining the total photovoltaic power generation potential of the land road side of each area; Wherein, a region includes one or more grid points.

2. The method according to claim 1, characterized in that: The step S1 comprises: Divide the range to be measured into multiple grid points according to a predetermined spatial resolution; Obtain meteorological information and photovoltaic array information for each grid point; Based on the meteorological information of each grid point, the actual irradiance received by the photovoltaic panel at each grid point at time t is calculated as follows: TAKE NOTE t =DHI t +DNI t ×cosθ Z,t F t =1-(DHI t ÷GHI t , 2 Among them, GHI t 、DNI t , DHI t are the global downward irradiance, direct irradiance component and diffuse irradiance component at time t respectively; θ Z,t is the solar zenith angle at time t; GTI t is the actual amount of radiation received by the photovoltaic panel at time t; β t 、f albedo,t are the photovoltaic array inclination angle and the surface albedo at time t; M t is the scattered radiation component coefficient at time t; F t is the intermediate variable; α t is the plane incident angle of the photovoltaic panel at time t; The irradiance actually received by the photovoltaic panel at each grid point is sorted in time to form a sequence of irradiance actually received by the photovoltaic panel; Based on the actual irradiation received by the photovoltaic panels at each grid point at time t, the unit installed photovoltaic power generation P at each grid point at time t is calculated. pvt,t ,as follows: Among them, f pv is the photovoltaic derating factor; I0 is the irradiance under the standard test environment; α p is the power temperature coefficient of the photovoltaic panel assembly; T0 is the temperature of the photovoltaic panel assembly under the standard test environment; T t is the actual temperature of the photovoltaic panel assembly; The unit installed photovoltaic power generation of each grid point is arranged in time to form a unit installed photovoltaic power generation sequence.

3. The method according to claim 1, characterized in that: The step S2 comprises: Obtaining the original OSM road network data and screening and cleaning it to obtain segmented and usable road network data; Each section of available road network data includes a plurality of latitude and longitude coordinate pairs arranged in order, and the geodesic distances between adjacent latitude and longitude coordinate pairs are calculated and summed to obtain the total geodesic distance of each section of land road as the available mileage of each section of land road; Based on the available mileage of each land section, select the corresponding paving width on both sides of the road for different types of land roads based on the scenario, and multiply the available mileage of each land section by the corresponding paving width on both sides of the road to obtain the photovoltaic paving area of ​​each land section; Summarize the photovoltaic paving area of ​​each section of land in each grid point to obtain the potential photovoltaic paving area on the transportation network side of each grid point; Based on the potential photovoltaic laying area on the transportation network side of each grid point and the land area for building photovoltaic power stations, the potential photovoltaic installed capacity on the transportation network side is calculated.

4. The method according to claim 3, characterized in that: The step S3 comprises: According to the coordinates of the grid points and the coordinates of the representative points of each land section, the nearest grid points are matched for the land road representative points in the region; For each land representative point r in the region j ∈A, perform the following matching calculation to obtain the nearest grid point g k(j) The index k(j) of: k(j)=argmin i∈{1,2,...,n} d[(years j ,lon j ),(years i ,lon i )] in, is the set of representative land points in the region; r j is the representative point of the jth land route; n is the number of grid points; (lat i ,lon i ) is the radian longitude and latitude coordinates of the i-th grid point; (lat j ,lon j ) is the latitude and longitude coordinates of the jth land representative point in radians; d[(lat j ,lon j ),(lat i ,lon i )] is the spherical distance between two longitude and latitude coordinate pairs, and R is the approximate radius of the earth; Based on the index k(j) of the nearest grid point matched to each land representative point, the unit installed capacity photovoltaic power generation sequence of the nearest grid point is obtained as the photovoltaic power generation potential sequence on the road side of each segmented land road; The representative point of each land route segment is the first coordinate pair among the L coordinate pairs of each segmented land route, where L≥1.

5. The method according to claim 4, characterized in that: In step S4, based on the potential installed capacity of photovoltaic power generation on the road side of each segment of the land in each region and the unit installed capacity power generation potential sequence, the total photovoltaic power generation potential on the road side of the land in the region is calculated as follows: Among them, W scen,T P is the total power generation potential of roadside photovoltaic power generation in the area within T time under the scenario scen; E,scen,j is the potential installed capacity of roadside photovoltaic power generation for the jth section of land under the scenario ScEN; k(j) (t) is the unit installed photovoltaic output of the roadside photovoltaic power generation of the jth land section at time t; m is the number of land segments in the region.

6. The method according to claim 2, characterized in that: The actual temperature T of the photovoltaic panel assembly t , calculated as follows: Among them, T a is the external environment temperature.

7. The method according to claim 2, characterized in that: The plane incident angle α of the photovoltaic panel at time t t , calculated as follows: a t =arccos[cosβ t ×cosθ Z,t +sinβ t ×sinθ Z,t ×cos(θ A,t -l t )] Among them, θ A,t is the solar azimuth at time t; t is the azimuth angle of the photovoltaic array at time t.

8. The method according to claim 3, characterized in that: The OSM original road network data includes highway network data and railway network data; The available road network data includes the expressway, national highway, provincial highway data in the road network data and the railway data in the railway network; The available road network data is a collection of segmented land roads.

9. The method according to claim 5, characterized in that: The scenario scenarios include conservative laying, general laying, and optimistic laying; the three scenarios correspond to three installation widths.

10. The method according to any one of claims 1 to 9, characterized in that: The meteorological information includes weather data and sun position information; The weather data includes radiation, surface albedo and external ambient temperature; wherein the radiation includes direct radiation component and scattered radiation component; The solar position information includes the solar zenith angle and the solar azimuth angle. The photovoltaic array information includes a photovoltaic panel tracking method and an optimal inclination angle of the photovoltaic panel at each grid point.

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