Calculation Method for Traffic Energy Generation Potential Based on Meteorological Information

Abstract

The present invention relates to a method for calculating the traffic energy-based power generation potential, belonging to the field of quantifying traffic energy potential, and solves the problem of low accuracy of the quantification result of the available power generation potential for traffic energy conversion. It includes calculating the photovoltaic power generation sequence per unit installed capacity of each grid point based on the meteorological information and photovoltaic array information of the grid points; calculating the available photovoltaic mileage and potential photovoltaic laying area on the traffic network side of each grid point based on the OSM original road network data and the land area per unit installed capacity, and then obtaining the potential installed capacity of photovoltaic on the traffic network side; based on the photovoltaic power generation sequence per unit installed capacity of each grid point and the potential installed capacity of photovoltaic on the traffic network side, matching the photovoltaic power generation sequence per unit installed capacity corresponding to the nearest grid point for each segmented land route, and calculating the photovoltaic power generation potential sequence on the side of the segmented land route; summarizing and calculating the photovoltaic power generation potential sequences on the side of each segmented land route within each region in the range to be measured, and obtaining the total photovoltaic power generation potential on the side of the land route within each region.

Description

Technical Field

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

[0002] Energy conservation and emission reduction in the transportation field is one of the keys to the transformation and upgrading of the industry. The energy and transportation sectors account for the highest proportions in China's carbon emissions, 43% and 26% respectively. Energy conservation and emission reduction in the transportation field has become one of the key parts of the industry's transformation and upgrading. In the end-use energy consumption structure, transportation energy accounts for about 17%. In the carbon emission structure, transportation accounts for about 10.4%. In the transportation energy structure, the proportion of electricity is less than 5%, and the proportion of green electricity is less than 2%. Promoting the replacement of green electric energy in typical application scenarios such as highways, ports, and railways can effectively play the role of reliable local replacement of new energy. Therefore, evaluating the potential of land transportation energy conversion is of great significance for the integrated development of transportation and energy and the green development of transportation energy in China.

[0003] Most of the existing technologies regarding traffic energy conversion focus on electric vehicles on the load side as the entry point of the transportation network, lacking consideration of the synergistic effect on 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 potential of the natural endowment of the transportation system adopt the method of dividing by resource areas, lacking an evaluation method that takes into account the refined meteorological data corresponding to different roads. In addition, most of the existing technologies focus on the analysis of the energy supply potential of renewable energy at daily, monthly, and annual time resolutions. However, the hourly volatility and uncertainty of new energy require the configuration of corresponding hourly energy storage systems. The existing technologies cannot further carry out the matching analysis of the source and load at a more accurate time scale, thus affecting the accurate analysis and optimization of the power system. Summary of the Invention

[0004] In view of the above analysis, the embodiments of the present invention aim to provide a method for calculating the power generation potential of traffic energy conversion based on meteorological information to solve the technical problem of low accuracy of the quantification results of the available power generation potential of traffic energy conversion in the existing methods.

[0005] The object 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 traffic energy conversion based on meteorological information, including the following steps:

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

[0008] Step S2: Based on the OSM original road network data and the unit installed area, calculate the available mileage of photovoltaic power on the traffic network side and the potential photovoltaic laying area at each grid point, and then obtain the potential installed capacity of photovoltaic power on the traffic network side;

[0009] Step S3: Based on the unit installed photovoltaic power generation sequence at each grid point and the potential installed capacity of photovoltaic power on the traffic network side, match the unit installed photovoltaic power generation sequence corresponding to the nearest grid point for the segmented land route, and calculate the photovoltaic power generation potential sequence on the side of the segmented land route;

[0010] Step S4: Aggregate and calculate the photovoltaic power generation potential sequence on the side of each segmented land route in each area within the range to be measured, and obtain the total photovoltaic power generation potential on the side of the land route within each area;

[0011] Among them, one area includes one or more grid points.

[0012] Further, the step S1 includes:

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

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

[0015] Based on the meteorological information of each grid point, calculate the irradiance actually received by the photovoltaic panel at time t for each grid point, and the calculation is 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 irradiance actually received by the photovoltaic panel at time t; β t 、f albedo,t are the photovoltaic array tilt angle and surface albedo at time t respectively; M t is the diffuse irradiance component coefficient at time t; F t is an 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 by time to form a sequence of the irradiance actually received by the photovoltaic panel.

[0021] Based on the irradiance actually received by the photovoltaic panel at each grid point at time t, calculate the installed photovoltaic power generation P at each grid point at time t pvt,t , as follows:

[0022]

[0023] where 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 module; T0 is the temperature of the photovoltaic panel module under the standard test environment; T t is the actual temperature of the photovoltaic panel module;

[0024] The installed photovoltaic power generation at each grid point is sorted by time to form a sequence of installed photovoltaic power generation.

[0025] Further, the step S2 includes:

[0026] Obtain the original OSM road network data and perform screening and cleaning to obtain segmented available road network data;

[0027] Each segment of available road network data includes a plurality of longitude and latitude coordinate pairs arranged in order. Calculate the geodesic distance between adjacent longitude and latitude coordinate pairs and sum them to obtain the total geodesic distance of each segment of land route as the available mileage of each segment of land route;

[0028] Based on the available mileage of each segment of land route, select the corresponding laying width on both sides of the road for different categories of land routes according to the scenario, and multiply the available mileage of each segment of land route by the corresponding laying width on both sides of the road to obtain the photovoltaic installable area of each segment of land route;

[0029] Summarize the photovoltaic installable areas of each segment of land route in each grid point to obtain the photovoltaic potential installable area on the traffic network side of each grid point;

[0030] Based on the photovoltaic potential installable area on the traffic network side of each grid point and the land area for building a photovoltaic power station, calculate the photovoltaic potential installed capacity on the traffic network side.

[0031] Further, the step S3 includes:

[0032] According to the coordinates of the grid point and the coordinates of the representative point of each segment of land route, match the nearest grid point for the set of representative points of land routes in the region;

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

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

[0035]

[0036] where is the set of overland representative points within the area; r j is the representative point of the j-th overland segment; n is the number of grid points; (lat i , lon i ) is the radian-based longitude and latitude coordinates of the i-th grid point; (lat j , lon j ) is the radian-based longitude and latitude coordinates of the j-th overland representative point; d[(lat j , lon j ), (lat i , lon i )] is the spherical distance between two pairs of longitude and latitude coordinates, and R is the approximate radius of the Earth;

[0037] Based on the index k(j) of the nearest grid point matched for each overland representative point, obtain the unit installed photovoltaic power generation sequence of the nearest grid point as the photovoltaic power generation potential sequence on the roadside of each segmented overland route;

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

[0039] Furthermore, in step S4, based on the photovoltaic potential installed capacity and the unit installed power generation potential sequence on the roadside of each segmented overland route in each area, calculate the total photovoltaic power generation potential on the roadside of overland routes within the area as follows:

[0040]

[0041] where W scen,T is the total photovoltaic power generation potential on the roadside of overland routes within the area under scenario scen at time T; P E,scen,j is the photovoltaic potential installed capacity on the roadside of the j-th overland segment under scenario scen; w k(j) (t) is the unit installed photovoltaic power output on the roadside of the j-th overland segment at time t; and m is the number of overland segments within the area.

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

[0043]

[0044] where T a is the ambient temperature.

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

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

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

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

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

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

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

[0052] Furthermore, the meteorological information includes weather data and solar position information;

[0053] The weather data includes irradiance, surface albedo, and ambient temperature; among them, the irradiance includes direct irradiance component and diffuse irradiance component;

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

[0055] The photovoltaic array information includes the photovoltaic panel tracking method and the 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 conversion, thereby improving the accuracy of the quantification results of energy conversion potential.

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

[0059] 3. By evaluating the energy conversion potential of land transportation, the present invention helps to promote the replacement of green electric energy in typical application scenarios such as highways and railways, effectively play the role of reliable local replacement of new energy, and is of great significance for achieving the dual-carbon goal.

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

[0061] In the present invention, the above technical solutions can also be combined with each other to achieve more preferred combination schemes. Other features and advantages of the present invention will be described in the subsequent specification, and some advantages can be made obvious from the specification or understood by implementing the present invention. The objectives and other advantages of the present invention can be realized and obtained from the content specifically pointed out in the specification and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] The drawings are only for the purpose of showing specific embodiments and are not considered as limiting the present invention. Throughout the drawings, the same reference signs represent the same components.

[0063] Figure 1 It is a flowchart of the calculation method for the power generation potential of traffic energy conversion based on meteorological information in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0064] The following will specifically describe the preferred embodiments of the present invention in conjunction with the drawings, where the drawings form a part of this application and are used together with the embodiments of the present invention to explain the principles of the present invention, rather than to limit the scope of the present invention.

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

[0066] A specific embodiment of the present invention, as Figure 1 shown, discloses a calculation method for the power generation potential of traffic energy conversion based on meteorological information, including the following steps:

[0067] Step S1: Calculate the photovoltaic power generation sequence per unit installed capacity of each grid point based on the meteorological information and photovoltaic array information of the grid points.

[0068] Step S2: Calculate the available mileage of photovoltaic power generation on the traffic network side and the potential photovoltaic laying area of each grid point based on the OSM (Open Street Map) original road network data and the land area per unit installed capacity, and then obtain the potential installed capacity of photovoltaic power generation on the traffic network side.

[0069] Step S3: Based on the photovoltaic power generation sequence per unit installed capacity of each grid point and the potential installed capacity of photovoltaic power generation on the traffic network side, match the photovoltaic power generation sequence per unit installed capacity corresponding to the nearest grid point for the segmented land route, and calculate the photovoltaic power generation potential sequence on the side of the segmented land route.

[0070] Step S4: Aggregate and calculate the photovoltaic power generation potential sequences on the sides of each segmented land route in each area within the range to be measured, and obtain the total photovoltaic power generation potential on the sides of the land routes within each area.

[0071] Among them, one area includes one or more grid points.

[0072] The said Step S1 includes:

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

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

[0075] Based on the meteorological information of each grid point, calculate the irradiance actually received by the photovoltaic panel at time t of each grid point, and the calculation is 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 irradiance actually received by the photovoltaic panel at time t; β t , f albedo,t are the tilt angle of the photovoltaic array and the surface albedo at time t respectively; M t is the diffuse irradiance component coefficient at time t; F t is an intermediate variable; α t is the plane incidence angle of the photovoltaic panel at time t;

[0081] The irradiance actually received by the photovoltaic panel at each grid point is sorted by time to form an irradiance sequence actually received by the photovoltaic panel.

[0082] Based on the irradiance actually received by the photovoltaic panel at each grid point at time t, calculate the installed photovoltaic power generation P at each grid point at time t pvt,t , as follows:

[0083]

[0084] where, 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 module; T0 is the temperature of the photovoltaic panel module under the standard test environment; T t is the actual temperature of the photovoltaic panel module;

[0085] The installed photovoltaic power generation at each grid point is sorted by time to form an installed photovoltaic power generation sequence.

[0086] where, F t is an intermediate variable used for calculation convenience and has no special physical meaning.

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

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

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

[0090]

[0091] where, T a is the ambient temperature.

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

[0093] T a is the ambient temperature (temperature data per hour); T0 is the temperature of the photovoltaic module in the standard test environment.

[0094] The plane incident angle α of the photovoltaic panel at time t t , is 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] where θ A,t is the solar azimuth angle at time t; λ t is the azimuth angle of the photovoltaic array at time t.

[0098] Each area within the range to be measured and calculated is divided into multiple grid points according to a predetermined spatial resolution; exemplarily, within the whole country, with a predetermined spatial distribution rate of 0.5°×0.5°, 4158 grid points evenly distributed throughout the country.

[0099] A grid point refers to dividing the whole 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 distribution rate of 0.5°×0.5°, and the predetermined spatial resolution can be selected according to specific requirements.

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

[0101] The weather data includes irradiance, surface albedo, and ambient temperature; among them, the irradiance includes direct irradiance component and diffuse irradiance component;

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

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

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

[0105] The meteorological information is from the NASA POWER project platform, which is an open-source platform and the data can be downloaded independently.

[0106] The optimal inclination angle of the photovoltaic panel is the optimal inclination angle corresponding to each county or city downloaded (generally, based on historical data, the inclination angle with the largest received irradiance calculated is the optimal inclination angle). There is no strict regulation in the present invention on what the specific degree of the optimal inclination angle must be, so each place can adjust it according to its own needs.

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

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

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

[0110] The said step S2 includes:

[0111] Obtain the original OSM road network data and perform screening and cleaning to obtain segmented available road network data;

[0112] Each segment of available road network data includes a plurality of ordered longitude and latitude coordinate pairs. Calculate the geodesic distance between adjacent longitude and latitude coordinate pairs and sum them up to obtain the total geodesic distance of each segment of land route as the available mileage of each segment of land route;

[0113] Based on the available mileage of each segment of land route, select the corresponding laying width on both sides of the road for different categories of land routes according to the scenario, and multiply the available mileage of each segment of land route by the corresponding laying width on both sides of the road to obtain the photovoltaic installable area of each segment of land route;

[0114] Summarize the photovoltaic installable area of each section of land route at each grid point to obtain the photovoltaic potential installable area on the transportation network side of each grid point;

[0115] Based on the photovoltaic potential installable area on the transportation network side of each grid point and the land area for building a photovoltaic power station, calculate the photovoltaic potential installed capacity on the transportation network side.

[0116] In practical applications, calculate the available mileage, installable area and corresponding potential installed capacity of photovoltaic on the transportation network side based on OSM road network data and land use index data, specifically including:

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

[0118] The available road network data includes highway data (expressways, national highways, provincial highways) in the highway network data and railway data in the railway network;

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

[0120] (1) Obtain the original OSM road network data, screen and clean it to obtain the available road network data;

[0121] The original road network data includes all road types of highway network data and railway network data; clean and screen the original data, and retain highway data (expressways, national highways, provincial highways) in the highway network data and railway data in the railway network.

[0122] The content of the available road network data includes highway data (expressways, national highways, provincial highways) in the highway network data and railway data in the railway network. The available road network data is obtained by screening and cleaning the original road network data; the finally obtained available road network data form is a collection of segmented land route attributes.

[0123] The highway network data is shown in Table 1.

[0124] Table 1: Highway road network data fields

[0125] Field Description Osm_id Unique identifier of the road in the OpenStreetMap database Code Code of the road type Fclass Functional class of the road Name Name of the road Ref Number of the road Oneway One-way attribute of the road Maxspeed Maximum speed limit of the road Layer Layer or altitude level where the road is located Bridge Whether it is a bridge Tunnel Whether it is a tunnel Fclass_cn Chinese functional class of the road Type Type of the road Coodinates Latitude and longitude coordinates of the road

[0126] The railway network data is shown in Table 2.

[0127] Table 2: Railway road network data fields

[0128]

[0129]

[0130] (2) Calculate the available road network mileage; calculate the available road network mileage based on the above segmented available road network data. Each piece of land-based available road network data includes multiple ordered longitude and latitude coordinate pairs. Calculate the geodesic distance between adjacent longitude and latitude coordinate pairs and sum them up to obtain the total geodesic distance of each piece of land as the available length of that piece of land; summarize the available lengths of the segmented land-based roads to obtain the total land-based available mileage of each region.

[0131] (3) Calculate the available area for roadside PV installation under multiple scenarios. Based on the above segmented land-based available mileage, set corresponding laying widths on both sides of different types of land-based roads. Multiply each piece of land-based available mileage by the corresponding laying width to obtain the available PV installation area for each segmented land-based road; summarize the available PV installation areas of the segmented land-based roads to obtain the total potential land-based PV installation area of each region; the laying width is set based on the road conditions of the scenario.

[0132] (4) Calculate the potential installed capacity of roadside PV under each scenario. Based on the above segmented available installation area of land-based roads, calculate the potential installed capacity of segmented land-based roads based on the formula where P E represents the potential installed capacity, unit: megawatt, MW; S E represents the actual available area, unit: square meter, m 2 ; S represents the land area required for building a one-megawatt PV power station per construction unit, unit: square meter per megawatt, m 2 / MW; summarize the potential installed capacity of roadside PV for segmented land-based roads to obtain the total potential installed capacity of land-based PV in each region.

[0133] Calculate the available mileage, available installation area and corresponding potential installed capacity of roadside PV on the transportation network based on OSM road network data and unit installed capacity land area data; the OSM road network data includes highway network data and railway network data; the road network data contains data such as longitude and latitude coordinate pairs, names, and road attributes of segmented land-based roads.

[0134] The function of step 2 is to screen and clean the original OSM road network data to obtain available road network data, then calculate the available mileage and potential PV installation area of each section of the road network, and finally calculate the potential installed capacity of roadside PV on the transportation network based on these data. Calculate the available mileage and installation area 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 available PV installation area based on the laying widths on both sides of different road types and scenarios, and finally combining the unit installed capacity land area data to calculate the potential installed capacity of roadside PV in each grid point, providing key spatial and capacity data for evaluating the potential of transportation energy generation.

[0135] The said step S3 includes:

[0136] Match the nearest grid points for the set of land route representative points in the region according to the coordinates of the grid points and the coordinates of the representative points of each land route segment;

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

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

[0139] Formula (8)

[0140]

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

[0142] Based on the index k(j) of the nearest grid point matched for each land route representative point, obtain the unit installed photovoltaic power generation sequence of the nearest grid point as the photovoltaic power generation potential sequence on the side of each segmented land route;

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

[0144] In practical applications, according to the unit installed photovoltaic power output sequence of each grid point and the potential installed capacity of the roadside photovoltaic, match the unit installed photovoltaic power output sequence corresponding to the nearest grid point for the segmented land route, and calculate the photovoltaic power generation potential sequence on the side of the segmented land route, specifically including:

[0145] Match the unit installed photovoltaic power output sequence corresponding to the nearest grid point for the set of land route representative points in the region according to the coordinates of the grid points and the coordinates of the representative points of the segmented land route; 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 segmented overland representative points are defined as the first coordinate pair among the L (L≥1) coordinate pairs of each overland segment; the set of overland representative points within the region is defined as m represents the total number of all overland representative points, where r j represents the representative point of the j-th overland segment;

[0147] The closest grid point found is denoted as g k(j) , where k(j) represents the index of the closest grid point to the overland point r j ;

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

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

[0150] According to the unit installed photovoltaic power generation sequences of each grid point and the potential installed capacity of the roadside photovoltaic, match the unit installed photovoltaic power generation sequence corresponding to the closest grid point for the segmented overland, and calculate the potential power generation sequence of the roadside photovoltaic for the segmented overland;

[0151] The function of step S3 is to match each segmented overland with the closest grid point, so as to apply the unit installed photovoltaic power generation sequence of the grid point to the corresponding overland segment, thereby calculating the potential power generation sequence of the photovoltaic for each overland segment. This step involves finding the closest grid point to each overland representative point based on the coordinates of the grid point and the overland representative point, and then using the photovoltaic power generation data of these grid points to estimate the potential power generation of the photovoltaic for each overland segment. This step is a key step in combining the photovoltaic power generation potential with the actual transportation network, providing the photovoltaic power generation data of the segmented overland for the subsequent calculation of the potential power generation of the transportation energy conversion. This step matches the segmented overland in step S2 with the unit installed photovoltaic power generation sequence obtained in step S1, fusing the results of the previous two steps in space to achieve the integration of the photovoltaic resource network and the transportation network.

[0152] Specifically for step S4.

[0153] In step S3, based on the potential installed capacity of the roadside photovoltaic and the unit installed power generation potential sequence for each segmented overland within each region, calculate the total potential power generation of the roadside photovoltaic within the region, and the calculation is as follows:

[0154]

[0155] Among them, W scen,T is the total potential of roadside photovoltaic power generation on land roads within the area under scenario scen within time T; P E,scen,j is the potential installed capacity of roadside photovoltaic on the j-th land road under scenario scen; w k(j) (t) is the unit installed photovoltaic power output of the roadside photovoltaic on the j-th land road at time t; m is the number of segments of land roads within the area.

[0156] The scenario scen includes three scenarios: conservative laying, general laying, and optimistic laying; the three scenarios correspond to three installed widths.

[0157] Summarize the total potential of roadside photovoltaic power generation on land roads in each area according to the sequence of photovoltaic power generation potential on the segmented land roads, and complete the evaluation of the power generation potential of traffic energy in each area.

[0158] For scenario scen, different installed widths are selected during the calculation of different scenarios.

[0159] The function of step S4 is to summarize and calculate the potential of roadside photovoltaic power generation on all segmented land roads in each area. By combining the potential installed capacity of photovoltaic on each segmented land road and the sequence of unit installed photovoltaic power generation potential, the total potential of roadside photovoltaic power generation on land roads in the area is estimated. This step considers the installed widths under different laying scenarios (conservative, general, optimistic), so as to provide a specific evaluation of the photovoltaic power generation potential for each scenario, and finally complete the comprehensive evaluation of the power generation potential of traffic energy in each area.

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

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

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

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

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

[0165] As described above, the above are only the preferred specific embodiments 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 those skilled in the art within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention.

Claims

1. A calculation method for the potential of traffic energy-based power generation based on meteorological information, characterized in that, It includes the following steps: Step S1: Calculate the photovoltaic power generation sequence per unit installed capacity of each grid point based on the meteorological information and photovoltaic array information of the grid points; Step S2: Calculate the available mileage of photovoltaic power generation on the traffic network side and the potential photovoltaic laying area of each grid point based on the OSM original road network data and the land area per unit installed capacity, and then obtain the potential installed capacity of photovoltaic power generation on the traffic network side; Step S3: Based on the photovoltaic power generation sequence per unit installed capacity of each grid point and the potential installed capacity of photovoltaic power generation on the traffic network side, match the photovoltaic power generation sequence per unit installed capacity corresponding to the nearest grid point for the segmented land route, and calculate the photovoltaic power generation potential sequence on the side of the segmented land route; Step S4: Aggregate and calculate the photovoltaic power generation potential sequences on the sides of each segmented land route in each area within the range to be measured, and obtain the total photovoltaic power generation potential on the land route side within each area; Wherein, one area includes one or more grid points; The step S1 includes: Divide the range to be measured into multiple grid points according to a predetermined spatial resolution; Obtain the meteorological information and photovoltaic array information of each grid point; Based on the meteorological information of each grid point, calculate each grid point The actual irradiance received by the photovoltaic panel at the moment is calculated as follows: ； ； ； ； Among them, , , are respectively the global downward irradiance, direct irradiance component and diffuse irradiance component at time is the solar zenith angle at time is the irradiance actually received by the photovoltaic panel at time , are respectively the inclination angle of the photovoltaic array and the surface albedo at time is the diffuse irradiance component coefficient at time is an intermediate variable; is the plane incidence angle of the photovoltaic panel at time The irradiation amounts actually received by the photovoltaic panels at each grid point are sorted by time to form a sequence of irradiation amounts actually received by the photovoltaic panels; Based on the actual irradiance received by the photovoltaic panels at each grid point at a certain moment, calculate the installed capacity of photovoltaic power generation per unit at a certain moment as follows: ； Among them, is the photovoltaic derating factor; is the irradiance under the standard test environment; is the power temperature coefficient of the photovoltaic panel module; is the temperature of the photovoltaic panel module under the standard test environment; is the actual temperature of the photovoltaic panel module; The photovoltaic power generation per unit installed capacity at each grid point is sorted by time to form a photovoltaic power generation sequence per unit installed capacity.

2. The method according to claim 1, characterized in that, The step S2 includes: Obtain the OSM original road network data and perform screening and cleaning to obtain segmented available road network data; Each segment of available road network data includes a plurality of ordered longitude and latitude coordinate pairs. Calculate the geodesic distance between adjacent longitude and latitude coordinate pairs and sum them up to obtain the total geodesic distance of each land route as the available mileage of each land route; Based on the available mileage of each land route, select the corresponding laying width on both sides of the road for different categories of land routes according to the scenario, and multiply the available mileage of each land route by the corresponding laying width on both sides of the road to obtain the photovoltaic laying area of each land route; Aggregate the photovoltaic laying areas of each land route in each grid point to obtain the potential photovoltaic laying area on the traffic network side of each grid point; Based on the potential photovoltaic laying area on the traffic network side of each grid point and the land area for building a photovoltaic power station, calculate the potential installed capacity of photovoltaic power generation on the traffic network side.

3. The method according to claim 2, wherein The step S3 includes: Match the nearest grid point for the set of representative points of land routes within the area according to the coordinates of the grid points and the coordinates of the representative points of each land route; For each overland representative point within the area , perform the following matching calculation to obtain the index of the nearest grid point : ； ； Among them, is the set of overland representative points in the region; is the representative point of the th overland segment; is the number of grid points; is the radian-based longitude and latitude coordinates of the th grid point; is the radian-based longitude and latitude coordinates of the th overland representative point; is the spherical distance between two pairs of longitude and latitude coordinates, is the approximate radius of the Earth; Indices of the nearest grid points matched for each overland representative point , the installed capacity per unit of the nearest grid points is obtained as the photovoltaic power generation sequence for each segmented overland roadside, serving as the photovoltaic power generation potential sequence for each segmented overland roadside. Among them, the representative point of each overland section is the first coordinate pair among the coordinate pairs of each segmented overland section, .

4. The method according to claim 3, wherein In step S4, based on the potential installed capacity of photovoltaic power generation and the photovoltaic power generation potential sequence per unit installed capacity on the side of each segmented land route in each area, calculate the total photovoltaic power generation potential on the land route side within the area, and the calculation is as follows: ； Among them, is the total potential of roadside photovoltaic power generation on land in the area under the scenario within a certain time; is the potential installed capacity of roadside photovoltaic on the th section of land road under the scenario; is the unit installed photovoltaic output of the roadside photovoltaic on the th section of land road at the moment; is the number of land road segments in the area.

5. The method according to claim 1, characterized in that, The actual temperature of the photovoltaic panel assembly , is calculated as follows: ； Among them, is the external environmental temperature.

6. The method according to claim 1, wherein The plane incident angle of the photovoltaic panel at a given moment is calculated as follows: ； Among them, is the solar azimuth angle at a certain moment; is the azimuth angle of the photovoltaic array at a certain moment.

7. The method according to claim 2, wherein The OSM original road network data includes highway network data and railway network data; The available road network data includes highway data such as expressways, national highways, and provincial highways in the highway network data and railway data in the railway network; The available road network data is a set of segmented land routes.

8. The method according to claim 4, characterized in that, The described scenario includes three scenarios: conservative laying, general laying, and optimistic laying; the three scenarios correspond to three installation widths.

9. The method according to any one of claims 1-8, characterized in that The meteorological information includes weather data and solar position information; The weather data includes irradiation amount, surface albedo, and ambient temperature; wherein, the irradiation amount includes direct irradiation component and diffuse irradiation component; The solar position information includes solar zenith angle and solar azimuth angle; The photovoltaic array information includes the tracking method of the photovoltaic panels and the optimal inclination angles of the photovoltaic panels at each grid point.

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