A management method and device for photovoltaic power generation in highway service areas

Abstract

The present invention provides a method and device for managing the photovoltaic power generation amount in a highway service area. The method includes: obtaining the power amount Qg generated by the photovoltaic modules corresponding to the target highway service area in each unit time period within a first preset time period; obtaining the vehicle information entering the target highway service area in each unit time period within the first preset time period, and obtaining the power amount Qc required by the target highway service area in each unit time period based on the obtained vehicle information; for the s-th unit time period, if Qgs > Qcs corresponding to this unit time period, the remaining power amount is stored, and if Qgs < Qcs, the power amount Qd is provided to obtain the available power amount corresponding to the s-th unit time period; obtaining the maximum value among the available power amounts within the first preset time period as the reference power amount, and obtaining the capacity of the storage battery based on the reference power amount. The present invention can reasonably manage the photovoltaic power generation amount.

Description

Technical Field

[0001] The present invention relates to the technical field of electric power, and particularly to a method and device for managing the photovoltaic power generation amount in highway service areas. Background Art

[0002] With the strong advocacy of clean energy, electric vehicles have been widely popularized. With the continuous improvement of the battery endurance of electric vehicles, more and more electric vehicles are driving on highways. This places higher requirements on the power supply capacity of highway service areas. As an important renewable new energy, solar energy has become the focus of the application of clean energy. As the core part of the solar power generation system, photovoltaic modules have been widely applied. However, the current layout of photovoltaic modules basically depends on experience, which may lead to unreasonable layout of photovoltaic modules. In addition, the management of photovoltaic power generation amount has not been effectively managed. Summary of the Invention

[0003] In view of the above technical problems, the technical solution adopted by the present invention is as follows:

[0004] According to a first aspect of the present invention, there is provided a method for managing the photovoltaic power generation amount in a highway service area, the method including the following steps:

[0005] S200, obtaining the power generation amount Qg generated by the photovoltaic modules corresponding to the target highway service area in each unit time period within a first preset time period.

[0006] S210, obtaining the vehicle information entering the target highway service area in each unit time period within the first preset time period, and obtaining the required power amount Qc of the target highway service area in each unit time period based on the obtained vehicle information; the vehicle information includes the traffic flow and the number of electric vehicles.

[0007] S220, for the s-th unit time period, if the Qg corresponding to this unit time period s > Qc s , then storing the remaining power amount Qr = (Qg s - Qc s ), if Qg s < Qc s , then providing the power amount Qd = (Qc s - Qg s ), to obtain the available power amount corresponding to the s-th unit time period; wherein, the stored power amount is equal to Qr × α s , α sα is the storage decay coefficient corresponding to the s-th unit time period, where s ranges from 1 to N, and N is the number of unit time periods; the available power in the current unit time period is equal to the available power corresponding to the previous unit time period plus the power stored in the current unit time period or minus the power provided in the current unit time period.

[0008] S230. Obtain the maximum value of the available power within the first preset time period as the reference power, and obtain the capacity of the storage battery based on the reference power.

[0009] According to the second aspect of the present invention, there is provided a management device for photovoltaic power generation in a highway service area, the device including:

[0010] A first acquisition module, configured to acquire the power Qg generated by the photovoltaic modules corresponding to the target highway service area in each unit time period within the first preset time period.

[0011] A second acquisition module, configured to acquire vehicle information entering the target highway service area in each unit time period within the first preset time period, and acquire the power Qc required by the target highway service area in each unit time period based on the acquired vehicle information; the vehicle information includes traffic flow and the number of electric vehicles.

[0012] A processing module, for the s-th unit time period, if the Qg corresponding to this unit time period s > Qc s , then store the remaining power Qr = (Qg s - Qc s ), if Qg s < Qc s , then provide the power Qd = (Qc s - Qg s ), to obtain the available power corresponding to the s-th unit time period; where the stored power is equal to Qr × α s , α s is the storage decay coefficient corresponding to the s-th unit time period, s ranges from 1 to N, and N is the number of unit time periods; the available power in the current unit time period is equal to the available power corresponding to the previous unit time period plus the power stored in the current unit time period or minus the power provided in the current unit time period.

[0013] A third acquisition module, configured to acquire the maximum value of the available power within the first preset time period as the reference power, and acquire the capacity of the storage battery based on the reference power.

[0014] The present invention has at least the following beneficial effects:

[0015] The management method for the photovoltaic power generation amount in highway service areas provided by the embodiments of the present invention determines the capacity of the storage batteries to be arranged based on the power generation amount of the photovoltaic modules in the highway service areas within a set time period and the power amount required by the service areas within the set time period, so as to be able to reasonably manage the photovoltaic power generation amount in the highway service areas.

[0016] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. Brief Description of the Drawings

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0018] Figure 1 It is a flowchart of the management method for the photovoltaic power generation amount in highway service areas provided by the embodiments of the present invention. Detailed Embodiments

[0019] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present invention belongs. The terms used in the description of the present invention herein are only for the purpose of describing specific embodiments, and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0021] It should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe the steps as sequential processes, many of the steps can be implemented in parallel, concurrently, or simultaneously. In addition, the order of the steps can be rearranged. The process can be terminated when its operation is completed, but there can also be additional steps not included in the drawings. The process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0022] An embodiment of the present invention provides a method for managing the photovoltaic power generation in a highway service area, as follows Figure 1 shown, the method may include the following steps:

[0023] S200, obtain the power Qg generated by the photovoltaic modules corresponding to the target highway service area in each unit time period within the first preset time period.

[0024] S210, obtain the vehicle information entering the target highway service area in each unit time period within the first preset time period, and obtain the power Qc required by the target highway service area in each unit time period based on the obtained vehicle information; the vehicle information includes traffic flow and the number of electric vehicles.

[0025] S220, for the s-th unit time period, if the Qg corresponding to this unit time period s > Qc s , then store the remaining power Qr = (Qg s - Qc s ), if Qg s < Qc s , then provide the power Qd = (Qc s - Qg s ), to obtain the available power corresponding to the s-th unit time period; where the stored power is equal to Qr × α s , α s is the storage decay coefficient corresponding to the s-th unit time period, and the value of s ranges from 1 to N, where N is the number of unit time periods; the available power of the current unit time period is equal to the available power of the previous unit time period plus the power stored in the current unit time period or minus the power provided in the current unit time period.

[0026] In the embodiment of the present invention, each time of discharging, the storage decay coefficient will be set to the initial value α 0 . If the (s - 1)-th unit time period is in the discharging state of providing power, then the decay storage coefficient of the s-th unit time period is α 0 , that is, α s = α 0 . If the (s - 1)-th unit time period is in the power storage state of storing power, the storage decay coefficient corresponding to the s-th unit time period is equal to (α s-1 - k × α s-1 ), α s-1 is the storage decay coefficient of the (s - 1)-th unit time period, k is a preset coefficient, 0 < k < 1, and k can be specifically obtained based on the calculation formula of the battery decay coefficient. The decay coefficient SOH of the battery satisfies: SOH = 1 - (C init - C batt ) / 0.2 × C init , C initis the initial capacity of the battery, C batt is the current capacity of the battery.

[0027] S230, obtain the maximum value of the available power within the first preset time period as the reference power, and obtain the capacity of the storage battery based on the reference power.

[0028] In the embodiment of the present invention, the total capacity of the storage battery pack and the capacity of the selected single storage battery can be determined according to the energy storage setting to determine the number of storage batteries required.

[0029] The management method for the photovoltaic power generation amount in the highway service area provided by the embodiment of the present invention determines the capacity of the storage battery to be arranged based on the photovoltaic power generation amount of the photovoltaic modules in the highway service area within the set time period and the power required by the service area within the set time period, so as to be able to reasonably manage the photovoltaic power generation amount in the highway service area.

[0030] Further, in the embodiment of the present invention, the target highway service area can be the highway service area designated by the user. The duration of the first preset time period can be set according to actual needs. For example, it can be 1 year. The duration of the unit time period can be the duration designated by the user. For example, it can be one day or one month, etc., and preferably one day.

[0031] Further, in the embodiment of the present invention, the installation position of the photovoltaic modules corresponding to the target highway service area can be obtained based on the following steps:

[0032] S300, obtain the required power Qt of the target highway service area within the second preset time period.

[0033] S310, obtain the grid unit corresponding to the target highway service area based on Qt.

[0034] S320, obtain the installable area of the photovoltaic modules corresponding to the target highway service area as the target installation area, and divide the target installation area by using the grid unit to obtain a plurality of grid areas.

[0035] S330, obtain the sunlight exposure amount of any grid area within the preset time period and the distance between any grid area and the target highway service area.

[0036] S340, obtain the occluded area and the change speed of the occluded area of any grid area within the preset time period based on the normalized difference vegetation index and environmental variables of the green plants in the corresponding area of any grid area; the occluded area is the projected area of the green plants in the corresponding area of the grid area in the corresponding grid area.

[0037] S350. Obtain a target grid as the grid for installing photovoltaic modules based on the sunlight amount of the grid area corresponding to the target installation area, the distance between the grid area and the target highway service area, the blocked area of the grid area within a preset time period, and the change speed of the blocked area.

[0038] In this embodiment, by comprehensively considering the sunlight amount of the installation area, the distance from the service area, and the influence of green plants on the installation area, it is possible to select the optimal installation area for photovoltaic modules as much as possible, achieving the optimal layout of photovoltaic modules.

[0039] In the embodiment of the present invention, the duration of the second preset time period can be greater than the duration of the first preset time period, and specifically can be a time period specified by the user. For example, it can be 1 year or more than 1 year, such as 10 years.

[0040] Further, in the embodiment of the present invention, Qt is obtained based on a trained power prediction model. The power prediction model can be an existing AI model, such as a deep neural network model, etc.

[0041] Further, in the embodiment of the present invention, the trained power prediction model is obtained through the following steps:

[0042] S201. Obtain a sample data set. The sample data set includes multiple sample data. Each sample data includes U and D, where U is the ID of the corresponding highway service area, and D is the power consumption time series data corresponding to the corresponding highway service area within a set historical time period. D = {D 1 , D 2 , ……, D i , ……, D n}, D i is the power consumption data corresponding to the i-th unit time period. The value of i ranges from 1 to n, and n is the number of unit time periods corresponding to the set historical period. D i = (DC i , DE i , Q i ). DC i is the traffic volume entering the corresponding highway service area within the i-th unit time period, DE i is the number of electric vehicles entering the corresponding highway service area within the i-th unit time period, and Q i is the power consumption of the corresponding highway service area within the i-th unit time period.

[0043] In the embodiment of the present invention, the duration of the set historical time period can be a time period specified by the user. For example, several years. The power consumption data in the sample data can be obtained based on the historical data of the corresponding service area.

[0044] S202, Input the training sample data of the current batch into the current power consumption prediction model for training to obtain the corresponding prediction results. The prediction results include the power consumption data corresponding to the next unit time period of the unit time period corresponding to the current batch.

[0045] S203, Obtain the current loss function value of the current power consumption prediction model based on the prediction results of the current batch and the corresponding true results, and determine whether the current loss function value meets the preset model training end condition. If it meets, execute step S205; otherwise, execute step S204.

[0046] S204, Update the parameters of the current power consumption prediction model based on the current loss function value, and use the sample data of the next batch as the training sample data of the current batch, and execute S202.

[0047] S205, Use the current power consumption prediction model as the trained power consumption prediction model.

[0048] In the embodiments of the present invention, the loss function value can be calculated based on the existing loss function. The preset model training end condition can be set according to actual needs. For example, the loss is less than or less than or equal to the set loss threshold and remains unchanged within the set time period.

[0049] Further, Qt can be specifically obtained through the following steps:

[0050] S10, Based on the traffic flow and the number of electric vehicles in the target highway service area within the set historical time period, determine the traffic flow and the number of electric vehicles in the target highway service area within the unit time period as the initial power consumption data.

[0051] S11, Set the counter variable j = 1.

[0052] S12, If j ≤ k, execute S13; otherwise, execute S16; k is the number of unit time periods corresponding to the preset time period, k = roundup(t1 / t2), t1 is the duration corresponding to the preset time period, t2 is the duration corresponding to the unit time period, and roundup() represents rounding up.

[0053] S13, Use the current prediction result of the trained power consumption prediction model as the current power consumption data corresponding to the target highway service area, and add the current prediction result to the current prediction result set; the current prediction result includes the corresponding predicted traffic flow, predicted number of electric vehicles, and predicted power consumption; the initial value of the current prediction result set is empty.

[0054] S14. Input the current power consumption data corresponding to the target highway service area into the trained power consumption prediction model to obtain the corresponding current prediction result.

[0055] S15. Set j = j + 1 and execute S12.

[0056] S16. Obtain Qt based on the predicted power consumption corresponding to the current prediction result set.

[0057] Further, in the embodiment of the present invention, the grid unit corresponding to the target highway service area is obtained by referring to a preset look-up table, wherein each row of data in the preset query table includes a highway service area, the power consumption of the service area within a preset time period, and the corresponding grid unit.

[0058] Among them, the preset query table can be obtained based on the following steps:

[0059] S201. Obtain the power required by any reference highway service area within a preset time period.

[0060] In the embodiment of the present invention, the reference highway service area can be a highway service area specified by the user.

[0061] S202. Obtain the installable area of the photovoltaic module corresponding to any reference highway service area as the corresponding target installation area.

[0062] In the embodiment of the present invention, the installable area of the photovoltaic module corresponding to the highway service area can be determined according to actual needs. For example, it can be on both sides of the highway between the reference highway service area and the highway service area adjacent to the reference highway service area. If there is a green belt on the highway, it can also include above the green belt, etc. S203. Use the preset initial grid unit to divide the target installation area corresponding to any reference highway service area to obtain the corresponding multiple grid areas; the preset initial grid unit is a grid area suitable for installing a photovoltaic module, that is, the size of the preset initial grid unit is set to be able to install the size of a photovoltaic module. The grid unit can be rectangular or square.

[0063] S204. Obtain the sunshine amount of any grid area corresponding to any reference highway service area within the preset time period.

[0064] S205. Based on the power required by any reference highway service area within a preset time period and the sunshine amount corresponding to each grid area, obtain the target grid area from the multiple grid areas as the grid unit corresponding to the reference highway service area; wherein, the target grid area is a square area formed by at least one initial grid unit, and the power generated by the target grid area is greater than or equal to the power required by the corresponding reference highway service area within a preset time period.

[0065] S206. Form the preset query table based on the power consumption required by any reference highway service area within a preset time period and the corresponding grid cells.

[0066] Furthermore, the power generation Qg of the photovoltaic module within each unit time period in the first preset time period is obtained based on the sunlight exposure amount in the corresponding unit time period, and the specific obtaining method can be the existing technology. The sunlight exposure amount in each unit time period is obtained based on a trained sunlight exposure amount prediction model. The sunlight exposure amount prediction model can be an AI model, such as a deep neural network model.

[0067] Furthermore, the trained sunlight exposure amount prediction model is obtained through the following steps:

[0068] S1. Obtain a training sample data set. Each sample data includes the sunlight exposure amount time series data SA at the corresponding sampling point within a set historical time period, SA = {SA 1 , SA 2 , ……, SA r , ……, SA m}, SA r is the sunlight exposure amount data corresponding to the r-th unit time period, where r ranges from 1 to m, and m is the number of unit time periods corresponding to the set historical period. SA r =(L r , SA1 r , SA2 r ), L r is the location of the corresponding sampling point of the corresponding sample data, SA1 r is the weather characteristic information corresponding to the corresponding sampling point in the r-th unit time period, and SA2 r is the sunlight exposure amount corresponding to the corresponding sampling point in the r-th unit time period.

[0069] In the embodiment of the present invention, the sampling point can be an unobstructed open area. The location of the sampling point can be the longitude and latitude coordinates of the sampling point, which can be obtained through the corresponding remote sensing image.

[0070] In the embodiment of the present invention, the weather characteristic information can include sunrise time, sunset time, ultraviolet intensity, temperature, humidity, visibility, etc. The sunlight exposure amount of the sampling point can be measured by an installed sunshine recorder, sunshine radiation sensor, etc.

[0071] S2. Input the training sample data of the current batch into the current sunlight exposure prediction model for training to obtain the corresponding prediction results. The prediction results include the weather characteristic information and sunlight exposure amount corresponding to the next unit time period of the unit time period corresponding to the current batch.

[0072] S3. Obtain the current loss function value of the current sunshine amount prediction model based on the prediction results of the current batch and the corresponding true results, and determine whether the current loss function value meets the preset model training end condition. If it meets, execute step S5; otherwise, execute step S4.

[0073] S4. Update the parameters of the current sunshine amount prediction model based on the current loss function value, and use the sample data of the next batch as the training sample data of the current batch, then execute S2.

[0074] S5. Take the current sunshine amount prediction model as the trained sunshine amount prediction model.

[0075] Further, the sunshine amount in each unit time period within the first preset time period of the photovoltaic module can be obtained by inputting the installation position of the photovoltaic module and the weather characteristic information corresponding to the previous unit time period into the trained sunshine amount prediction model.

[0076] As is known to those skilled in the art, the first unit time period within the first preset time period is the current time period. The sunshine amount corresponding to the subsequent unit time period t is obtained based on the weather characteristic information corresponding to the previous unit time period t - 1.

[0077] Further, in the embodiment of the present invention, the installable area of the photovoltaic module corresponding to the target highway service area can be on both sides of the highway between the target highway service area and the adjacent highway service area. If there is a green belt on the highway, it can also include above the green belt, etc.

[0078] Further, in the embodiment of the present invention, the distance between each grid area and the target highway service area can be the distance between the center of the grid area and the center of the corresponding highway service area.

[0079] As is known to those skilled in the art, the position of each position point in each grid area can be obtained based on the corresponding map.

[0080] Further, in the embodiment of the present invention, the corresponding area of any grid area can be the nearest green plant planting area to the grid area. The blocked area of any grid area within the preset time period can be predicted based on the current normalized difference vegetation index and environmental variables of the green plants in the area corresponding to the grid area.

[0081] In the embodiment of the present invention, the environmental variables can be air temperature, precipitation, etc.

[0082] Specifically, based on the current normalized difference vegetation index (NDVI) and environmental variables, it is possible to predict the growth range of green plants in the corresponding area after a preset period of time, and then obtain a regression model between the occluded area, NDVI, and environmental variables.

[0083] As is known to those skilled in the art, since the occluded area of each grid region in each unit time period can be known, the change rate of the occluded area of each grid region within the preset time period can be obtained.

[0084] Furthermore, the target grid region is obtained through the following steps:

[0085] S161: Based on the sunlight exposure, distance, occluded area, and change rate of the occluded area corresponding to any grid region, determine the scores corresponding to the sunlight exposure, distance, occluded area, and change rate of the occluded area of this grid region.

[0086] In the embodiments of the present invention, the method for determining the scores of sunlight exposure, distance, occluded area, and change rate of the occluded area can be set according to actual needs. Generally, the scores of sunlight exposure, distance, occluded area, and change rate of the occluded area are positively correlated with the magnitudes of sunlight exposure, distance, occluded area, and change rate of the occluded area. For example, the greater the sunlight exposure, the greater the corresponding score, and vice versa.

[0087] S162: Multiply the scores corresponding to the sunlight exposure, distance, occluded area, and change rate of the occluded area of any grid region by the corresponding weights respectively, and add the obtained multiplication results to obtain the installation weight of this grid region.

[0088] In the embodiments of the present invention, the weights of sunlight exposure, distance, occluded area, and change rate of the occluded area can be set according to actual needs. In one exemplary embodiment, the weights of sunlight exposure, distance, occluded area, and change rate of the occluded area can be the same, for example, all 0.25. In another exemplary embodiment, the weights of sunlight exposure, distance, occluded area, and change rate of the occluded area can be different. For example, the weights of sunlight exposure, distance, occluded area, and change rate of the occluded area can be set in a decreasing order.

[0089] S163: Take the grid region corresponding to the maximum value among all installation weights as the target grid region. Based on the same inventive concept, the embodiments of the present invention provide a management device for the photovoltaic power generation amount in a highway service area. The device includes:

[0090] A first acquisition module, configured to acquire the power generation amount Qg generated by the photovoltaic modules corresponding to the target highway service area in each unit time period within the first preset time period.

[0091] A second acquisition module, configured to acquire vehicle information entering a target highway service area within each unit time period of a first preset time period, and acquire the power Qc required by the target highway service area in each unit time period based on the acquired vehicle information; the vehicle information includes traffic flow and the number of electric vehicles.

[0092] A processing module, for the s-th unit time period, if the Qg corresponding to this unit time period s > Qc s , then store the remaining power Qr = (Qg s - Qc s ), if Qg s < Qc s , then provide the power Qd = (Qc s - Qg s ) to obtain the available power corresponding to the s-th unit time period; where the stored power is equal to Qr × α s , α s is the storage decay coefficient corresponding to the s-th unit time period, s ranges from 1 to N, and N is the number of unit time periods; the available power of the current unit time period is equal to the available power corresponding to the previous unit time period plus the power stored in the current unit time period or minus the power provided in the current unit time period.

[0093] A third acquisition module, configured to acquire the maximum value of the available power within the first preset time period as a reference power, and acquire the capacity of the storage battery based on the reference power.

[0094] This device can be used to execute Figure 1 the method shown in the embodiments shown, therefore, for the functions that can be realized by each functional module of this device, reference can be made to Figure 1 the description of the embodiments shown, and details are not repeated here. An embodiment of the present invention also provides an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are configured to execute the method of the embodiment of the present invention.

[0095] An embodiment of the present invention also provides a non-transitory computer-readable storage medium, storing computer-executable instructions, and the computer instructions are used to execute the method of the embodiment of the present invention.

[0096] It should be understood that various forms of processes shown above can be used, steps can be reordered, added or deleted. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in the present invention can be achieved, and no limitations are imposed herein.

[0097] The above specific embodiments do not constitute a limitation on the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub - combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for managing photovoltaic power generation in a highway service area, characterized in that: The method comprises the following steps: S200, obtaining the amount of electricity Qg generated by the photovoltaic assembly corresponding to the target high-speed service area in each unit time period within a first preset time period; S210, obtaining vehicle information entering the target highway service area in each unit time period within the first preset time period, and obtaining the power Qc required by the target highway service area in each unit time period based on the obtained vehicle information; The vehicle information includes vehicle flow and the number of electric vehicles; S220, for the s-th unit time period, if the Qg corresponding to the unit time period s >Qc s , then the remaining power Qr = (Qg s -Qc s ) for storage, if Qg s <Qc s , then the power provided is Qd=(Qc s -Qg s ), and the available power corresponding to the s-th unit time period is obtained; where the stored power is equal to Qr×α s , α s is the storage attenuation coefficient corresponding to the sth unit time period, s ranges from 1 to N, N is the number of unit time periods; the available power in the current unit time period is equal to the available power corresponding to the previous unit time period plus the power stored in the current unit time period or minus the power provided in the current unit time period; S230, obtaining the maximum amount of power available in the first preset time period as a reference amount of power, and obtaining the capacity of the battery based on the reference amount of power; The installation location of the photovoltaic module corresponding to the target high-speed service area is obtained based on the following steps: S300, obtaining the power Qt required by the target highway service area within a second preset time period; S310, obtaining a grid unit corresponding to a target highway service area based on Qt; S320, obtaining a photovoltaic module installable area corresponding to a target highway service area as a target installation area, and dividing the target installation area by using the grid units to obtain a plurality of grid areas; S330, obtaining the sunshine amount of any grid area in the preset time period and the distance between any grid area and the target highway service area; S340, based on the normalized vegetation index and environmental variables of the green plants in the area corresponding to any grid area, obtaining the blocked area and the speed of change of the blocked area of ​​any grid area within a preset time period; the blocked area is the projection area of ​​the green plants in the area corresponding to the grid area in the corresponding grid area; S350, based on the sunshine amount of the grid area corresponding to the target installation area, the distance between the grid area and the target high-speed service area, the shaded area of ​​the grid area within a preset time period and the speed of change of the shaded area, obtain the target grid area as the grid area for installing photovoltaic modules.

2. The method according to claim 1, characterized in that Qt is obtained based on the trained power prediction model.

3. The method according to claim 2, characterized in that The trained power prediction model is obtained through the following steps: S201, obtaining a sample data set, wherein the sample data set includes a plurality of sample data, each sample data includes U and D, wherein U is the ID of the corresponding high-speed service area, and D is the power consumption time series data corresponding to the corresponding high-speed service area in a set historical time period, D={D1, D2, ..., D i , ..., D n }, D i is the electricity consumption data corresponding to the i-th unit time period, i ranges from 1 to n, n is the number of unit time periods corresponding to the set historical segment, D i =(DC i ,DE i , Q i ), DC i is the traffic volume entering the corresponding highway service area in the i-th unit time period, DE i is the number of electric vehicles entering the corresponding highway service area in the i-th unit time period, Q i is the power consumption of the corresponding high-speed service area in the i-th unit time period; S202, inputting the training sample data of the current batch into the current power prediction model for training to obtain corresponding prediction results, wherein the prediction results include power consumption data corresponding to the next unit time period of the unit time period corresponding to the current batch; S203, based on the prediction results of the current batch and the corresponding actual results, the current loss function value of the current electricity prediction model is obtained, and it is determined whether the current loss function value meets the preset model training end condition. If so, step S205 is executed, otherwise, step S204 is executed; S204, updating the parameters of the current power prediction model based on the current loss function value, and using the next batch of sample data as the training sample data of the current batch, and executing S202; S205: Using the current power prediction model as the trained power prediction model.

4. The method according to claim 1, characterized in that: The amount of electricity Qg generated by the photovoltaic component in each unit time period within the first preset time period is obtained based on the sunshine amount in the corresponding unit time period, and the sunshine amount in each unit time period is obtained based on the trained sunshine amount prediction model.

5. The method according to claim 4, characterized in that The trained sunshine amount prediction model is obtained through the following steps: S1, obtain a training sample data set, each sample data includes the sunshine amount time series data SA of the corresponding sampling point of the corresponding sample data in the set historical time period, SA = {SA1, SA2, ..., SA r , ..., SA m }, SA r is the sunshine data corresponding to the rth unit time period, r ranges from 1 to m, m is the number of unit time periods corresponding to the set historical period, SA r =(L r , SA1 r , SA2 r ), L r is the position of the sampling point corresponding to the sample data, SA1 r is the weather characteristic information corresponding to the sampling point in the rth unit time period, SA2 r is the sunshine amount corresponding to the sampling point in the rth unit time period; S2, inputting the training sample data of the current batch into the current sunshine prediction model for training to obtain the corresponding prediction result, wherein the prediction result includes the weather characteristic information and sunshine amount corresponding to the next unit time period of the unit time period corresponding to the current batch; S3, based on the prediction results of the current batch and the corresponding actual results, the current loss function value of the current sunshine prediction model is obtained, and it is determined whether the current loss function value meets the preset model training end condition. If so, step S5 is executed, otherwise, step S4 is executed; S4, updating the parameters of the current sunshine amount prediction model based on the current loss function value, and using the next batch of sample data as the training sample data of the current batch, and executing S2; S5: Using the current sunshine amount prediction model as the trained sunshine amount prediction model.

6. The method according to claim 1, characterized in that The target grid area is obtained by the following steps: S161, based on the sunshine amount, distance, shaded area and shaded area change rate corresponding to any grid area, determining the scores corresponding to the sunshine amount, distance, shaded area and shaded area change rate corresponding to the grid area; S162, multiplying the scores corresponding to the sunshine amount, distance, shaded area and shaded area change speed corresponding to any grid area by the corresponding weights respectively and adding the respective multiplication results as the installation weight of the grid area; S163: The grid area corresponding to the largest of all installation weights is used as the target grid area.

7. A management device for photovoltaic power generation in a highway service area, characterized in that: The device comprises: A first acquisition module is used to acquire the amount of electricity Qg generated by the photovoltaic assembly corresponding to the target high-speed service area in each unit time period within a first preset time period; A second acquisition module is used to acquire vehicle information entering the target highway service area in each unit time period within the first preset time period, and acquire the power Qc required by the target highway service area in each unit time period based on the acquired vehicle information; the vehicle information includes vehicle flow and the number of electric vehicles; The processing module is used for the s-th unit time period, if the Qg corresponding to the unit time period s >Qc s , then the remaining power Qr = (Qg s -Qc s ) for storage, if Qg s <Qc s , then the power provided is Qd=(Qc s -Qg s ), and the available power corresponding to the s-th unit time period is obtained; where the stored power is equal to Qr×α s , α s is the storage attenuation coefficient corresponding to the sth unit time period, s ranges from 1 to N, N is the number of unit time periods; the available power in the current unit time period is equal to the available power corresponding to the previous unit time period plus the power stored in the current unit time period or minus the power provided in the current unit time period; A third acquisition module, used to acquire the maximum amount of power available within the first preset time period as a reference amount of power, and acquire the capacity of the battery based on the reference amount of power; The installation location of the photovoltaic module corresponding to the target high-speed service area is obtained based on the following steps: S300, obtaining the power Qt required by the target highway service area within a second preset time period; S310, obtaining a grid unit corresponding to a target highway service area based on Qt; S320, obtaining a photovoltaic module installable area corresponding to a target highway service area as a target installation area, and dividing the target installation area by using the grid units to obtain a plurality of grid areas; S330, obtaining the sunshine amount of any grid area in the preset time period and the distance between any grid area and the target highway service area; S340, based on the normalized vegetation index and environmental variables of the green plants in the area corresponding to any grid area, obtaining the blocked area and the speed of change of the blocked area of ​​any grid area within a preset time period; the blocked area is the projection area of ​​the green plants in the area corresponding to the grid area in the corresponding grid area; S350, based on the sunshine amount of the grid area corresponding to the target installation area, the distance between the grid area and the target high-speed service area, the shaded area of ​​the grid area within a preset time period and the speed of change of the shaded area, obtain the target grid area as the grid area for installing photovoltaic modules.

8. The device according to claim 7, characterized in that The target grid area is obtained by the following steps: S161, based on the sunshine amount, distance, shaded area and shaded area change rate corresponding to any grid area, determining the scores corresponding to the sunshine amount, distance, shaded area and shaded area change rate corresponding to the grid area; S162, multiplying the scores corresponding to the sunshine amount, distance, shaded area and shaded area change speed corresponding to any grid area by the corresponding weights respectively and adding the respective multiplication results as the installation weight of the grid area; S163: The grid area corresponding to the largest of all installation weights is used as the target grid area.

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