Method and device for monitoring carbon emission reduction of expressway service area photovoltaic power generation system

Abstract

The application provides a highway service area photovoltaic power generation system carbon emission reduction amount monitoring method and device, the method comprises the following steps: determining the installation position of the photovoltaic module of any target highway service area; installing the photovoltaic module at the determined installation position, starting the photovoltaic module and monitoring the photovoltaic module in real time; at the current monitoring moment, acquiring the power generated by the photovoltaic module of any target highway service area in the current monitoring time period and the power consumed by any target highway service area in the current monitoring time period; acquiring the power difference between the power generated by the photovoltaic module of any target highway service area in the current monitoring time period and the power consumed by any target highway service area in the current monitoring time period, and performing visual display. The application can monitor the carbon emission reduction amount of the highway service area photovoltaic power generation system in real time.

Description

Technical Field

[0001] This invention relates to the field of power technology, and in particular to a method and device for monitoring the carbon emission reduction of a photovoltaic power generation system in a highway service area. Background Technology

[0002] With the strong advocacy for clean energy, electric vehicles have become widely used. As battery range continues to improve, more and more electric vehicles are operating on highways. This places higher demands on the power supply capacity of highway service areas. Solar energy, as an important renewable energy source, has become a key area for clean energy applications. Therefore, real-time monitoring of carbon emission reduction from energy use in highway service areas is a worthy research topic. Summary of the Invention

[0003] To address the aforementioned technical problems, the technical solution adopted by this invention is as follows:

[0004] According to a first aspect of the present invention, a method for monitoring the carbon emission reduction of a photovoltaic power generation system in a highway service area is provided, the method comprising the following steps:

[0005] S400 determines the installation location of photovoltaic modules in any target highway service area.

[0006] S410: Install photovoltaic modules at the designated installation location, start the photovoltaic modules, and monitor the photovoltaic modules in real time.

[0007] S420: At the current monitoring time, obtain the electricity generated by the photovoltaic modules of any target highway service area during the current monitoring time period and the electricity consumed by any target highway service area during the current monitoring time period; the current monitoring time period is the time period between the current monitoring time and the previous monitoring time.

[0008] S430: Obtain the power difference between the power generated by the photovoltaic module of any target highway service area during the current monitoring period and the power consumed by any target highway service area during the current monitoring period, and display it visually; wherein, the power difference with a negative value is displayed with a set color.

[0009] According to a second aspect of the present invention, a real-time monitoring device for energy carbon emission reduction in highway service areas is provided, the device comprising:

[0010] The first determining module is used to determine the installation location of photovoltaic modules in any target highway service area.

[0011] The second determining module is used to install photovoltaic modules at the determined installation location, start the photovoltaic modules, and monitor the photovoltaic modules in real time.

[0012] The power monitoring module is used to obtain the power generated by the photovoltaic modules of any target highway service area during the current monitoring time period and the power consumed by any target highway service area during the current monitoring time period; the current monitoring time period is the time period between the current monitoring time and the previous monitoring time.

[0013] The display module is used to obtain the difference between the electricity generated by the photovoltaic modules of any target highway service area during the current monitoring period and the electricity consumed by any target highway service area during the current monitoring period, and to display it visually; wherein, the electricity difference with a negative value is displayed with a set color.

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

[0015] The real-time monitoring scheme for energy carbon emission reduction in highway service areas provided in this embodiment of the invention can monitor the energy carbon emission reduction in highway service areas in real time.

[0016] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A flowchart illustrating a method for monitoring carbon emission reduction of a photovoltaic power generation system in a highway service area, provided as an embodiment of the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within 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 one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of this invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated 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 these steps can be performed in parallel, concurrently, or simultaneously. Furthermore, the order of the steps can be rearranged. A process can be terminated when its operation is complete, but it may also have additional steps not included in the figures. A process can correspond to a method, function, procedure, subroutine, subroutine, etc.

[0022] This invention provides a method for monitoring the carbon emission reduction of a photovoltaic power generation system in a highway service area, such as... Figure 1 As shown, the method may include the following steps:

[0023] S400 determines the installation location of photovoltaic modules in any target highway service area.

[0024] S410: Install photovoltaic modules at the designated installation location, start the photovoltaic modules, and monitor the photovoltaic modules in real time.

[0025] S420: At the current monitoring time, obtain the electricity generated by the photovoltaic modules of any target highway service area during the current monitoring time period and the electricity consumed by any target highway service area during the current monitoring time period; the current monitoring time period is the time period between the current monitoring time and the previous monitoring time.

[0026] S430: Obtain the power difference between the power generated by the photovoltaic module of any target highway service area during the current monitoring period and the power consumed by any target highway service area during the current monitoring period, and display it visually; wherein, the power difference with a negative value is displayed with a set color.

[0027] The real-time monitoring scheme for energy carbon emission reduction in highway service areas provided in this embodiment of the invention can monitor the energy carbon emission reduction in highway service areas in real time.

[0028] In this embodiment of the invention, the photovoltaic module can be an existing photovoltaic module, such as a combiner box, power converter, cable tray, and other components.

[0029] Furthermore, in this embodiment of the invention, the target highway service area can be a highway service area designated by the user. Multiple target highway service areas can be communicatively connected to a remote monitoring terminal.

[0030] Furthermore, the S400 may specifically include:

[0031] S410, obtain the power Qt required by the target highway service area in the second preset time period.

[0032] S420 uses Qt to obtain the grid cells corresponding to the target highway service area.

[0033] S430: Obtain the photovoltaic module installation area corresponding to the target highway service area as the target installation area, and divide the target installation area into multiple grid areas using the grid unit.

[0034] S440, obtain the amount of sunshine in any grid area during the preset time period and the distance between any grid area and the target highway service area.

[0035] S450, obtain the normalized vegetation index and environmental variables of the green plants in any grid area, and obtain the shaded area and the rate of change of the shaded area in any grid area within a preset time period; the shaded area is the projected area of ​​the green plants in the corresponding grid area.

[0036] S460, based on the solar irradiance of the grid area corresponding to the target installation area, the distance between the grid area and the target highway service area, the shaded area of ​​the grid area within a preset time period and the rate of change of the shaded area, obtains the target grid as the grid for installing photovoltaic modules.

[0037] In this embodiment of the invention, by comprehensively considering the amount of sunlight in the installation area, the distance between the installation area and the service area, and the impact of greenery on the installation area, the optimal photovoltaic module installation area can be selected as much as possible, thereby achieving the optimal layout of the photovoltaic modules.

[0038] Furthermore, in this embodiment of the invention, Qt can be 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.

[0039] Furthermore, in this embodiment of the invention, the trained power prediction model can be obtained through the following steps:

[0040] S101, Obtain a sample dataset, which includes multiple sample data, each sample data including U and D, where U is the ID of the corresponding highway service area, such as the name or name code of the service area, and D is the electricity consumption time sequence data of the corresponding highway service area within a set historical time period, D = {D1, D2, ..., D...} i , ..., D n}, D i This refers to the electricity consumption data corresponding to the i-th time unit, where i ranges from 1 to n, and n is the number of time units corresponding to the set historical segment. i =(DC) i DE i Q i DC i Let DE be the traffic flow entering the corresponding highway service area within the i-th time unit, i.e., the total number of vehicles entering the service area, including both gasoline and electric vehicles. i Let Q be the number of electric vehicles entering the corresponding highway service area within the i-th time unit. i This represents the electricity consumption of the corresponding highway service area during the i-th time unit.

[0041] In this embodiment of the invention, the duration of the historical time period can be a user-specified period, such as several years. The duration of a unit time period can be a user-specified duration, such as one day or one month, preferably one day. The electricity consumption data in the sample data can be obtained based on historical data of the corresponding service area.

[0042] S102, input the training sample data of the current batch into the current power prediction model for training, and 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.

[0043] S103: Based on the prediction results of the current batch and the corresponding actual results, obtain the current loss function value of the current power prediction model, and determine whether the current loss function value meets the preset model training termination condition. If it does, proceed to step S105; otherwise, proceed to step S104.

[0044] S104, update the parameters of the current power 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 S102.

[0045] S105, use the current power prediction model as the trained power prediction model.

[0046] In this embodiment of the invention, the loss function value can be calculated based on an existing loss function. The preset model training termination condition can be set according to actual needs. For example, the loss is less than or equal to a set loss threshold and remains unchanged within a set time period.

[0047] Furthermore, Qt can be obtained through the following steps:

[0048] S10, based on the traffic flow and number of electric vehicles of the target highway service area within a set historical time period, determine the traffic flow and number of electric vehicles of the target highway service area within a unit time period, and use them as initial electricity consumption data.

[0049] S11, set the counter variable j = 1.

[0050] 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() means rounding up.

[0051] S13, the current prediction result based on the trained power prediction model is used as the current power consumption data corresponding to the target highway service area, and the current prediction result is added 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.

[0052] S14, input the current electricity consumption data corresponding to the target highway service area into the trained electricity prediction model to obtain the corresponding current prediction result.

[0053] S15, set j = j + 1, execute S12;

[0054] S16, obtain Qt based on the predicted electricity consumption corresponding to the current prediction result set.

[0055] Furthermore, in this embodiment of the invention, the grid unit corresponding to the target highway service area is obtained by consulting a preset lookup table, wherein each row of data in the preset lookup table includes the highway service area, the electricity consumption of the service area within a preset time period, and the corresponding grid unit.

[0056] The preset lookup table can be obtained based on the following steps:

[0057] S201, obtain the electricity required by any reference highway service area within a preset time period.

[0058] In this embodiment of the invention, the reference highway service area can be a highway service area designated by the user.

[0059] S202, Obtain the photovoltaic module installation area corresponding to any reference highway service area as the corresponding target installation area.

[0060] In this embodiment of the invention, the area where photovoltaic modules can be installed corresponding to a highway service area can be determined based on actual needs. For example, it can be the area on both sides of the highway between a reference highway service area and an adjacent highway service area. If there is a green belt on the highway, it can also include the area above the green belt, etc.

[0061] S203, the target installation area corresponding to any reference highway service area is divided using a preset initial grid unit to obtain multiple corresponding 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 a photovoltaic module. The grid unit can be rectangular or square.

[0062] S204, obtain the sunshine duration of any grid area corresponding to any reference highway service area within the preset time period.

[0063] S205, based on the electricity required by any reference highway service area within a preset time period and the sunshine amount corresponding to each grid area, a target grid area is obtained from 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 electricity generated by the target grid area is greater than or equal to the electricity required by the corresponding reference highway service area within the preset time period.

[0064] S206. Based on the electricity required by any reference highway service area within a preset time period and the corresponding grid cells, the preset query table is formed.

[0065] Furthermore, photovoltaic modules can be monitored in real time according to a set monitoring cycle. The monitoring cycle can be set based on actual needs; for example, the monitoring cycle can be 1 hour. The duration of each monitoring time period is equal to one monitoring cycle.

[0066] Furthermore, in this embodiment of the invention, the electricity generated by the photovoltaic modules in any target highway service area during the current monitoring period can be obtained based on the solar irradiance of the photovoltaic modules during the current monitoring period, and the specific method for obtaining this information can be existing technology. The solar irradiance of the photovoltaic modules during the current monitoring period is obtained based on a trained solar irradiance prediction model. The solar irradiance prediction model can be an AI model, such as a deep neural network model.

[0067] Furthermore, the trained solar radiation prediction model can be obtained through the following steps:

[0068] S1, Obtain the training sample dataset. Each sample dataset includes the solar sunshine duration time series data SA of the corresponding sampling point within a set historical time period, SA = {SA1, SA2, ..., SA3}. r , ..., SA m}, SA r This refers to the solar sunshine data corresponding to the r-th time unit, where r ranges from 1 to m, and m is the number of time units corresponding to the set historical period. SA r =(L r SA1 r SA2 r ), L r SA1 represents the location of the sampling point corresponding to the corresponding sample data. r SA2 represents the weather feature information corresponding to the sampling point in the r-th time unit. r This represents the solar radiation at the corresponding sampling point in the r-th unit time period.

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

[0070] In this embodiment of the invention, weather characteristic information may include sunrise time, sunset time, ultraviolet radiation intensity, temperature, humidity, visibility, etc. The amount of sunshine at the sampling point can be obtained by installing a sunmeter, solar radiation sensor, etc.

[0071] S2, input the training sample data of the current batch into the current sunshine prediction model for training, and obtain the corresponding prediction results. The prediction results include the weather feature information and sunshine amount corresponding to the next unit time period corresponding to the unit time period of the current batch.

[0072] S3. Based on the prediction results of the current batch and the corresponding real results, obtain the current loss function value of the current sunshine amount prediction model, and determine whether the current loss function value meets the preset model training termination condition. If it does, proceed to step S5; otherwise, proceed to step S4.

[0073] S4, update the parameters of the current solar radiation prediction model based on the current loss function value, and use the next batch of sample data as the training sample data of the current batch, and execute S2.

[0074] S5, use the current solar radiation prediction model as the trained solar radiation prediction model.

[0075] Furthermore, the amount of sunshine in any grid area during the preset time period is obtained based on the following steps:

[0076] S20 uses the location of any grid area and the weather feature information corresponding to the current unit time period as the initial input data.

[0077] S21, set the counter variable j1 = 1.

[0078] S22, if j1≤k1, execute S23, otherwise execute S26; k1 is the number of unit time periods corresponding to the preset time period, k1=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() means rounding up.

[0079] S23, the current prediction result based on the trained solar radiation prediction model is used as the current input data for any grid area, and the current prediction result is added to the current prediction result set; the current prediction result includes the corresponding weather feature information and solar radiation; the initial value of the current prediction result set is empty.

[0080] S24, input the current input data corresponding to any grid area into the trained solar radiation prediction model to obtain the corresponding current prediction result.

[0081] S25, set j1 = j1 + 1, execute S22.

[0082] S26. Obtain the sunshine amount of any grid area within a preset time period based on the sunshine amount corresponding to the current prediction result set of any grid area.

[0083] Furthermore, the solar irradiance of the photovoltaic modules during the current monitoring period can be obtained by inputting the installation location of the photovoltaic modules and the weather characteristic information corresponding to the current monitoring period into a trained solar irradiance prediction model.

[0084] Furthermore, in this embodiment of the invention, if there is one target highway service area, the photovoltaic module installation area corresponding to the target highway service area can be located on both sides of the highway between the target highway service area and an adjacent highway service area. If there is a green belt on the highway, it can also include the area above the green belt, etc. If there are two target highway service areas, the photovoltaic module installation area corresponding to the target highway service area can be located on both sides of the highway between the two corresponding highway service areas. If there is a green belt on the highway, it can also include the area above the green belt, etc. If there are multiple target highway service areas, the photovoltaic module installation area corresponding to the target highway service area can be located on both sides of all highways within the enclosure of the multiple highway service areas. If there is a green belt on the corresponding highway, it can also include the area above the green belt, etc.

[0085] Furthermore, in this embodiment of the 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.

[0086] Those skilled in the art will know that the location of each point in each grid area can be obtained based on the corresponding map.

[0087] Furthermore, in S140, the area corresponding to any grid area can be the green planting area closest to the grid area. The shading area of ​​any grid area within a preset time period can be predicted based on the current normalized vegetation index and environmental variables of the green plants in the area corresponding to that grid area.

[0088] In this embodiment of the invention, environmental variables may include temperature, precipitation, etc.

[0089] Specifically, based on the current normalized vegetation index and environmental variables, the growth range of vegetation in the corresponding area can be predicted after a preset time period, thereby obtaining a regression model between the shaded area and the normalized vegetation index and environmental variables.

[0090] Those skilled in the art will know that, since the occluded area of ​​each grid region in each unit time period can be known, the rate of change of the occluded area of ​​each grid region in a preset time period can be obtained.

[0091] Furthermore, in this embodiment of the invention, the target grid region can be obtained through the following steps:

[0092] S161. Based on the solar radiation, distance, shaded area, and rate of change of shaded area corresponding to any grid area, determine the scores corresponding to the solar radiation, distance, shaded area, and rate of change of shaded area corresponding to that grid area.

[0093] In this embodiment of the invention, the determination method for the scores of solar radiation, distance, obscured area, and rate of change of obscured area can be set based on actual needs. Generally, the scores of solar radiation, distance, obscured area, and rate of change of obscured area are positively correlated with the magnitude of solar radiation, distance, obscured area, and rate of change of obscured area. For example, the greater the solar radiation, the greater the corresponding score, and vice versa.

[0094] S162: Multiply the scores for solar radiation, distance, obscured area, and rate of change of obscured area corresponding to any grid area by their respective weights, and add the results of these multiplications together to obtain the installation weight for that grid area.

[0095] In this embodiment of the invention, the weights of solar radiation, distance, shaded area, and rate of change of the shaded area can be set based on actual needs. In one illustrative embodiment, the weights of solar radiation, distance, shaded area, and rate of change of the shaded area can be the same, for example, all of which are 0.25. In another illustrative embodiment, the weights of solar radiation, distance, shaded area, and rate of change of the shaded area can be different; for example, the weights of solar radiation, distance, shaded area, and rate of change of the shaded area can be set in a decreasing order.

[0096] S163, take the grid region corresponding to the largest of all installation weights as the target grid region.

[0097] Based on the same inventive concept, embodiments of the present invention provide a real-time monitoring device for energy carbon emission reduction in highway service areas, the device comprising:

[0098] The first determining module is used to determine the installation location of photovoltaic modules in any target highway service area.

[0099] The second determining module is used to install photovoltaic modules at the determined installation location, start the photovoltaic modules, and monitor the photovoltaic modules in real time.

[0100] The power monitoring module is used to obtain the power generated by the photovoltaic modules of any target highway service area during the current monitoring time period and the power consumed by any target highway service area during the current monitoring time period; the current monitoring time period is the time period between the current monitoring time and the previous monitoring time.

[0101] The display module is used to obtain the difference between the electricity generated by the photovoltaic modules of any target highway service area during the current monitoring period and the electricity consumed by any target highway service area during the current monitoring period, and to display it visually; wherein, the electricity difference with a negative value is displayed with a set color.

[0102] This device can be used to perform Figure 1 The method shown in the illustrated embodiment is relevant here; therefore, the functions that each functional module of the device can achieve can be referred to. Figure 1 The embodiments shown are described in detail below.

[0103] This 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, the instructions being configured to perform the method described in this invention.

[0104] This invention also provides a non-transitory computer-readable storage medium storing computer-executable instructions for performing the methods described in this invention.

[0105] It should be understood that the various forms of processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this invention can be achieved, and this is not limited herein.

[0106] The specific embodiments described above do not constitute a limitation on the scope of protection of this 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 principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for monitoring the carbon emission reduction of a photovoltaic power generation system in a highway service area, characterized in that, The method includes the following steps: S400 determines the installation location of photovoltaic modules in any target highway service area; S410: Install photovoltaic modules at the determined installation location, start the photovoltaic modules, and monitor the photovoltaic modules in real time; S420, at the current monitoring time, acquire the electricity generated by the photovoltaic modules of any target highway service area during the current monitoring time period and the electricity consumed by any target highway service area during the current monitoring time period; the current monitoring time period is the time period between the current monitoring time and the previous monitoring time. S430: Obtain the power difference between the power generated by the photovoltaic module of any target highway service area during the current monitoring period and the power consumed by any target highway service area during the current monitoring period, and display it visually; wherein, the power difference with a negative value is displayed with a set color; The S400 specifically includes: S401, Obtain the power Qt required by the target highway service area in the second preset time period; S402, using Qt to obtain the grid cells corresponding to the target highway service area; S403, obtain the photovoltaic module installation area corresponding to the target highway service area as the target installation area, and divide the target installation area into multiple grid areas using the grid unit; S404, obtain the amount of sunshine in any grid area during the preset time period and the distance between any grid area and the target highway service area; S405, obtain the normalized vegetation index and environmental variables of the green plants in any grid area, and obtain the shaded area and the rate of change of the shaded area in any grid area within a preset time period; the shaded area is the projected area of ​​the green plants in the corresponding grid area. S406. Based on the solar irradiance of the grid area corresponding to the target installation area, the distance between the grid area and the target highway service area, the shaded area of ​​the grid area within a preset time period, and the rate of change of the shaded area, the target grid is obtained as the grid for installing photovoltaic modules.

2. The method according to claim 1, characterized in that, Qt is obtained based on a 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: S101, Obtain a sample dataset, which includes multiple sample data, each sample data including U and D, where U is the ID of the corresponding highway service area, and D is the electricity consumption time series data of the corresponding highway service area within a set historical time period, D={D1, D2, ..., D...} i , ..., D n }, D i This refers to the electricity consumption data corresponding to the i-th time unit, where i ranges from 1 to n, and n is the number of time units corresponding to the set historical segment. i = (DC i DE i Q i ), DC i Let DE be the traffic flow entering the corresponding highway service area within the i-th time unit. i Let Q be the number of electric vehicles entering the corresponding highway service area within the i-th time unit. i This refers to the electricity consumption of the corresponding highway service area during the i-th time unit. S102, input the training sample data of the current batch into the current power prediction model for training, and 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. S103. Based on the prediction results of the current batch and the corresponding actual results, obtain the current loss function value of the current power prediction model, and determine whether the current loss function value meets the preset model training termination condition. If it does, proceed to step S105; otherwise, proceed to step S104. S104, Update the parameters of the current power 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 S102; S105, use the current power prediction model as the trained power prediction model.

4. The method according to claim 3, characterized in that, Qt obtains this through the following steps: S10, Based on the traffic flow and number of electric vehicles of the target highway service area in a historical time period, determine the traffic flow and number of electric vehicles of the target highway service area in a unit time period as the initial power load data. S11, set the counter variable j=1; 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() means rounding up; S13, the current prediction result based on the trained power prediction model is used as the current power consumption data corresponding to the target highway service area, and the current prediction result is added 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; S14, input the current electricity consumption data corresponding to the target highway service area into the trained electricity prediction model to obtain the corresponding current prediction result; S15, set j=j+1, execute S12; S16, obtain Qt based on the predicted electricity consumption corresponding to the current prediction result set.

5. The method according to claim 1, characterized in that, The grid cells corresponding to the target highway service area are obtained by consulting a preset query table. Each row of data in the preset query table includes the highway service area, the electricity consumption of the service area within a preset time period, and the corresponding grid cells.

6. The method according to claim 5, characterized in that, The preset lookup table is obtained based on the following steps: S201, Obtain the electricity required by any reference highway service area within a preset time period; S202, Obtain the photovoltaic module installation area corresponding to any reference highway service area as the corresponding target installation area; S203, the target installation area corresponding to any reference highway service area is divided using a preset initial grid unit to obtain multiple corresponding grid areas; the preset initial grid unit is a grid area suitable for installing a photovoltaic module; S204, Obtain the sunshine duration of any grid area corresponding to any reference highway service area within the preset time period; S205, based on the electricity required by any reference highway service area within a preset time period and the sunshine amount corresponding to each grid area, a target grid area is obtained from multiple grid areas as the grid unit corresponding to the reference highway service area; wherein, the target grid area is a square area composed of at least one initial grid unit, and the electricity generated by the target grid area is greater than or equal to the electricity required by the corresponding reference highway service area within the preset time period. S206. Based on the electricity required by any reference highway service area within a preset time period and the corresponding grid cells, the preset query table is formed.

7. The method according to claim 1, characterized in that, The amount of electricity generated by the photovoltaic modules in any target highway service area during the current monitoring period can be obtained based on the amount of sunshine generated by the photovoltaic modules during the current monitoring period.

8. The method according to claim 1, characterized in that, The target mesh is obtained through the following steps: S161. Based on the solar radiation, distance, shaded area and rate of change of shaded area corresponding to any grid area, determine the scores corresponding to the solar radiation, distance, shaded area and rate of change of shaded area corresponding to the grid area. S162, multiply the scores corresponding to the solar radiation, distance, shaded area and rate of change of shaded area of ​​any grid area by their respective weights, and add the results of the multiplications to obtain the installation weight of the grid area. S163, take the grid region corresponding to the largest of all installation weights as the target grid.

9. A real-time monitoring device for energy carbon emission reduction in highway service areas, characterized in that, The device includes: The first determining module is used to determine the installation location of photovoltaic modules in any target highway service area; The second determining module is used to install photovoltaic modules at the determined installation location, start the photovoltaic modules, and monitor the photovoltaic modules in real time. The power monitoring module is used to obtain, at the current monitoring time, the power generated by the photovoltaic modules of any target highway service area during the current monitoring time period and the power consumed by any target highway service area during the current monitoring time period; the current monitoring time period is the time period between the current monitoring time and the previous monitoring time. The display module is used to obtain the difference between the electricity generated by the photovoltaic modules of any target highway service area during the current monitoring period and the electricity consumed by any target highway service area during the current monitoring period, and to display it visually; wherein, the electricity difference with a negative value is displayed with a set color; The first determining module is specifically used to perform the following operations: S401, Obtain the power Qt required by the target highway service area in the second preset time period; S402, using Qt to obtain the grid cells corresponding to the target highway service area; S403, obtain the photovoltaic module installation area corresponding to the target highway service area as the target installation area, and divide the target installation area into multiple grid areas using the grid unit; S404, obtain the amount of sunshine in any grid area during the preset time period and the distance between any grid area and the target highway service area; S405, obtain the normalized vegetation index and environmental variables of the green plants in any grid area, and obtain the shaded area and the rate of change of the shaded area in any grid area within a preset time period; the shaded area is the projected area of ​​the green plants in the corresponding grid area. S406. Based on the solar irradiance of the grid area corresponding to the target installation area, the distance between the grid area and the target highway service area, the shaded area of ​​the grid area within a preset time period, and the rate of change of the shaded area, the target grid is obtained as the grid for installing photovoltaic modules.

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