Collaborative planning method and management system for new energy

Abstract

The invention relates to the technical field of new energy vehicle charging planning management, and discloses a collaborative planning method and management system for new energy, and the system comprises a new energy planning parameter collection module, a new energy planning analysis module, and a new energy planning management feedback module. Intelligent and accurate analysis of the number of new energy vehicle charging piles required theoretically in the target geographic area is carried out according to the mean value of the charging access times of the new energy vehicle in the target geographic area in combination with an intelligent recognition algorithm and scientifically set standard data of the new energy vehicle charging piles with different charging access times; the planning management quality of the new energy automobile charging pile is improved; the current actual number and the planned new number of the new energy vehicle charging piles in the target geographic area are accurately collected based on numerical analysis, digital processing of the planning management result of the new energy vehicle charging piles in the target geographic area is achieved, and the applicability of planning management of the new energy vehicle charging piles is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of new energy vehicle charging planning management, and in particular to a collaborative planning method and management system for new energy. Background Art

[0002] The new energy vehicle charging management system refers to the various regulations and management measures for the charging process of new energy vehicles. Its purpose is to ensure the safety, efficiency and fairness of new energy vehicle charging and promote the popularization and development of new energy vehicles. The new energy vehicle charging management system generally includes the following aspects: 1. Charging facility construction and management: stipulate the construction standards and management requirements of charging facilities, including the layout, quantity, power, etc. of charging facilities. At the same time, formulate management regulations such as maintenance, inspection and updating of charging facilities to ensure the normal and reliable operation of charging facilities. 2. Charging service management: stipulate the charging standards and methods for charging services, and establish a cooperation mechanism between charging consumers and charging service providers. At the same time, improve the after-sales guarantee mechanism of charging services, solve problems that may arise during charging, and improve user satisfaction. 3. Charging network construction and management: formulate the construction plan and development strategy of the charging network, and promote the interconnection of charging facilities. Establish a supervision mechanism for the charging network to ensure the quality and safety of charging services. 4. Charging equipment standards and technical specifications: formulate technical standards and specifications for charging equipment to ensure the quality and safety of charging equipment. At the same time, promote advanced charging technology to improve charging efficiency and charging speed. Among them, the planning and management of new energy vehicle charging piles has become an important guarantee for ensuring the safe and convenient use of new energy vehicles; however, the existing planning and management of new energy vehicle charging piles cannot achieve scientific and intelligent assessment of the demand for new energy vehicle charging piles in the target geographical area, nor can it dynamically and accurately analyze the number of new energy vehicle charging piles to be newly built in the target geographical area, which reduces the efficiency and rationality of the planning and management of new energy vehicle charging piles.

[0003] A Chinese invention patent application with publication number CN118037489A discloses a charging management method and system for shared charging piles for new energy vehicles. The method collects navigation preference information and charging selection information, establishes a mapping relationship between the owner's personal end and the vehicle end, collects the vehicle's current location information, and calculates and plans to obtain charging planning information; thereby intelligently helping users select charging piles and improving charging efficiency. However, the above technical solutions cannot scientifically evaluate the number of new energy vehicle charging piles in a specific geographical area based on new energy vehicle charging demand parameters. Summary of the invention

[0004] In order to solve the problem that the existing planning and management of new energy vehicle charging piles cannot achieve scientific and intelligent assessment of the demand quantity of new energy vehicle charging piles in the target geographical area, and cannot dynamically and accurately analyze the number of newly built new energy vehicle charging piles in the target geographical area, which reduces the efficiency and rationality of the planning and management of new energy vehicle charging piles, the above purpose is to accurately collect the characteristic information of the target geographical area and the planning time period parameters of the new energy vehicle charging piles, intelligently establish the spatial coordinate information of the target geographical area, accurately search the characteristic information of the new energy vehicle charging visits in the target geographical area, efficiently count the average number of new energy vehicle charging visits in the target geographical area, scientifically analyze the demand quantity of new energy vehicle charging piles in the target geographical area, accurately collect the current number of new energy vehicle charging piles in the target geographical area, accurately plan the number of newly built new energy vehicle charging piles in the target geographical area, and visually feedback the planning and management results of new energy vehicle charging piles in the target geographical area.

[0005] The present invention is implemented by the following technical solution: a collaborative planning method for new energy, the method comprising the following steps:

[0006] S1. Collecting characteristic text data of the target geographic area and planning time period data of new energy vehicle charging piles;

[0007] S2, constructing and processing the spatial coordinate information of the target geographical area for planning new energy vehicle charging piles based on the target geographical area feature text data and the geographical area spatial coordinate data, and generating the target geographical area spatial coordinate data;

[0008] S3, collecting and processing the new energy vehicle charging access information of the target geographical area based on the new energy vehicle charging pile planning time period data and the target geographical area spatial coordinate data, and generating new energy vehicle charging access feature text data of the target geographical area;

[0009] S4, performing statistical processing on the number of new energy vehicle charging visits in the target geographical area according to the new energy vehicle charging pile planning time period data and the new energy vehicle charging visit characteristic text data in the target geographical area, generating statistical data on the number of new energy vehicle charging visits in the target geographical area, and performing average processing on the number of new energy vehicle charging visits in the target geographical area, generating an average number of new energy vehicle charging visits in the target geographical area;

[0010] S5. Analyze and process the number of new energy vehicle charging piles required in the target geographical area according to the average number of new energy vehicle charging visits in the target geographical area and the standard data of new energy vehicle charging piles with different charging visit times, and generate new energy vehicle charging pile demand data in the target geographical area;

[0011] S6. Perform a search process on the current number of new energy vehicle charging piles in the target geographical area according to the characteristic text data of the target geographical area, generate current data on new energy vehicle charging piles in the target geographical area, and perform a new planning process on the number of new energy vehicle charging piles in the target geographical area according to the demand data on new energy vehicle charging piles in the target geographical area, and generate new construction data on new energy vehicle charging piles in the target geographical area;

[0012] S7. Construct the planning and management data of new energy vehicle charging piles in the target geographical area and perform the planning and management result feedback operation of new energy vehicle charging piles.

[0013] Preferably, the operation steps of collecting the target geographical area characteristic text data and the new energy vehicle charging pile planning time period data are as follows:

[0014] S11, collecting location feature text information of the target geographical area online through a data collection dialog box, and generating target geographical area feature text data I; the target geographical area includes any one of an office building geographical area, a shopping mall geographical area, a park geographical area and a school geographical area, and the target geographical area feature text data includes name feature text data, geographical location feature text data and geographical location number feature text data of the target geographical area;

[0015] The planning time length parameters of new energy vehicle charging piles in the target geographical area are collected online through the data collection dialog box, and the planning time period data J of new energy vehicle charging piles is generated, where J = [j1, j2], j1 and j2 represent the planning time starting data and the planning time end data of new energy vehicle charging piles respectively, and the units of j1 and j2 are mainly composed of years, months and days.

[0016] Preferably, the spatial coordinate information construction process of the target geographical area for planning new energy vehicle charging piles is performed based on the target geographical area feature text data and the geographical area spatial coordinate data, and the operation steps for generating the target geographical area spatial coordinate data are as follows:

[0017] S21, establish the geographic area spatial coordinate data set matrix B = (B1, ..., B n ,…,B ι ), n=1,2,3,…,ι; where B n represents the geographic region spatial coordinate data set corresponding to the nth geographic region, ι represents the maximum number of geographic regions; B n =(b n,1 ,…,b n,m ,…,b n,κ ), m=1,2,3,…,κ; where b n,m Represents the geographic area spatial coordinate data set B nThe mth geographic region spatial coordinate data in , κ represents the maximum value of the number of geographic region spatial coordinates, and the geographic region spatial coordinate data includes the longitude, latitude and altitude of the geographic region;

[0018] S22, using the BERT language model algorithm to compare the target geographic area feature text data I with the geographic area spatial coordinate data set B in the geographic area spatial coordinate data set matrix B. n According to the geographic region characteristic character matching, the geographic region spatial coordinate data set B corresponding to the target geographic region characteristic text data I is searched out. n , and construct the target geographic area spatial coordinate data set B'=(b'1,…,b' m ,…,b' κ ), where b' m It represents the spatial coordinate data of the mth target geographical area in the target geographical area, and the spatial coordinate data of the target geographical area includes the longitude, latitude and altitude of the target geographical area.

[0019] Preferably, the operation steps of collecting and processing the new energy vehicle charging access information of the target geographical area based on the new energy vehicle charging pile planning time period data and the target geographical area spatial coordinate data to generate the new energy vehicle charging access feature text data of the target geographical area are as follows:

[0020] S31, using a unified cost search algorithm based on the new energy vehicle charging pile planning time starting point data j1, the new energy vehicle charging pile planning time end point data j2 and the target geographic area spatial coordinate data set B'. m On the new energy vehicle charging platform, all new energy vehicle charging access text information in the target geographic area within the planning period of the new energy vehicle charging pile is searched according to the time and space coordinate characters, and a new energy vehicle charging access feature text data set C = (c1,…,c p ,…,c λ ), p=1,2,3,…,λ; where c p represents the target geographical area new energy vehicle charging access feature text data corresponding to the pth target geographical area new energy vehicle charging access user collected, λ represents the maximum number of target geographical area new energy vehicle charging access users, the target geographical area new energy vehicle charging access feature text data includes the target geographical area new energy vehicle charging access user's access number feature text data, access time point feature text data and access space coordinate feature text data, the new energy vehicle charging platforms include eCharge, Teladian, Xingxing Charging, Youyi Charging and Juneng Charging.

[0021] Preferably, according to the new energy vehicle charging pile planning time period data and the new energy vehicle charging visit characteristic text data of the target geographical area, statistical processing of the new energy vehicle charging visit number in the target geographical area is performed to generate statistical data of the new energy vehicle charging visit number in the target geographical area and perform average processing of the new energy vehicle charging visit number in the target geographical area, and the operation steps of generating the average number of new energy vehicle charging visit number in the target geographical area are as follows:

[0022] S41, based on the new energy vehicle charging pile planning time starting point data j1, the new energy vehicle charging pile planning time end point data j2 in the new energy vehicle charging pile planning time period data J and the target geographical area new energy vehicle charging access feature text data set C p Perform time character matching to search for the total number of new energy vehicle charging visits per day in the target geographic area within the time period from the new energy vehicle charging pile planning time starting point data j1 to the new energy vehicle charging pile planning time end data j2 corresponding to the new energy vehicle charging pile planning time period data J, and generate a new energy vehicle charging visit statistics set D = (d1, ..., d o ,…,d ν ), o=1,2,3,…,ν; where d o represents the statistical data of the number of new energy vehicle charging visits in the target geographical area collected on day o, ν represents the maximum number of daily visits, where ν = j2-j1+1, d o The unit is times per day;

[0023] S42, the target geographical area new energy vehicle charging visit statistics data set D of the target geographical area new energy vehicle charging visit statistics data set D o Perform numerical processing on the average number of visits to charge new energy vehicles in the target geographical area, and measure the average number of visits to charge new energy vehicles in the target geographical area in The unit is times per day.

[0024] Preferably, the number of new energy vehicle charging piles required in the target geographical area is analyzed and processed according to the average number of new energy vehicle charging visits in the target geographical area and the standard data of new energy vehicle charging piles with different charging visit times, and the operation steps of generating the new energy vehicle charging pile demand data in the target geographical area are as follows:

[0025] S51, when the average number of new energy vehicle charging visits in the target geographical area is When the generation is completed, a standard data set of new energy vehicle charging piles with different charging visit times is established E = (e1,…,eg ,…,e θ ), g = 1, 2, 3, ..., θ; where e g represents the standard data of new energy vehicle charging piles with different charging access times corresponding to the type of daily charging access times in the g-th geographical area, ν represents the maximum number of types of daily charging access times in the geographical area, e g The unit is unit, and the standard data of new energy vehicle charging piles with different charging visit times represents the number of charging piles information set based on the daily new energy vehicle charging visit times information standard of the geographical area object;

[0026] S52: average the number of new energy vehicle charging visits in the target geographic area The standard data set E of the new energy vehicle charging pile with different charging visit times and the standard data set E of the new energy vehicle charging pile with different charging visit times g Perform a numerical match on the number of daily charging visits in a geographic area to search for the average number of new energy vehicle charging visits in the target geographic area. The corresponding standard data of new energy vehicle charging piles with different charging access times g , and generate the new energy vehicle charging pile demand data of the target geographical area through data identification xuqiu , execute to generate the new energy vehicle charging pile demand data e in the target geographical area xuqiu The specific steps are as follows:

[0027] S521, initialization, defining the relevant structural parameters as vectors, in the standard data set E of new energy vehicle charging piles with different charging visit times constituting a θ-dimensional optimization problem, the number of charging piles is identified by the sand cat, which represents a 1×θ array of the problem solution, and each variable value a1, a2,…, a θ are all floating point numbers, and each variable value a1 to a θ It is between the lower bound and the upper bound in the search space of the standard data set E of new energy vehicle charging piles with different charging visit times, and the fitness of each charging pile number identification sand cat is obtained by the fitness function of the problem to be solved;

[0028] S522, search for prey, the final parameter and main parameter for controlling the transition between the exploration and development phases is Λ, when |Λ|>1, the charging pile number identification sand cat will be the average number of new energy vehicle charging visits in the target geographical area in the standard data set E of new energy vehicle charging piles with different charging visit times. Corresponding to the standard data of new energy vehicle charging piles with different charging access times gThe numerical matching of the number of daily charging visits in the geographical area is performed. The sand cat search process for identifying the number of charging piles depends on the release of low-frequency noise. Assuming that the sensitivity range of the sand cat for identifying the number of charging piles is from 0 to 2kHz, Inspired by the number of charging piles to identify the auditory characteristics of sand cats, assuming The value is 2, t is the current iteration number, T is the maximum iteration number, and rand(0,1) represents a random number between 0 and 1; in Represents the sensitivity vector; each charging pile number recognition sand cat updates its position according to the best candidate position and the current position and its sensitivity range Π, that is, searches for the average number of new energy vehicle charging visits in the target geographical area in the standard data set E of new energy vehicle charging piles with different charging visit times. The most matching standard data of new energy vehicle charging piles with different charging access times g The position is calculated as follows: Z(t+1)=Π×(Z(t)-rand(0,1)×Z best (t)), where Z(t+1) represents the current position of the sand cat individual in the search space of the standard data set E of new energy vehicle charging piles with different charging visit times in the t+1th iteration of the search prey stage, and Z(t) represents the current position of the sand cat individual in the search space of the standard data set E of new energy vehicle charging piles with different charging visit times in the tth iteration of the search prey stage, and Z best (t) represents the best candidate position of the sand cat in the search space of the standard data set E of new energy vehicle charging piles with different charging visit times in the t-th iteration of the number of charging piles in the prey search stage;

[0030] S523, attack prey, when |Λ|≤1, the charging pile number identification sand cat searches in the search space of the standard data set E of new energy vehicle charging piles with different charging visit times, and generates a random position using the best candidate position and the current position, that is, randomly searches in the search space of the standard data set E of new energy vehicle charging piles with different charging visit times for the average number of new energy vehicle charging visits in the target geographical area. The matching new energy vehicle charging pile standard data of different charging access times g Assuming that the sensitivity range of the charging pile number recognition sand cat is a circle, the roulette method is used to randomly select an angle θ for each charging pile number recognition sand cat, according to the following random position calculation formula: A random position search is performed in the search space of the standard data set E of new energy vehicle charging piles with different charging visit times, wherein Z'(t+1) represents the random position of the sand cat individual in the search space of the standard data set E of new energy vehicle charging piles with different charging visit times in the attack prey stage by identifying the number of charging piles in the t+1th iteration, represents the sensitivity vector, cos(Θ) represents the cosine value of angle Θ, and Z rand Indicates the random position of the charging pile number identification sand cat in the search space of the standard data set E of new energy vehicle charging piles with different charging visit times in the attack prey stage. The random position makes the charging pile number identification sand cat approach and attack the prey, that is, search for the average number of new energy vehicle charging visits in the target geographical area in the search space of the standard data set E of new energy vehicle charging piles with different charging visit times. The matching new energy vehicle charging pile standard data of different charging access times g ;

[0031] S524: When the algorithm meets the maximum number of iterations, output the average number of new energy vehicle charging visits in the target geographic area. The most matching standard data of new energy vehicle charging piles with different charging access times g , otherwise continue to iterate until the maximum number of iterations is met;

[0032] S53, the standard data of the new energy vehicle charging piles with different charging access times output in step S524 g And generate the new energy vehicle charging pile demand data in the target geographical area through data identification xuqiu The target geographic area new energy vehicle charging pile demand data represents the current theoretical demand quantity of new energy vehicle charging piles in the target geographic area, e xuqiu The unit is Taiwan.

[0033] Preferably, the current number of new energy vehicle charging piles in the target geographical area is searched and processed based on the target geographical area characteristic text data, the current data of new energy vehicle charging piles in the target geographical area is generated, and the number of new energy vehicle charging piles in the target geographical area is newly planned and processed with the new energy vehicle charging pile demand data in the target geographical area, and the operation steps of generating the new energy vehicle charging piles newly built data in the target geographical area are as follows:

[0034] S61, inputting the target geographical area characteristic text data I into the search dialog box of the new energy vehicle charging platform, and performing numerical statistical processing on the number of new energy vehicle charging piles in the target geographical area, and measuring the current data e of new energy vehicle charging piles in the target geographical area. dangqian, the current data of new energy vehicle charging piles in the target geographical area represents the current actual number of new energy vehicle charging piles in the target geographical area, e dangqian The unit is Taiwan;

[0035] S62, the new energy vehicle charging pile demand data of the target geographical area xuqiu Current data on new energy vehicle charging stations in the target geographic area dangqian Perform differential processing on the number of charging piles to measure the new construction data of new energy vehicle charging piles in the target geographical area. xinjian The new energy vehicle charging pile construction data in the target geographical area indicates the number of new energy vehicle charging piles that need to be newly constructed in the target geographical area, where e xinjian =e xuqiu -e dangqian , e xinjian The unit is Taiwan.

[0036] Preferably, the steps of constructing the planning and management data of new energy vehicle charging piles in the target geographical area and performing the planning and management result feedback operation of new energy vehicle charging piles are as follows:

[0037] S71, the target geographical area characteristic text data I, the new energy vehicle charging pile planning time period data J, the target geographical area new energy vehicle charging pile demand data e xuqiu 、Current data of new energy vehicle charging piles in the target geographical area dangqian 、New construction data of new energy vehicle charging piles in the target geographical area xinjian Perform data collection and combination processing, and construct the new energy vehicle charging pile planning and management data U in the target geographical area, where U = (I, J, e xuqiu ,e dangqia ,ne xinjian );

[0038] S72, outputting the planning and management data U of the new energy vehicle charging piles in the target geographical area through a display screen to provide feedback on the planning and management results of the new energy vehicle charging piles.

[0039] The present invention also provides a collaborative planning management system for new energy, which is used to implement the collaborative planning method for new energy. The system includes a new energy planning parameter acquisition module, a new energy planning analysis module, and a new energy planning management feedback module;

[0040] The new energy planning parameter acquisition module includes a target geographic area feature information acquisition unit, a new energy vehicle charging pile planning time period acquisition unit, a geographic area spatial coordinate storage unit, and a target geographic area spatial coordinate establishment unit;

[0041] The target geographic area characteristic information acquisition unit acquires the target geographic area characteristic text data through a data acquisition dialog box; the new energy vehicle charging pile planning time period acquisition unit acquires the new energy vehicle charging pile planning time period data through a data acquisition dialog box; the geographic area spatial coordinate storage unit is used to store the geographic area spatial coordinate data; the target geographic area spatial coordinate establishment unit performs spatial coordinate information construction processing on the target geographic area for new energy vehicle charging pile planning based on the target geographic area characteristic text data and the geographic area spatial coordinate data, and generates the target geographic area spatial coordinate data;

[0042] The new energy planning analysis module includes a target geographical area new energy vehicle charging access feature information collection unit, a target geographical area new energy vehicle charging access number statistics unit, a target geographical area new energy vehicle charging access number average value measurement unit, a different charging access number new energy vehicle charging pile standard quantity storage unit, a target geographical area new energy vehicle charging pile demand quantity analysis unit, a target geographical area new energy vehicle charging pile current quantity collection unit, a target geographical area new energy vehicle charging pile new quantity measurement unit;

[0043] The target geographical area new energy vehicle charging access characteristic information collection unit performs charging access information collection and processing of the target geographical area new energy vehicle based on the new energy vehicle charging pile planning time period data and the target geographical area spatial coordinate data in combination with the new energy vehicle charging platform, and generates the target geographical area new energy vehicle charging access characteristic text data; the target geographical area new energy vehicle charging access frequency statistics unit performs charging access frequency statistics processing of the target geographical area new energy vehicle based on the new energy vehicle charging pile planning time period data and the target geographical area new energy vehicle charging access characteristic text data, and generates the target geographical area new energy vehicle charging access frequency statistics; the target geographical area new energy vehicle charging access frequency mean value measurement unit performs charging access frequency mean value processing of the target geographical area new energy vehicle based on the target geographical area new energy vehicle charging access frequency statistics, and generates the target geographical area new energy vehicle charging access frequency mean value; the standard number of new energy vehicle charging piles with different charging access times is stored A unit is used to store standard data of new energy vehicle charging piles with different charging visit times; the target geographical area new energy vehicle charging pile demand quantity analysis unit performs analysis and processing on the number of new energy vehicle charging piles required in the target geographical area according to the average number of new energy vehicle charging visits in the target geographical area and the standard data of new energy vehicle charging piles with different charging visit times, and generates the target geographical area new energy vehicle charging pile demand data; the target geographical area new energy vehicle charging pile current quantity acquisition unit performs search and processing on the current number of new energy vehicle charging piles in the target geographical area according to the target geographical area feature text data combined with the new energy vehicle charging platform, and generates the target geographical area new energy vehicle charging pile current data; the target geographical area new energy vehicle charging pile new construction quantity measurement unit performs planning processing on the number of new energy vehicle charging piles in the target geographical area according to the current data of the target geographical area new energy vehicle charging piles and the target geographical area new energy vehicle charging pile demand data, and generates the target geographical area new energy vehicle charging pile new construction data;

[0044] The new energy planning management feedback module includes a target geographical area new energy vehicle charging pile planning management result construction unit and a target geographical area new energy vehicle charging pile planning management result feedback operation execution unit;

[0045] The target geographical area new energy vehicle charging pile planning and management result construction unit is used to construct the target geographical area new energy vehicle charging pile planning and management data; the target geographical area new energy vehicle charging pile planning and management result feedback operation execution unit executes the new energy vehicle charging pile planning and management result feedback operation based on the target geographical area new energy vehicle charging pile planning and management data combined with the display screen.

[0046] Preferably, the target geographic area characteristic information collection unit collects the location characteristic text information of the target geographic area online through a data collection dialog box, and generates the target geographic area characteristic text data I;

[0047] The new energy vehicle charging pile planning time period collection unit collects the new energy vehicle charging pile planning time length parameters of the target geographical area online through the data collection dialog box, and generates new energy vehicle charging pile planning time period data J, where J = [j1, j2], j1 and j2 represent the new energy vehicle charging pile planning time starting point data and new energy vehicle charging pile planning time end point data respectively, and the units of j1 and j2 are mainly composed of years, months, and days.

[0048] The collaborative planning method and management system for new energy provided by the present invention have the following beneficial effects:

[0049] 1. By using the data collection dialog box to accurately obtain the characteristic information of the target geographical area and the planning time period information of the new energy vehicle charging piles in the target geographical area online, real data support is provided for the scientific planning of the number of new energy vehicle charging piles in the target geographical area; the standard preset geographical area spatial coordinate parameters are combined with the intelligent search algorithm target geographical area characteristic information to scientifically construct the spatial coordinate information of the target geographical area, so as to realize the accurate planning of the new energy vehicle charging pile demand information of the target geographical area location information and improve the scientific nature of the planning and management of new energy vehicle charging piles.

[0050] 2. Intelligent collection of new energy vehicle charging access information in the target geographical area and the planned time period is performed on the new energy vehicle charging platform based on the planning time period parameters of new energy vehicle charging piles and the spatial coordinate information of the target geographical area in combination with an intelligent search algorithm, thereby improving the reliability of planning and management of new energy vehicle charging piles; efficient statistics of the number of new energy vehicle charging visits per day in the planning time period of the target geographical area are performed based on the planning time period information of new energy vehicle charging piles and the characteristic information of new energy vehicle charging visits in the target geographical area, and the mean value of new energy vehicle charging visits in the target geographical area is accurately calculated by combining mean analysis to achieve numerical measurement of the frequency information of new energy vehicle charging visits in the target geographical area; intelligent and accurate analysis of the number of new energy vehicle charging piles required in the target geographical area is performed based on the mean number of new energy vehicle charging visits in the target geographical area combined with an intelligent recognition algorithm and scientifically set standard data of new energy vehicle charging piles with different charging visits, thereby improving the quality of planning and management of new energy vehicle charging piles; based on numerical analysis, the current actual number and planned new number of new energy vehicle charging piles in the target geographical area are accurately collected, and the planning and management results of new energy vehicle charging piles in the target geographical area are digitally processed to improve the applicability of planning and management of new energy vehicle charging piles.

[0051] 3. Based on the characteristic information of the target geographical area, the planning time information of the new energy vehicle charging piles in the target geographical area, the theoretical demand for new energy vehicle charging piles in the target geographical area, the current actual and planned new construction quantity, and combining data combinations, scientifically construct the planning and management data of new energy vehicle charging piles in the target geographical area, so as to realize the accurate and efficient collection of the planning and management result information of new energy vehicle charging piles; the planning and management result information of new energy vehicle charging piles in the target geographical area is independently and timely executed by combining the display screen to feedback the planning and management result of new energy vehicle charging piles, so as to realize efficient visual feedback of the planning and management result of new energy vehicle charging piles. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 A schematic diagram of a module for a collaborative planning and management system for new energy provided by the present invention;

[0053] Figure 2 A flow chart of a collaborative planning method for new energy provided by the present invention. DETAILED DESCRIPTION

[0054] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0055] The embodiment of the collaborative planning method and management system for new energy is as follows:

[0056] Embodiment 1:

[0057] See also Figure 1 - Figure 2 , a collaborative planning method for new energy, the method comprising the following steps:

[0058] S1. Collecting characteristic text data of the target geographic area and planning time period data of new energy vehicle charging piles;

[0059] S2. Construct and process the spatial coordinate information of the target geographical area for planning new energy vehicle charging piles based on the target geographical area feature text data and the geographical area spatial coordinate data to generate the target geographical area spatial coordinate data;

[0060] S3, collecting and processing the new energy vehicle charging access information in the target geographical area based on the new energy vehicle charging pile planning time period data and the target geographical area spatial coordinate data, and generating new energy vehicle charging access feature text data in the target geographical area;

[0061] S4. Perform statistical processing on the number of new energy vehicle charging visits in the target geographical area based on the new energy vehicle charging pile planning time period data and the new energy vehicle charging visit feature text data in the target geographical area to generate statistical data on the number of new energy vehicle charging visits in the target geographical area and perform average processing on the number of new energy vehicle charging visits in the target geographical area to generate the average number of new energy vehicle charging visits in the target geographical area;

[0062] S5. Analyze and process the number of new energy vehicle charging piles required in the target geographical area according to the average number of new energy vehicle charging visits in the target geographical area and the standard data of new energy vehicle charging piles with different charging visit times, and generate new energy vehicle charging pile demand data in the target geographical area;

[0063] S6. Perform search processing on the current number of new energy vehicle charging piles in the target geographical area based on the characteristic text data of the target geographical area, generate current data on new energy vehicle charging piles in the target geographical area, and perform planning processing on the number of new energy vehicle charging piles in the target geographical area based on the demand data on new energy vehicle charging piles in the target geographical area, and generate new construction data on new energy vehicle charging piles in the target geographical area;

[0064] S7. Construct the planning and management data of new energy vehicle charging piles in the target geographical area and perform the planning and management result feedback operation of new energy vehicle charging piles.

[0065] For further information, see Figure 1 - Figure 2 ,The steps for collecting the feature text data of the target geographic area and the planning time period data of new energy vehicle charging piles are as follows:

[0066] S11, collecting location feature text information of the target geographical area online through a data collection dialog box, and generating target geographical area feature text data I; the target geographical area includes any one of an office building geographical area, a shopping mall geographical area, a park geographical area and a school geographical area, and the target geographical area feature text data includes name feature text data, geographical location feature text data and geographical location number feature text data of the target geographical area;

[0067] The planning time length parameters of new energy vehicle charging piles in the target geographical area are collected online through the data collection dialog box, and the planning time period data J of new energy vehicle charging piles is generated, where J = [j1, j2], j1 and j2 represent the planning time starting data and the planning time end data of new energy vehicle charging piles respectively, and the units of j1 and j2 are mainly composed of years, months and days.

[0068] The spatial coordinate information of the target geographical area for new energy vehicle charging pile planning is constructed and processed based on the target geographical area feature text data and the geographical area spatial coordinate data. The operation steps for generating the target geographical area spatial coordinate data are as follows:

[0069] S21, establish the geographic area spatial coordinate data set matrix B = (B1, ..., B n ,…,B ι ), n=1,2,3,…,ι; where B n represents the geographic region spatial coordinate data set corresponding to the nth geographic region, ι represents the maximum number of geographic regions; B n =(b n,1 ,…,b n,m ,…,b n,κ ), m=1,2,3,…,κ; where b n,m Represents the geographic area spatial coordinate data set B n The mth geographic region spatial coordinate data in , κ represents the maximum value of the number of geographic region spatial coordinates, and the geographic region spatial coordinate data includes the longitude, latitude and altitude of the geographic region;

[0070] S22, using the BERT language model algorithm to compare the target geographic area feature text data I with the geographic area spatial coordinate data set B in the geographic area spatial coordinate data set matrix B. n According to the geographic region characteristic character matching, search for the geographic region spatial coordinate data set B corresponding to the target geographic region characteristic text data I n , and construct the target geographic area spatial coordinate data set B'=(b'1,…,b' m ,…,b' κ ), where b' m It represents the spatial coordinate data of the mth target geographical area in the target geographical area, and the spatial coordinate data of the target geographical area includes the longitude, latitude and altitude of the target geographical area.

[0071] Through the cooperation between the target geographic area characteristic information collection unit and the new energy vehicle charging pile planning time period collection unit, the data collection dialog box is used to accurately obtain the target geographic area characteristic information and the new energy vehicle charging pile planning time period information of the target geographic area online, so as to provide real data support for the scientific planning of the number of new energy vehicle charging piles in the target geographic area; the geographic area spatial coordinate storage unit and the target geographic area spatial coordinate establishment unit cooperate with each other, and the standard preset geographic area spatial coordinate parameters are combined with the target geographic area characteristic information of the intelligent search algorithm to scientifically construct the spatial coordinate information of the target geographic area, so as to realize the accurate planning of the new energy vehicle charging pile demand information of the target geographic area location information, and improve the scientific nature of the planning and management of new energy vehicle charging piles.

[0072] For further information, see Figure 1 - Figure 2 , based on the new energy vehicle charging pile planning time period data and the target geographic area spatial coordinate data, the new energy vehicle charging access information collection and processing of the target geographic area is performed to generate the new energy vehicle charging access feature text data of the target geographic area as follows:

[0073] S31, using a unified cost search algorithm based on the new energy vehicle charging pile planning time period data J, the new energy vehicle charging pile planning time start data j1, the new energy vehicle charging pile planning time end data j2 and the target geographic area spatial coordinate data set B' of the target geographic area spatial coordinate data b' m On the new energy vehicle charging platform, all new energy vehicle charging access text information in the target geographic area within the planning period of the new energy vehicle charging pile is searched according to the time and space coordinate characters, and a new energy vehicle charging access feature text data set C = (c1,…,c p ,…,c λ ), p=1,2,3,…,λ; where c p represents the target geographical area new energy vehicle charging access feature text data corresponding to the pth target geographical area new energy vehicle charging access user collected, λ represents the maximum number of target geographical area new energy vehicle charging access users, the target geographical area new energy vehicle charging access feature text data includes the target geographical area new energy vehicle charging access user's access number feature text data, access time point feature text data and access space coordinate feature text data, the new energy vehicle charging platforms include eCharge, Teladian, Xingxing Charging, Youyi Charging and Juneng Charging.

[0074] According to the new energy vehicle charging pile planning time period data and the new energy vehicle charging visit feature text data of the target geographical area, the new energy vehicle charging visit number statistical processing is performed in the target geographical area, the new energy vehicle charging visit number statistical data of the target geographical area is generated, and the new energy vehicle charging visit number average processing is performed in the target geographical area. The operation steps for generating the average number of new energy vehicle charging visit numbers in the target geographical area are as follows:

[0075] S41, based on the new energy vehicle charging pile planning time starting point data j1, the new energy vehicle charging pile planning time end point data j2 in the new energy vehicle charging pile planning time period data J and the target geographic area new energy vehicle charging access feature text data set C in the target geographic area new energy vehicle charging access feature text data c pPerform time character matching to search for the total number of new energy vehicle charging visits per day in the target geographic area during the time period from the new energy vehicle charging pile planning time starting point data j1 to the new energy vehicle charging pile planning time end data j2 corresponding to the new energy vehicle charging pile planning time period data J, and generate a statistical data set D = (d1,…,d o ,…,d ν ), o=1,2,3,…,ν; where d o represents the statistical data of the number of new energy vehicle charging visits in the target geographical area collected on day o, ν represents the maximum number of daily visits, where ν = j2-j1+1, d o The unit is times per day;

[0076] S42, the target geographic area new energy vehicle charging visit statistics data d in the target geographic area new energy vehicle charging visit statistics set D o Perform numerical processing on the average number of visits to charge new energy vehicles in the target geographical area, and measure the average number of visits to charge new energy vehicles in the target geographical area in The unit is times per day.

[0077] According to the average number of new energy vehicle charging visits in the target geographical area and the standard data of new energy vehicle charging piles with different charging visit times, the number of new energy vehicle charging piles required in the target geographical area is analyzed and processed, and the operation steps for generating the demand data of new energy vehicle charging piles in the target geographical area are as follows:

[0078] S51, when the average number of new energy vehicle charging visits in the target geographic area When the generation is completed, a standard data set of new energy vehicle charging piles with different charging visit times is established E = (e1,…,e g ,…,e θ ), g = 1, 2, 3, ..., θ; where e g represents the standard data of new energy vehicle charging piles with different charging access times corresponding to the type of daily charging access times in the g-th geographical area, ν represents the maximum number of types of daily charging access times in the geographical area, e g The unit is pcs. The standard data of new energy vehicle charging piles with different charging visit times represents the number of charging piles information set based on the daily new energy vehicle charging visit times information standard of the geographic area object;

[0079] S52: average number of new energy vehicle charging visits in the target geographic area The standard data set E of new energy vehicle charging piles with different charging visit times is compared with the standard data set E of new energy vehicle charging piles with different charging visit times. gPerform numerical matching of the number of daily charging visits in the geographic area and search for the average number of new energy vehicle charging visits in the target geographic area Standard data of new energy vehicle charging piles with different charging visit times g , and generate the new energy vehicle charging pile demand data of the target geographical area through data identification xuqiu , execute to generate the demand data of new energy vehicle charging piles in the target geographical area xuqiu The specific steps are as follows:

[0080] S521, initialization, defining the relevant structural parameters as vectors, in the θ-dimensional optimization problem formed by the standard data set E of new energy vehicle charging piles with different charging visit times, the number of charging piles is identified by the sand cat, which represents the 1×θ array of the problem solution, and each variable value a1, a2,…, a θ are all floating point numbers, and each variable value a1 to a θ It is between the lower bound and the upper bound in the search space of the standard data set E of new energy vehicle charging piles with different charging visit times. The fitness of the sand cat for each charging pile number identification is obtained through the fitness function of the problem to be solved;

[0081] S522, search for prey, the final parameter and main parameter controlling the transition between exploration and development phases is Λ. When |Λ|>1, the number of charging piles to identify the sand cat will be the average number of new energy vehicle charging visits in the target geographical area in the standard data set E of new energy vehicle charging piles with different charging visit times. Standard data of new energy vehicle charging piles corresponding to different charging visit times g The numerical matching of the number of daily charging visits in the geographical area is performed. The sand cat search process for identifying the number of charging piles depends on the release of low-frequency noise. Assuming that the sensitivity range of the sand cat for identifying the number of charging piles is from 0 to 2kHz, Inspired by the number of charging piles to identify the auditory characteristics of sand cats, assuming The value is 2, t is the current iteration number, T is the maximum iteration number, and rand(0,1) represents a random number between 0 and 1; in Represents the sensitivity vector; each charging pile number recognition sand cat updates its position according to the best candidate position and the current position and its sensitivity range Π, that is, searches for the average number of new energy vehicle charging visits in the target geographical area in the standard data set E of new energy vehicle charging piles with different charging visit times. The most matching standard data of new energy vehicle charging piles with different charging visit times g The position is calculated as follows:

[0082] Z(t+1)=Π×(Z(t)-rand(0,1)×Zbest (t)), where Z(t+1) represents the current position of the sand cat individual in the search space of the standard data set E of new energy vehicle charging piles with different charging visits in the t+1th iteration of the search for prey stage, and Z(t) represents the current position of the sand cat individual in the search space of the standard data set E of new energy vehicle charging piles with different charging visits in the tth iteration of the search for prey stage, Z best (t) represents the best candidate position of the sand cat in the search space of the standard data set E of new energy vehicle charging piles with different charging visit times in the t-th iteration of the number of charging piles in the prey search stage;

[0083] S523, attack prey, when |Λ|≤1, the charging pile number identification sand cat searches in the search space of the standard data set E of new energy vehicle charging piles with different charging visit times, and generates a random position using the best candidate position and the current position, that is, randomly searches in the search space of the standard data set E of new energy vehicle charging piles with different charging visit times for the average number of new energy vehicle charging visits in the target geographical area Standard data of new energy vehicle charging piles with different charging access times g Assuming that the sensitivity range of the charging pile number recognition sand cat is a circle, the roulette method is used to randomly select an angle θ for each charging pile number recognition sand cat, according to the following random position calculation formula: A random position search is performed in the search space of the standard data set E of new energy vehicle charging piles with different charging visit times, where Z'(t+1) represents the random position of the sand cat individual in the search space of the standard data set E of new energy vehicle charging piles with different charging visit times in the attack prey stage. represents the sensitivity vector, cos(Θ) represents the cosine value of angle Θ, and Z rand = represents the random position of the charging pile number recognition sand cat in the search space of the standard data set E of new energy vehicle charging piles with different charging visit times in the attack prey stage. The random position makes the charging pile number recognition sand cat approach and attack the prey, that is, search for the average number of new energy vehicle charging visits in the target geographical area in the search space of the standard data set E of new energy vehicle charging piles with different charging visit times. Standard data of new energy vehicle charging piles with different charging access times g ;

[0084] S524, when the algorithm meets the maximum number of iterations, output the standard data e of new energy vehicle charging piles with different charging visit times that best matches the average number of new energy vehicle charging visits D in the target geographical area. g , otherwise continue to iterate until the maximum number of iterations is met;

[0085] S53, the standard data of new energy vehicle charging piles with different charging access times output in step S524 g And generate the new energy vehicle charging pile demand data in the target geographical area through data identification xuqiu ,The demand data of new energy vehicle charging piles in the target geographical area represents the current theoretical demand number of new energy vehicle charging piles in the target geographical area, e xuqiu The unit is Taiwan.

[0086] The current number of new energy vehicle charging piles in the target geographical area is searched and processed based on the characteristic text data of the target geographical area, and the current data of new energy vehicle charging piles in the target geographical area is generated. The new energy vehicle charging pile demand data of the target geographical area is used to perform new planning processing on the number of new energy vehicle charging piles in the target geographical area. The operation steps for generating the new data of new energy vehicle charging piles in the target geographical area are as follows:

[0087] S61, input the target geographic area characteristic text data I into the search dialog box of the new energy vehicle charging platform, and perform numerical statistical processing on the number of new energy vehicle charging piles in the target geographic area, and measure the current data e of new energy vehicle charging piles in the target geographic area. dangqian ,The current data of new energy vehicle charging piles in the target geographical area represents the current actual number of new energy vehicle charging piles in the target geographical area, e dangqian The unit is Taiwan;

[0088] S62. The target geographic area's new energy vehicle charging pile demand data xuqiu Current data on new energy vehicle charging stations in the target geographic area dangqian Perform differential processing on the number of charging piles to measure the new construction data of new energy vehicle charging piles in the target geographical area. xinjian The new construction data of new energy vehicle charging piles in the target geographical area indicates the number of new energy vehicle charging piles that need to be newly planned in the target geographical area, where e xinjian =e xuqiu -e dangqian , e xinjian The unit is Taiwan.

[0089] Through the target geographical area new energy vehicle charging visit characteristic information collection unit, based on the new energy vehicle charging pile planning time period parameters and the target geographical area spatial coordinate information combined with the intelligent search algorithm, the target geographical area and the planning time period of new energy vehicle charging visit information are intelligently collected on the new energy vehicle charging platform, thereby improving the reliability of new energy vehicle charging pile planning and management; the target geographical area new energy vehicle charging visit number statistics unit and the target geographical area new energy vehicle charging visit number average measurement unit cooperate with each other, according to the new energy vehicle charging pile planning time period information and the target geographical area new energy vehicle charging visit characteristic information, the target geographical area daily new energy vehicle charging visit number within the planning time period is efficiently counted, combined with the mean analysis to accurately count the target geographical area new energy vehicle charging visit average, to achieve numerical measurement of the target geographical area new energy vehicle charging visit Frequency information; the standard quantity storage unit for new energy vehicle charging piles with different charging visit times and the demand quantity analysis unit for new energy vehicle charging piles in the target geographical area cooperate with each other, and the theoretical demand quantity of new energy vehicle charging piles in the target geographical area is intelligently and accurately analyzed according to the average number of new energy vehicle charging visits in the target geographical area combined with the intelligent recognition algorithm and the scientifically set standard data of new energy vehicle charging piles with different charging visit times, so as to improve the quality of planning and management of new energy vehicle charging piles; the current quantity collection unit for new energy vehicle charging piles in the target geographical area and the newly built quantity measurement unit for new energy vehicle charging piles in the target geographical area cooperate with each other, and the current actual quantity and planned new quantity of new energy vehicle charging piles in the target geographical area are accurately collected based on numerical analysis, so as to realize the digital processing of the planning and management results of new energy vehicle charging piles in the target geographical area, and improve the applicability of planning and management of new energy vehicle charging piles.

[0090] For further information, see Figure 1 - Figure 2 The steps for constructing the planning and management data of new energy vehicle charging piles in the target geographical area and performing the planning and management result feedback operation of new energy vehicle charging piles are as follows:

[0091] S71, target geographic area feature text data I, new energy vehicle charging pile planning time period data J, target geographic area new energy vehicle charging pile demand data e xuqiu 、Current data of new energy vehicle charging piles in the target geographical area dangqian 、Data on new construction of new energy vehicle charging piles in target geographical areas xinjian Perform data collection and combination processing, and construct the new energy vehicle charging pile planning and management data U in the target geographical area, where U = (I, J, e xuqiu ,e dangqian ,e xinjian );

[0092] S72, outputting the planning and management data U of the new energy vehicle charging piles in the target geographical area through a display screen to provide feedback on the planning and management results of the new energy vehicle charging piles.

[0093] Through the target geographical area new energy vehicle charging pile planning and management result construction unit, based on the target geographical area characteristic information, the target geographical area new energy vehicle charging pile planning time information, the target geographical area new energy vehicle charging pile theoretical demand, the current actual and planned new construction quantity and combined with data combination, the target geographical area new energy vehicle charging pile planning and management data is scientifically constructed to achieve accurate and efficient collection of new energy vehicle charging pile planning and management result information; the target geographical area new energy vehicle charging pile planning and management result feedback operation execution unit, the target geographical area new energy vehicle charging pile planning and management result information by combining the display screen to autonomously and timely execute the new energy vehicle charging pile planning and management result feedback operation, to achieve efficient visual feedback of new energy vehicle charging pile planning and management results.

[0094] Embodiment 2:

[0095] See also Figure 1 - Figure 2 , a collaborative planning management system for new energy, used to implement a collaborative planning method for new energy, the system includes a new energy planning parameter acquisition module, a new energy planning analysis module, and a new energy planning management feedback module;

[0096] The new energy planning parameter acquisition module includes a target geographic area feature information acquisition unit, a new energy vehicle charging pile planning time period acquisition unit, a geographic area spatial coordinate storage unit, and a target geographic area spatial coordinate establishment unit;

[0097] The target geographic area characteristic information collection unit collects the target geographic area characteristic text data through the data collection dialog box; the new energy vehicle charging pile planning time period collection unit collects the new energy vehicle charging pile planning time period data through the data collection dialog box; the geographic area spatial coordinate storage unit is used to store the geographic area spatial coordinate data; the target geographic area spatial coordinate establishment unit constructs and processes the spatial coordinate information of the target geographic area for the new energy vehicle charging pile planning based on the target geographic area characteristic text data and the geographic area spatial coordinate data, and generates the target geographic area spatial coordinate data;

[0098] The new energy planning analysis module includes a target geographic area new energy vehicle charging access feature information collection unit, a target geographic area new energy vehicle charging access number statistics unit, a target geographic area new energy vehicle charging access number average value measurement unit, a target geographic area new energy vehicle charging pile standard number storage unit with different charging access numbers, a target geographic area new energy vehicle charging pile demand number analysis unit, a target geographic area new energy vehicle charging pile current number collection unit, and a target geographic area new energy vehicle charging pile new number measurement unit;

[0099] The target geographic area new energy vehicle charging visit characteristic information collection unit performs charging visit information collection and processing of the target geographic area new energy vehicle based on the new energy vehicle charging pile planning time period data and the target geographic area spatial coordinate data in combination with the new energy vehicle charging platform, and generates the target geographic area new energy vehicle charging visit characteristic text data; the target geographic area new energy vehicle charging visit frequency statistics unit performs charging visit frequency statistics processing of the target geographic area new energy vehicle based on the new energy vehicle charging pile planning time period data and the target geographic area new energy vehicle charging visit characteristic text data, and generates the target geographic area new energy vehicle charging visit frequency statistics; the target geographic area new energy vehicle charging visit frequency mean value measurement unit performs charging visit frequency mean value processing of the target geographic area new energy vehicle based on the target geographic area new energy vehicle charging visit frequency statistics, and generates the target geographic area new energy vehicle charging visit frequency mean value; the target geographic area new energy vehicle charging pile standard quantity storage unit with different charging visit times, Used to store standard data of new energy vehicle charging piles with different charging visit times; a target geographical area new energy vehicle charging pile demand quantity analysis unit, which analyzes and processes the number of new energy vehicle charging piles required in the target geographical area according to the average number of new energy vehicle charging visits in the target geographical area and the standard data of new energy vehicle charging piles with different charging visit times, and generates the target geographical area new energy vehicle charging pile demand data; a target geographical area new energy vehicle charging pile current quantity acquisition unit, which searches and processes the current number of new energy vehicle charging piles in the target geographical area according to the target geographical area feature text data combined with the new energy vehicle charging platform, and generates the target geographical area new energy vehicle charging pile current data; a target geographical area new energy vehicle charging pile new construction quantity measurement unit, which performs the target geographical area new energy vehicle charging pile quantity new construction planning processing according to the target geographical area new energy vehicle charging pile current data and the target geographical area new energy vehicle charging pile demand data, and generates the target geographical area new energy vehicle charging pile new construction data;

[0100] The new energy planning management feedback module includes a target geographical area new energy vehicle charging pile planning management result construction unit and a target geographical area new energy vehicle charging pile planning management result feedback operation execution unit;

[0101] The target geographical area new energy vehicle charging pile planning and management result construction unit is used to construct the target geographical area new energy vehicle charging pile planning and management data; the target geographical area new energy vehicle charging pile planning and management result feedback operation execution unit executes the new energy vehicle charging pile planning and management result feedback operation based on the target geographical area new energy vehicle charging pile planning and management data combined with the display screen.

[0102] Further, the target geographic area characteristic information collection unit collects the location characteristic text information of the target geographic area online through the data collection dialog box, and generates the target geographic area characteristic text data I;

[0103] The new energy vehicle charging pile planning time period collection unit collects the new energy vehicle charging pile planning time length parameters of the target geographical area online through the data collection dialog box, and generates new energy vehicle charging pile planning time period data J, where J = [j1, j2], j1 and j2 represent the new energy vehicle charging pile planning time starting point data and new energy vehicle charging pile planning time end point data respectively, and the units of j1 and j2 are mainly composed of years, months, and days.

[0104] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A collaborative planning method for new energy, characterized in that: The method comprises the following steps: S1. Collecting characteristic text data of the target geographic area and planning time period data of new energy vehicle charging piles; S2, constructing and processing the spatial coordinate information of the target geographical area for planning new energy vehicle charging piles based on the target geographical area feature text data and the geographical area spatial coordinate data, and generating the target geographical area spatial coordinate data; S3, collecting and processing the new energy vehicle charging access information of the target geographical area based on the new energy vehicle charging pile planning time period data and the target geographical area spatial coordinate data, and generating new energy vehicle charging access feature text data of the target geographical area; S4, performing statistical processing on the number of new energy vehicle charging visits in the target geographical area according to the new energy vehicle charging pile planning time period data and the new energy vehicle charging visit characteristic text data in the target geographical area, generating statistical data on the number of new energy vehicle charging visits in the target geographical area, and performing average processing on the number of new energy vehicle charging visits in the target geographical area, generating an average number of new energy vehicle charging visits in the target geographical area; S5. Analyze and process the number of new energy vehicle charging piles required in the target geographical area according to the average number of new energy vehicle charging visits in the target geographical area and the standard data of new energy vehicle charging piles with different charging visit times, and generate new energy vehicle charging pile demand data in the target geographical area; S6. Perform a search process on the current number of new energy vehicle charging piles in the target geographical area according to the characteristic text data of the target geographical area, generate current data on new energy vehicle charging piles in the target geographical area, and perform a new planning process on the number of new energy vehicle charging piles in the target geographical area according to the demand data on new energy vehicle charging piles in the target geographical area, and generate new construction data on new energy vehicle charging piles in the target geographical area; S7. Construct the planning and management data of new energy vehicle charging piles in the target geographical area and perform the planning and management result feedback operation of new energy vehicle charging piles.

2. A collaborative planning method for new energy according to claim 1, characterized in that: The S1 comprises the following steps: S11, collecting location feature text information of the target geographic area online through a data collection dialog box, and generating target geographic area feature text data I; The planning time length parameters of new energy vehicle charging piles in the target geographical area are collected online through the data collection dialog box, and the planning time period data J of new energy vehicle charging piles is generated, where J = [j1, j2], j1 and j2 represent the planning time starting data and the planning time end data of new energy vehicle charging piles respectively, and the units of j1 and j2 are mainly composed of years, months and days.

3. A collaborative planning method for new energy according to claim 2, characterized in that: The S2 comprises the following steps: S21, establish the geographic area spatial coordinate data set matrix B = (B1, ..., B n ,…,B ι ), n=1,2,3,…,ι; where B n represents the geographic region spatial coordinate data set corresponding to the nth geographic region, ι represents the maximum number of geographic regions; B n =(b n,1 ,…,b n,m ,…,b n,κ ), m=1,2,3,…,κ; where b n,m Represents the geographic area spatial coordinate data set B n The spatial coordinate data of the mth geographic region, κ represents the maximum number of spatial coordinates of the geographic region; S22, using the BERT language model algorithm to compare the I with the B in the B n According to the geographical area characteristic character matching, search for the B corresponding to the I n , and construct the target geographic area spatial coordinate data set B'=(b'1,…,b' m ,…,b' κ ), where b' m Represents the spatial coordinate data of the mth target geographical area in the target geographical area.

4. A collaborative planning method for new energy according to claim 3, characterized in that: The S3 comprises the following steps: S31, using a unified cost search algorithm based on j1 ​​in J, j2 and b' in B' m On the new energy vehicle charging platform, all new energy vehicle charging access text information in the target geographic area within the planning period of the new energy vehicle charging pile is searched according to the time and space coordinate characters, and a new energy vehicle charging access feature text data set C = (c1,…,c p ,…,c λ ), p=1,2,3,…,λ; where c p represents the target geographical area new energy vehicle charging access feature text data corresponding to the pth target geographical area new energy vehicle charging access user collected, and λ represents the maximum number of new energy vehicle charging access users in the target geographical area.

5. A collaborative planning method for new energy according to claim 4, characterized in that: The S4 comprises the following steps: S41, based on j1, j2 in J and c in C p Perform time character matching to search for the total number of visits to new energy vehicles for charging per day in the target geographic area during the time period from j1 to j2 corresponding to J, and generate a statistical data set D = (d1, ..., d o ,…,d ν ), o=1,2,3,…,ν; where d o represents the statistical data of the number of new energy vehicle charging visits in the target geographical area collected on day o, ν represents the maximum number of daily visits, where ν = j2-j1+1, d o The unit is times per day; S42, for the d in the D o Perform numerical processing on the average number of visits to charge new energy vehicles in the target geographical area, and measure the average number of visits to charge new energy vehicles in the target geographical area in The unit is times per day.

6. A collaborative planning method for new energy according to claim 5, characterized in that: The S5 comprises the following steps: S51, when the When the generation is completed, a standard data set of new energy vehicle charging piles with different charging visit times is established E = (e1,…,e g ,…,e θ ), g = 1, 2, 3, ..., θ; where e g represents the standard data of new energy vehicle charging piles with different charging access times corresponding to the type of daily charging access times in the g-th geographical area, ν represents the maximum number of types of daily charging access times in the geographical area, e g The unit is Taiwan; S52, the With the E in the e g Perform a numerical match on the number of daily charging visits in a geographic area to search for the The corresponding e g , and generate the new energy vehicle charging pile demand data of the target geographical area through data identification xuqiu , execute to generate the new energy vehicle charging pile demand data e in the target geographical area xuqiu The specific steps are as follows: S521, initialization, defining the relevant structural parameters as vectors, in the E-constituted θ-dimensional optimization problem, the number of charging piles is identified by the sand cat, which represents the 1×θ array of the problem solution, and each variable value a1, a2,…, a θ are all floating point numbers, and each variable value a1 to a θ It is located between the lower bound and the upper bound in the E search space, and the fitness of each charging pile number identification sand cat is obtained by the fitness function of the problem to be solved; S522, search for prey, the final parameter and main parameter for controlling the transition between the exploration and development phases is Λ, when |Λ|>1, the number of charging piles identifies the sand cat in the E search space. Corresponding to the e g Perform numerical matching of the number of daily charging visits in a geographic area; each charging pile number identification sand cat updates its own position according to the best candidate position and the current position and its sensitivity range, that is, searches for the position that matches the one in the E search space. The best match for the e g location; S523, attack prey, when |Λ|≤1, the charging pile number identification sand cat searches in the E search space, and generates a random position using the best candidate position and the current position, that is, randomly searches for the prey in the E search space. Match the e g Assuming that the sensitivity range of the charging pile number recognition sand cat is a circle, the roulette method is used to randomly select an angle for each charging pile number recognition sand cat to search for a random position in the E search space; the random position makes the charging pile number recognition sand cat approach and attack the prey, that is, search for the prey that is consistent with the prey in the E search space. Match the e g ; S524, when the algorithm meets the maximum number of iterations, output The best match for the e g , otherwise continue to iterate until the maximum number of iterations is met; S53, the output in step S524 g And generate the new energy vehicle charging pile demand data in the target geographical area through data identification xuqiu The target geographic area new energy vehicle charging pile demand data represents the current theoretical demand quantity of new energy vehicle charging piles in the target geographic area, e xuqiu The unit is Taiwan.

7. A collaborative planning method for new energy according to claim 6, characterized in that: The S6 comprises the following steps: S61, inputting the I into the search dialog box of the new energy vehicle charging platform, and performing numerical statistical processing on the number of new energy vehicle charging piles in the target geographical area, and measuring the current data of new energy vehicle charging piles in the target geographical area. dangqian , where e dangqian The unit is Taiwan; S62, the e xuqiu With the e dangqian Perform differential processing on the number of charging piles to measure the new construction data of new energy vehicle charging piles in the target geographical area. xinjian , where e xinjian The unit is Taiwan.

8. A collaborative planning method for new energy according to claim 7, characterized in that: The S7 comprises the following steps: S71, the I, J, e xuqiu 、 dangqian 、 xinjian Carry out data collection and combination processing, and construct the new energy vehicle charging pile planning and management data U in the target geographical area; S72, outputting the planning and management results of new energy vehicle charging piles through the display screen.

9. A collaborative planning management system for new energy, used to implement a collaborative planning method for new energy as claimed in any one of claims 1 to 8, characterized in that: The system includes a new energy planning parameter acquisition module, a new energy planning analysis module, and a new energy planning management feedback module; The new energy planning parameter acquisition module includes a target geographic area feature information acquisition unit, a new energy vehicle charging pile planning time period acquisition unit, a geographic area spatial coordinate storage unit, and a target geographic area spatial coordinate establishment unit; The target geographic area characteristic information acquisition unit acquires the target geographic area characteristic text data through a data acquisition dialog box; the new energy vehicle charging pile planning time period acquisition unit acquires the new energy vehicle charging pile planning time period data through a data acquisition dialog box; the geographic area spatial coordinate storage unit is used to store the geographic area spatial coordinate data; the target geographic area spatial coordinate establishment unit performs spatial coordinate information construction processing on the target geographic area for new energy vehicle charging pile planning based on the target geographic area characteristic text data and the geographic area spatial coordinate data, and generates the target geographic area spatial coordinate data; The new energy planning analysis module includes a target geographical area new energy vehicle charging access feature information collection unit, a target geographical area new energy vehicle charging access number statistics unit, a target geographical area new energy vehicle charging access number average value measurement unit, a different charging access number new energy vehicle charging pile standard quantity storage unit, a target geographical area new energy vehicle charging pile demand quantity analysis unit, a target geographical area new energy vehicle charging pile current quantity collection unit, a target geographical area new energy vehicle charging pile new quantity measurement unit; The target geographical area new energy vehicle charging access characteristic information collection unit performs charging access information collection and processing of the target geographical area new energy vehicle based on the new energy vehicle charging pile planning time period data and the target geographical area spatial coordinate data in combination with the new energy vehicle charging platform, and generates the target geographical area new energy vehicle charging access characteristic text data; the target geographical area new energy vehicle charging access frequency statistics unit performs charging access frequency statistics processing of the target geographical area new energy vehicle based on the new energy vehicle charging pile planning time period data and the target geographical area new energy vehicle charging access characteristic text data, and generates the target geographical area new energy vehicle charging access frequency statistics; the target geographical area new energy vehicle charging access frequency mean value measurement unit performs charging access frequency mean value processing of the target geographical area new energy vehicle based on the target geographical area new energy vehicle charging access frequency statistics, and generates the target geographical area new energy vehicle charging access frequency mean value; the standard number of new energy vehicle charging piles with different charging access times is stored A unit is used to store standard data of new energy vehicle charging piles with different charging visit times; the target geographical area new energy vehicle charging pile demand quantity analysis unit performs analysis and processing on the number of new energy vehicle charging piles required in the target geographical area according to the average number of new energy vehicle charging visits in the target geographical area and the standard data of new energy vehicle charging piles with different charging visit times, and generates the target geographical area new energy vehicle charging pile demand data; the target geographical area new energy vehicle charging pile current quantity acquisition unit performs search and processing on the current number of new energy vehicle charging piles in the target geographical area according to the target geographical area feature text data combined with the new energy vehicle charging platform, and generates the target geographical area new energy vehicle charging pile current data; the target geographical area new energy vehicle charging pile new construction quantity measurement unit performs planning processing on the number of new energy vehicle charging piles in the target geographical area according to the current data of the target geographical area new energy vehicle charging piles and the target geographical area new energy vehicle charging pile demand data, and generates the target geographical area new energy vehicle charging pile new construction data; The new energy planning management feedback module includes a target geographical area new energy vehicle charging pile planning management result construction unit and a target geographical area new energy vehicle charging pile planning management result feedback operation execution unit; The target geographical area new energy vehicle charging pile planning and management result construction unit is used to construct the target geographical area new energy vehicle charging pile planning and management data; the target geographical area new energy vehicle charging pile planning and management result feedback operation execution unit executes the new energy vehicle charging pile planning and management result feedback operation based on the target geographical area new energy vehicle charging pile planning and management data combined with the display screen.

10. A collaborative planning and management system for new energy according to claim 9, characterized in that: The target geographic area characteristic information collection unit collects the location characteristic text information of the target geographic area online through the data collection dialog box, and generates the target geographic area characteristic text data I; The new energy vehicle charging pile planning time period collection unit collects the new energy vehicle charging pile planning time length parameters of the target geographical area online through the data collection dialog box, and generates new energy vehicle charging pile planning time period data J, where J = [j1, j2], j1 and j2 represent the new energy vehicle charging pile planning time starting point data and new energy vehicle charging pile planning time end point data respectively, and the units of j1 and j2 are mainly composed of years, months, and days.

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