CN117787583A - Parking lot charging berth calculating method and system based on demand side - Google Patents
Parking lot charging berth calculating method and system based on demand side Download PDFInfo
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Abstract
The invention discloses a parking lot charging berth calculating method and system based on a demand side. The method comprises the following steps: according to the new energy parking record data, acquiring the number of times of parking the new energy vehicle and acquiring the number of times of daily average parking of the new energy vehicle; if the daily average parking times of the new energy vehicle is greater than or equal to the parking times threshold value, cleaning parking record data are obtained; according to the parking time length, obtaining short-time parking record number in a counting period, calculating the median of the parking time length, and calculating the average number of times of parking turnover according to the median of the parking time length; according to the new energy vehicle charging record data and the parking record number, calculating the charging behavior probability accompanying the parking of the new energy vehicle in the current parking lot; calculating the annual average growth rate of the new energy vehicle according to the new energy vehicle conservation amount data, and calculating the expansion coefficient of the charging demand; and calculating the number of quick-charging berths of the current parking lot according to the charging behavior probability, the charging demand expansion coefficient, the short-time parking record number, the statistical period and the daily average parking turnover number.
Description
Technical Field
The invention relates to the technical field of intelligent parking, in particular to a parking lot charging berth calculating method and system based on a demand side.
Background
The rapid growth of new energy vehicles has also led to a proliferation of parking-charging demands for new energy vehicles. And the yard built in the early stage often has no new energy vehicle charging facilities and needs to be re-planned and modified. The traditional method often omits the planning of constructing a small amount of charging berths for a single parking lot, but provides an address selection scheme for newly building a charging station of a large new energy vehicle based on the distribution of a power grid and the situation of electricity consumption peaks and valleys at the angle of standing on the power supply side. However, on one hand, the method regards the charging demands of widely dispersed new energy vehicles in cities as a few points, and the real charging demand distribution situation of the new energy vehicles cannot be reflected, so that scientific and reasonable planning decisions cannot be made; on the other hand, only a newly built large-scale charging station is concerned, but not how many common berths should be transformed into charging berths for the built parking lot, and the existing parking resources cannot be fully utilized.
Disclosure of Invention
The invention aims to solve the technical problem of low calculation accuracy of the required quantity of the charging berths of the new energy vehicle in the traditional method. In order to achieve the above purpose, the invention provides a parking lot charging berth calculating method and system based on a demand side.
The invention provides a parking lot charging berth calculating method based on a demand side, which comprises the following steps:
acquiring new energy parking record data of a current parking lot;
acquiring the number of times of parking new energy vehicles according to the new energy parking record data, and acquiring the number of times of daily average parking of the new energy vehicles according to the number of times of parking the new energy vehicles;
if the daily average parking times of the new energy vehicle is greater than or equal to a parking times threshold value, carrying out data cleaning on the new energy parking record data to obtain cleaning parking record data;
obtaining short-time parking record numbers in a counting period according to the parking time in the cleaning parking record data, calculating the median of the parking time according to the short-time parking record numbers, and calculating the average number of times of parking turnover according to the median of the parking time;
acquiring new energy vehicle charging record data and parking record number of a built charging berth, and calculating charging behavior probability accompanying when the new energy vehicle in the current parking lot parks according to the new energy vehicle charging record data and the parking record number;
acquiring new energy vehicle preservation amount data of a city where the current parking lot is located, calculating the annual average growth rate of the new energy vehicles according to the new energy vehicle preservation amount data, and calculating a charging demand expansion coefficient according to the annual average growth rate of the new energy vehicles;
and calculating the number of quick-charging berths of the current parking lot according to the charging behavior probability, the charging demand expansion coefficient, the short-time parking record number, the statistical period and the daily average parking turnover number.
In one embodiment, the method further comprises:
obtaining a long-time parking record number in a counting period according to the parking time in the cleaning parking record data;
calculating the slow-charging berth number of the current parking lot according to the charging behavior probability, the charging demand expansion coefficient, the long-time parking record number and the statistical period;
if the sum of the fast filling berth number and the slow filling berth number is smaller than or equal to the total number of the parking lot berths in the current parking lot, the fast filling berth number and the slow filling berth number are built in the current parking lot.
In one embodiment, the method further comprises:
if the sum of the fast-filling berth number and the slow-filling berth number is larger than the total number of the parking lot berths of the current parking lot, calculating the fast-filling berth correction number according to the fast-filling berth number, the slow-filling berth number and the total number of the parking lot berths, and constructing the fast-filling berth correction number in the current parking lot.
In one embodiment, the method further comprises:
if the sum of the fast filling berth number and the slow filling berth number is larger than the total number of the parking lot berths of the current parking lot, calculating the slow filling berth correction number according to the fast filling berth number, the slow filling berth number and the total number of the parking lot berths, and constructing the slow filling berth correction number in the current parking lot.
In one embodiment, the method further comprises:
if the daily average parking times of the new energy vehicle is smaller than the parking times threshold, a charging berth is not built in the current parking lot.
The invention provides a parking lot charging berth calculating system based on a demand side, which comprises the following components:
the data acquisition module is used for acquiring new energy parking record data of the current parking lot;
the parking frequency acquisition module is used for acquiring the parking frequency of the new energy vehicle according to the new energy parking record data and acquiring the daily average parking frequency of the new energy vehicle according to the new energy vehicle parking frequency;
the data cleaning module is used for cleaning the data of the new energy parking record data to obtain cleaning parking record data if the daily average parking times of the new energy vehicle is greater than or equal to a parking times threshold value;
the short-time parking parameter calculation module is used for obtaining the short-time parking record number in a counting period according to the parking time in the cleaning parking record data, calculating the median of the parking time according to the short-time parking record number, and calculating the average number of times of parking turnover according to the median of the parking time;
the charging behavior probability calculation module is used for acquiring charging record data and parking record number of the new energy vehicle with the built charging berth and calculating the charging behavior probability accompanying the parking of the new energy vehicle in the current parking lot according to the charging record data and the parking record number of the new energy vehicle;
the expansion coefficient calculation module is used for acquiring the new energy vehicle holding quantity data of the city where the current parking lot is located, calculating the annual average growth rate of the new energy vehicles according to the new energy vehicle holding quantity data, and calculating the expansion coefficient of the charging demand according to the annual average growth rate of the new energy vehicles;
and the fast charge berth calculating module is used for calculating the number of the fast charge berths of the current parking lot according to the charging behavior probability, the charging demand expansion coefficient, the short-time parking record number, the statistical period and the daily parking turnover number.
In one embodiment, the system further comprises:
the long-time parking record acquisition module is used for acquiring the long-time parking record number in the counting period according to the parking time in the cleaning parking record data;
the slow-charging berth calculating module is used for calculating the slow-charging berth number of the current parking lot according to the charging behavior probability, the charging demand expansion coefficient, the long-time parking record number and the statistical period;
and the quantity construction planning module is used for constructing the fast filling berth quantity and the slow filling berth quantity in the current parking lot if the sum of the fast filling berth quantity and the slow filling berth quantity is smaller than or equal to the total number of the parking lot berths in the current parking lot.
In one embodiment, the system further comprises:
and the quick charge correction module is used for calculating the quick charge berth correction quantity according to the quick charge berth quantity, the slow charge berth quantity and the total number of the parking lots if the sum of the quick charge berth quantity and the slow charge berth quantity is larger than the total number of the parking lots of the current parking lot, and constructing the quick charge berth correction quantity in the current parking lot.
In one embodiment, the system further comprises:
and the slow-filling correction module is used for calculating slow-filling berth correction quantity according to the fast-filling berth quantity, the slow-filling berth quantity and the total number of the parking lots if the sum of the fast-filling berth quantity and the slow-filling berth quantity is larger than the total number of the parking lots of the current parking lot, and constructing the slow-filling berth correction quantity in the current parking lot.
In one embodiment, the system further comprises:
and the planning module is used for not building a charging berth in the current parking lot if the daily average parking times of the new energy vehicle is smaller than the parking times threshold value.
According to the parking lot charging berth calculating method and system based on the demand side, the new energy parking record data of the current parking lot and the new energy vehicle charging record data and the parking record number of the built charging berth are fully fused, the quick charging berth number of the current parking lot is calculated through the obtained charging behavior probability, the charging demand expansion coefficient, the short-time parking record number, the statistical period and the daily parking turnover number, the reliable and accurate quick charging berth number is provided for the current parking lot, the calculating accuracy of the parking lot charging berth number based on the demand side is improved, efficient use of the charging facilities built by the current parking lot can be guaranteed, and the unnecessary cost of the current parking lot due to the fact that too many charging berths are built blindly is avoided. Meanwhile, by the parking lot charging berth calculating method based on the demand side, more and more parking lots can be built to build the charging berths, the distance for a vehicle owner to find the charging piles is shortened, and the problem of difficult charging is solved.
Drawings
Fig. 1 is a schematic flow chart of steps of a parking lot charging berth calculating method based on a demand side.
Fig. 2 is a schematic structural diagram of a demand-side-based parking lot charging berth computing system provided by the invention.
Detailed Description
The technical invention of the present invention will be described in further detail below by means of the accompanying drawings and examples.
Referring to fig. 1, the invention provides a parking lot charging berth calculating method based on a demand side, comprising:
s10, acquiring new energy parking record data of a current parking lot;
s20, acquiring the number of times of parking the new energy vehicle according to the new energy parking record data, and acquiring the number of times of daily average parking of the new energy vehicle according to the number of times of parking the new energy vehicle;
s30, if the daily average parking times of the new energy vehicle is greater than or equal to the parking times threshold, carrying out data cleaning on the new energy parking record data to obtain cleaning parking record data;
s40, obtaining short-time parking record numbers in a counting period according to the parking time in the cleaning parking record data, calculating the median of the parking time according to the short-time parking record numbers, and calculating the average number of times of parking turnover according to the median of the parking time;
s50, acquiring new energy vehicle charging record data and parking record number of the built charging berth, and calculating the charging behavior probability accompanying when the new energy vehicle in the current parking lot parks according to the new energy vehicle charging record data and the parking record number;
s60, acquiring new energy vehicle maintenance data of a city where a current parking lot is located, calculating the annual average growth rate of the new energy vehicles according to the new energy vehicle maintenance data, and calculating the expansion coefficient of the charging demand according to the annual average growth rate of the new energy vehicles;
s70, calculating the number of quick-charging berths of the current parking lot according to the charging behavior probability, the charging demand expansion coefficient, the short-time parking record number, the statistical period and the daily average parking turnover number.
In this embodiment, the total parking record data of a certain parking lot in a period of time is acquired. And identifying the parking record data of the new energy vehicle from the parking record data, and obtaining the new energy parking record data of the current parking lot. When new energy parking record data are screened from the parking record data, the green license plate and the yellow green license plate correspond to the new energy vehicles through license plate color judgment. If the license plate color is missing, the license plate number can be judged, 7 is a non-new energy vehicle, and 8 is a new energy vehicle. Acquiring the number of times of parking the new energy vehicle based on the new energy parking record data, and further acquiring the number of times of daily average parking of the new energy vehicle N based on the number of times of parking the new energy vehicle ele 。
Based on new energy vehicle average parking times N ele Determining whether or not it is greater than or equal to the threshold number of parking times N min And if yes, cleaning the new energy parking record data. Threshold number of stops N min May be set to a range of 8 to 12. In one embodiment, it can be arranged that10。
When the new energy parking record data is subjected to data cleaning, the parking records with too short parking time length and the parking records with too long parking time length are screened out. Too short a parking time period and too long a parking time period can be set according to actual conditions, for example: if the parking time is less than 5 minutes, the non-effective charging requirement is considered, and the non-effective charging requirement belongs to the short parking time and is cleaned; and when the parking time is longer than 7 days, determining that the data of the zombie vehicle is long, and cleaning the zombie vehicle. And obtaining cleaning parking record data through data cleaning.
In the cleaning parking record data, according to the parking time length, obtaining the short-time parking record number N of the new energy vehicle in the statistical period (T) short . In one embodiment, the parking duration is less than or equal to 6 hours, the number of hours can be limited according to the actual situation, and the method is not particularly limited in this embodiment, and only exemplary embodiments are described. Calculating the median T of the parking time according to the short-time parking record number mid And calculating the average number of times of revolution of the vehicle in the day according to the median of the vehicle-stopping time length phi=12/T mid 。
And acquiring charging record data and parking record number of the new energy vehicle through a third party platform. And screening out the yard data which is similar to the yard in scale and geographic position and has the charging berth built from the charging record data and the parking record number of the new energy source truck, and generating the charging record data and the parking record number of the new energy source truck with the charging berth built. Further, according to the new energy vehicle charging record data and the parking record number, the charging behavior probability accompanying the parking of the new energy vehicle in the current parking lot is calculated. Charging behavior probability (P) =new energy vehicle charging record data (a)/new energy parking record number (B).
Acquiring new energy vehicle holding quantity data M of the current parking lot in the city of the current parking lot in the last n years (n is more than or equal to 3) 1 ，M 2 …M n . Calculating new energy vehicle annual average growth rate (U) = (M) n /M 1 ) And (n-1) -1. And calculating a charging demand expansion coefficient mu= (1+U)/(m) according to the annual average growth rate of the new energy vehicle. m may range from 2 to 5.
According to the charging behavior probability, the charging demand expansion coefficient and the short-time stopAnd (3) counting the number of vehicle records, counting the period and the number of average parking turnovers, and calculating the number of quick-filling berths of the current parking lot. Quick-charging berth number A of current parking lot fast ＝P*μ*N short /(T x phi). In one embodiment, if the number of fast-fill berths A in the current parking lot fast And if not, rounding upwards.
According to the parking lot charging berth calculating method based on the demand side, the new energy parking record data of the current parking lot and the new energy vehicle charging record data and the parking record number of the built charging berth are fully fused, and the quick charging berth number of the current parking lot is calculated through the charging behavior probability, the charging demand expansion coefficient, the short-time parking record number, the counting period and the daily average parking turnover number which are obtained through calculation, so that the reliable and accurate quick charging berth number is provided for the current parking lot, the calculation accuracy of the charging berth number of the parking lot based on the demand side is improved, efficient use of the charging facilities built by the current parking lot can be ensured, and the unnecessary cost of the current parking lot due to the fact that the excessive charging berth is built blindly is avoided. Meanwhile, by the parking lot charging berth calculating method based on the demand side, more and more parking lots can be built to build the charging berths, the distance for a vehicle owner to find the charging piles is shortened, and the problem of difficult charging is solved.
In one embodiment, the demand side-based parking lot charging berth calculating method further includes:
s80, obtaining a long-time parking record number in a statistical period according to the parking time in the cleaning parking record data;
s90, calculating the slow-charging berth number of the current parking lot according to the charging behavior probability, the charging demand expansion coefficient, the long-time parking record number and the statistical period;
s100, if the sum of the number of fast-filling berths and the number of slow-filling berths is smaller than or equal to the total number of parking lot berths in the current parking lot, the number of fast-filling berths and the number of slow-filling berths are built in the current parking lot.
In the present embodiment, the number of long-term stops N is counted in the counting period (T) long . In one embodiment, the duration of the parking>For 6 hoursThe number of hours corresponding to the slow charge requirement can be limited according to practical situations, and the embodiment is not particularly limited and only illustrated.
Calculating slow-charging berth number A of current parking lot slow ＝P*μ*N long and/T. Wherein P is the charging behavior probability, and μ is the charging demand expansion coefficient. In one embodiment, if the number of slow-fill berths A of the current parking lot slow And if not, rounding downwards.
Judging the sum of the number of fast-charging berths and the number of slow-charging berths, namely A fast +A slow ≤A park Whether or not it is. A is that park The total number of parking space berths in the current parking space. If true, constructing corresponding quick-charging berth quantity A in the current parking lot fast Number of slow-filling berths A slow 。
According to the parking lot charging berth calculating method based on the demand side, the number of fast charging berths and the number of slow charging berths which need to be built are calculated according to the operated parking lot, huge pressure on a local power grid caused by a large-scale charging station can be effectively avoided, an owner can find available charging berths conveniently by a short distance, market demands are met from the demand side, and the method can be applied to the construction of specific types of berths such as barrier-free berths, large truck berths and taxi berths.
In one embodiment, the demand side-based parking lot charging berth calculating method further includes:
s101, if the sum of the number of fast-filling berths and the number of slow-filling berths is larger than the total number of parking lot berths of the current parking lot, calculating the correction number of the fast-filling berths according to the number of the fast-filling berths, the number of the slow-filling berths and the total number of the parking lot berths, and building the correction number of the fast-filling berths in the current parking lot.
In this embodiment, if the sum of the number of fast-fill berths and the number of slow-fill berths, i.e., A fast +A slow >A park Calculating the corrected quantity A 'of the fast-charging berths' fast ＝A fast /(A slow +A fast )*A park And constructing corresponding quick berth correcting quantity in the current parking lot. In a real worldIn the embodiment, if the number of corrected fast filling berths A' fast And if not, rounding upwards.
In one embodiment, the demand side-based parking lot charging berth calculating method further includes:
s102, if the sum of the number of fast filling berths and the number of slow filling berths is larger than the total number of parking lot berths in the current parking lot, calculating the correction number of slow filling berths according to the number of fast filling berths, the number of slow filling berths and the total number of parking lot berths, and constructing the correction number of slow filling berths in the current parking lot.
In this embodiment, the slow-fill berth correction quantity A 'is calculated' slow ＝A slow /(A slow +A fast )*A park . In one embodiment, if the slow fill berth is modified by an amount A' slow And if not, rounding downwards. Thus, in the current parking lot, the corresponding slow-filling berth correction quantity A 'is built' slow And the correction quantity A 'of the fast-charging berth' fast 。
In one embodiment, the demand side-based parking lot charging berth calculating method further includes:
and S103, if the daily average parking times of the new energy vehicle is smaller than the parking times threshold, not building a charging berth in the current parking lot.
In this embodiment, for example, the number of times N of daily average parking of new energy vehicles ele Less than the threshold number of times of parking N min And in the current parking lot, the charging berth is not built.
In one embodiment, according to the demand-side-based parking lot charging berth calculation method provided by the invention, a specific implementation process is described by taking planning of a charging berth plan for a certain old parking lot in C city as an example.
The parking lot is positioned in the central urban area of C city, and is used for building a parking lot for a community, but can be opened to external vehicles, and the total number of parking lots is 350, namely the total number of parking lots A of the current parking lot park 350. Because the new energy vehicle is expected to have a larger charging requirement when parking in a parking lot, the number of charged berths is calculated.
By docking the 2023 years 3-5 months (92 totalDay) and identifying the number of new energy vehicles according to the license plate number, and obtaining 5927 parking records of the number of times of parking the new energy vehicles, wherein the number of times of daily average parking of the new energy vehicles is N ele ＝64.42>N min The charging berth can be constructed.
And (3) cleaning the data of the new energy parking record, deleting 103 pieces of data with the parking time less than 5 minutes, and deleting 62 pieces of data with the parking time longer than 7 days. After the data are cleaned, 5762 new energy vehicles are parked and recorded, namely 5762 cleaning and parking record data are recorded.
For 5762 pieces of cleaning parking record data, further calculating according to the parking time length to obtain a short-time parking record number N with the parking time length less than or equal to 6 hours short 4918 pieces, parking time length>Long-term stop record number N of 6 hours long =844.
Record number N for short-time parking short The number of 4918 short-time parking records is analyzed, and most short-time parking records are found to be distributed in the period of 9:00 to 21:00, namely, the statistical period. The median of the parking time is T mid =3.25 hours. The number of average daily parking turnovers in the statistical period was further calculated to be Φ=3.69.
And screening out the district built with 10 facilities with similar scales and built charging berths within 5km around the current parking lot, acquiring 21930 new energy vehicle charging record data generated by the parking lots in 2023 and 3-5 months through a third party platform, 85772 parking record numbers and estimating P= 0.2557.
In consideration of the obvious rising trend of the new energy vehicle in C market in recent years, the charging requirement of the new energy vehicle growing increasingly can be met in a longer time after the charging berth is built, and future charging resources are reserved when the number of the berth is planned, so that repeated construction in a short period is avoided. For this purpose, the charge demand expansion coefficient μ is calculated. And acquiring the new energy vehicle maintenance data of the city 2020-2022, namely 10 ten thousand, 12.14 ten thousand and 17.1 ten thousand, and calculating the annual average growth rate U= 30.77% of the available new energy vehicles. Therefore, if the number of charging berths is required to meet the increase of the charging demand of the new energy vehicle within 3 years, the expansion coefficient of the charging demand is μ= 2.2361.
Calculating the number A of quick-charging berths fast =8.28, rounded up a fast =9. Calculating the number A of slow-filling berths slow =5.25, rounded down a slow =5.
Due to A slow +A fast =14, less than the total number of parking lots a park =350, thus, 9 fast-fill berths and 5 slow-fill berths are constructed.
Referring to fig. 2, the present invention provides a parking lot charging berth computing system 100 based on a demand side. The demand-side-based parking lot charging berth calculating system 100 includes a data acquiring module 10, a parking number acquiring module 20, a data cleaning module 30, a short-time parking parameter calculating module 40, a charging behavior probability calculating module 50, an expansion coefficient calculating module 60, and a quick charging berth calculating module 70. The data acquisition module 10 is used for acquiring new energy parking record data of a current parking lot. The parking number obtaining module 20 is configured to obtain the number of times of parking the new energy vehicle according to the new energy parking record data, and obtain the number of times of daily average parking of the new energy vehicle according to the number of times of parking the new energy vehicle. The data cleaning module 30 is configured to perform data cleaning on the new energy vehicle parking record data to obtain cleaning parking record data if the daily average parking times of the new energy vehicle is greater than or equal to the parking times threshold.
The short-time parking parameter calculation module 40 is configured to obtain a short-time parking record number in a statistics period according to the parking time in the cleaning parking record data, calculate a median of the parking time according to the short-time parking record number, and calculate a daily average number of parking revolutions according to the median of the parking time. The charging behavior probability calculation module 50 is configured to obtain charging record data and a parking record number of a new energy vehicle with a built charging berth, and calculate a charging behavior probability associated with parking of the new energy vehicle in the current parking lot according to the charging record data and the parking record number of the new energy vehicle.
The expansion coefficient calculating module 60 is configured to obtain new energy vehicle maintenance amount data of a city where the parking lot is currently located, calculate an annual average growth rate of the new energy vehicles according to the new energy vehicle maintenance amount data, and calculate a charging demand expansion coefficient according to the annual average growth rate of the new energy vehicles. The fast-charging berth calculating module 70 is configured to calculate the number of fast-charging berths in the current parking lot according to the charging behavior probability, the charging demand expansion coefficient, the short-time parking record number, the statistical period and the daily average parking turnover number.
In this embodiment, the description of the data acquisition module 10 may refer to the description of S10 in the above embodiment. The description of the parking number acquisition module 20 may refer to the description of S20 in the above-described embodiment. The relevant description of the data cleansing module 30 may refer to the relevant description of S30 in the above embodiment. The description of the short-time parking parameter calculation module 40 may refer to the description of S40 in the above embodiment. The description of the charging behavior probability calculation module 50 may refer to the description of S50 in the above embodiment. The description of the expansion coefficient calculation module 60 may refer to the description of S60 in the above embodiment. The description of the fast-fill berth calculating module 70 may refer to the description of S70 in the above embodiment.
In one embodiment, demand-side-based parking lot charging berth computing system 100 further includes long-term parking record acquisition module 70, slow-charge berth computing module 80, and quantity construction planning module 90. The long-time parking record acquisition module 70 is used for acquiring the number of long-time parking records in the counting period according to the parking time in the cleaning parking record data. The slow-charging berth calculating module 80 is configured to calculate the number of slow-charging berths in the current parking lot according to the charging behavior probability, the charging demand expansion coefficient, the long-time parking record number and the statistical period. The quantity construction planning module 90 is configured to construct the fast-fill berth quantity and the slow-fill berth quantity in the current parking lot if the sum of the fast-fill berth quantity and the slow-fill berth quantity is less than or equal to the total number of parking lot berths in the current parking lot.
In the present embodiment, the description of the long-term parking record acquisition module 70 may refer to the description of S70 in the above embodiment. The description of the slow-fill berth calculating module 80 may refer to the description of S80 in the above embodiment. The description of the number construction plan module 90 may refer to the description of S90 in the above embodiment.
In one embodiment, demand-side based parking lot charging berth computing system 100 also includes a quick charge correction module 100. The fast-charging correction module 100 is configured to calculate a fast-charging berth correction amount according to the fast-charging berth amount, the slow-charging berth amount, and the total number of the parking lots if the sum of the fast-charging berth amount and the slow-charging berth amount is greater than the total number of the parking lots of the current parking lot, and construct the fast-charging berth correction amount in the current parking lot.
In this embodiment, the description of the quick charge correction module 100 may refer to the description of S100 in the above embodiment.
In one embodiment, demand-side based parking lot charging berth computing system 100 also includes a slow charge correction module 101. The slow-filling correction module 101 is configured to calculate a slow-filling berth correction amount according to the fast-filling berth amount, the slow-filling berth amount, and the total number of the parking lots if the sum of the fast-filling berth amount and the slow-filling berth amount is greater than the total number of the parking lots of the current parking lot, and construct the slow-filling berth correction amount in the current parking lot.
In this embodiment, the description of the slow charge correction module 101 may refer to the description of S101 in the above embodiment.
In one embodiment, demand-side based parking lot charging berth computing system 100 also includes planning module 102. The planning module 102 is configured to not construct a charging berth in the current parking lot if the average daily parking frequency of the new energy vehicle is less than the threshold parking frequency.
In this embodiment, the description of the planning module 102 may refer to the description of S102 in the above embodiment.
In the various embodiments described above, the particular order or hierarchy of steps in the processes disclosed are examples of exemplary approaches. Based on design preferences, it is understood that the specific order or hierarchy of steps in the processes may be rearranged without departing from the scope of the present disclosure. The accompanying method claims present elements of the various steps in a sample order, and are not meant to be limited to the specific order or hierarchy.
Those of skill in the art will further appreciate that the various illustrative logical blocks (illustrative logical block) listed in the present invention, modules and steps may be implemented by electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components (illustrative components), modules, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design requirements of the overall system. Those skilled in the art may implement the described functionality in varying ways for each particular application, but such implementation is not to be understood as beyond the scope of the embodiments of the present invention.
The various illustrative logical blocks or modules described in connection with the embodiments of the present invention may be implemented or performed with a general purpose processor, a digital signal processor, an Application Specific Integrated Circuit (ASIC), a field programmable gate array or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general purpose processor may be a microprocessor, but in the alternative, the general purpose processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a digital signal processor and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a digital signal processor core, or any other similar configuration.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may be stored in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. In an example, a storage medium may be coupled to the processor such that the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC, which may reside in a user terminal. In the alternative, the processor and the storage medium may reside as distinct components in a user terminal.
While the foregoing is directed to embodiments of the present invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof, and the scope thereof is determined by the claims that follow.
Claims (10)
1. The parking lot charging berth calculating method based on the demand side is characterized by comprising the following steps of:
acquiring new energy parking record data of a current parking lot;
acquiring the number of times of parking new energy vehicles according to the new energy parking record data, and acquiring the number of times of daily average parking of the new energy vehicles according to the number of times of parking the new energy vehicles;
if the daily average parking times of the new energy vehicle is greater than or equal to a parking times threshold value, carrying out data cleaning on the new energy parking record data to obtain cleaning parking record data;
obtaining short-time parking record numbers in a counting period according to the parking time in the cleaning parking record data, calculating the median of the parking time according to the short-time parking record numbers, and calculating the average number of times of parking turnover according to the median of the parking time;
acquiring new energy vehicle charging record data and parking record number of a built charging berth, and calculating charging behavior probability accompanying when the new energy vehicle in the current parking lot parks according to the new energy vehicle charging record data and the parking record number;
acquiring new energy vehicle preservation amount data of a city where the current parking lot is located, calculating the annual average growth rate of the new energy vehicles according to the new energy vehicle preservation amount data, and calculating a charging demand expansion coefficient according to the annual average growth rate of the new energy vehicles;
and calculating the number of quick-charging berths of the current parking lot according to the charging behavior probability, the charging demand expansion coefficient, the short-time parking record number, the statistical period and the daily average parking turnover number.
2. The demand-side-based parking lot charging berth calculating method according to claim 1, further comprising:
obtaining a long-time parking record number in a counting period according to the parking time in the cleaning parking record data;
calculating the slow-charging berth number of the current parking lot according to the charging behavior probability, the charging demand expansion coefficient, the long-time parking record number and the statistical period;
if the sum of the fast filling berth number and the slow filling berth number is smaller than or equal to the total number of the parking lot berths in the current parking lot, the fast filling berth number and the slow filling berth number are built in the current parking lot.
3. The demand-side-based parking lot charging berth calculating method according to claim 2, further comprising:
if the sum of the fast-filling berth number and the slow-filling berth number is larger than the total number of the parking lot berths of the current parking lot, calculating the fast-filling berth correction number according to the fast-filling berth number, the slow-filling berth number and the total number of the parking lot berths, and constructing the fast-filling berth correction number in the current parking lot.
4. A demand side-based parking lot charging berth calculating method according to claim 3, further comprising:
if the sum of the fast filling berth number and the slow filling berth number is larger than the total number of the parking lot berths of the current parking lot, calculating the slow filling berth correction number according to the fast filling berth number, the slow filling berth number and the total number of the parking lot berths, and constructing the slow filling berth correction number in the current parking lot.
5. The demand-side-based parking lot charging berth calculating method according to claim 1, further comprising:
if the daily average parking times of the new energy vehicle is smaller than the parking times threshold, a charging berth is not built in the current parking lot.
6. A demand-side-based parking lot charging berth computing system, comprising:
the data acquisition module is used for acquiring new energy parking record data of the current parking lot;
the parking frequency acquisition module is used for acquiring the parking frequency of the new energy vehicle according to the new energy parking record data and acquiring the daily average parking frequency of the new energy vehicle according to the new energy vehicle parking frequency;
the data cleaning module is used for cleaning the data of the new energy parking record data to obtain cleaning parking record data if the daily average parking times of the new energy vehicle is greater than or equal to a parking times threshold value;
the short-time parking parameter calculation module is used for obtaining the short-time parking record number in a counting period according to the parking time in the cleaning parking record data, calculating the median of the parking time according to the short-time parking record number, and calculating the average number of times of parking turnover according to the median of the parking time;
the charging behavior probability calculation module is used for acquiring charging record data and parking record number of the new energy vehicle with the built charging berth and calculating the charging behavior probability accompanying the parking of the new energy vehicle in the current parking lot according to the charging record data and the parking record number of the new energy vehicle;
the expansion coefficient calculation module is used for acquiring the new energy vehicle holding quantity data of the city where the current parking lot is located, calculating the annual average growth rate of the new energy vehicles according to the new energy vehicle holding quantity data, and calculating the expansion coefficient of the charging demand according to the annual average growth rate of the new energy vehicles;
and the fast charge berth calculating module is used for calculating the number of the fast charge berths of the current parking lot according to the charging behavior probability, the charging demand expansion coefficient, the short-time parking record number, the statistical period and the daily parking turnover number.
7. The demand-side based parking lot charging berth computing system of claim 6, further comprising:
the long-time parking record acquisition module is used for acquiring the long-time parking record number in the counting period according to the parking time in the cleaning parking record data;
the slow-charging berth calculating module is used for calculating the slow-charging berth number of the current parking lot according to the charging behavior probability, the charging demand expansion coefficient, the long-time parking record number and the statistical period;
and the quantity construction planning module is used for constructing the fast filling berth quantity and the slow filling berth quantity in the current parking lot if the sum of the fast filling berth quantity and the slow filling berth quantity is smaller than or equal to the total number of the parking lot berths in the current parking lot.
8. The demand-side based parking lot charging berth computing system of claim 7, further comprising:
and the quick charge correction module is used for calculating the quick charge berth correction quantity according to the quick charge berth quantity, the slow charge berth quantity and the total number of the parking lots if the sum of the quick charge berth quantity and the slow charge berth quantity is larger than the total number of the parking lots of the current parking lot, and constructing the quick charge berth correction quantity in the current parking lot.
9. The demand-side based parking lot charging berth computing system of claim 8, further comprising:
and the slow-filling correction module is used for calculating slow-filling berth correction quantity according to the fast-filling berth quantity, the slow-filling berth quantity and the total number of the parking lots if the sum of the fast-filling berth quantity and the slow-filling berth quantity is larger than the total number of the parking lots of the current parking lot, and constructing the slow-filling berth correction quantity in the current parking lot.
10. The demand-side based parking lot charging berth computing system of claim 6, further comprising:
and the planning module is used for not building a charging berth in the current parking lot if the daily average parking times of the new energy vehicle is smaller than the parking times threshold value.
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| CN202311367754.6A CN117787583A (en) | 2023-10-20 | 2023-10-20 | Parking lot charging berth calculating method and system based on demand side |
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