CN117077872B - Intelligent scheduling management system for new energy electric automobile charging pile - Google Patents
Intelligent scheduling management system for new energy electric automobile charging pile Download PDFInfo
- Publication number
- CN117077872B CN117077872B CN202311340923.7A CN202311340923A CN117077872B CN 117077872 B CN117077872 B CN 117077872B CN 202311340923 A CN202311340923 A CN 202311340923A CN 117077872 B CN117077872 B CN 117077872B
- Authority
- CN
- China
- Prior art keywords
- charging
- charging pile
- scheduling
- pile
- module
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000007405 data analysis Methods 0.000 claims abstract description 12
- 238000007726 management method Methods 0.000 claims description 42
- 230000004913 activation Effects 0.000 claims description 19
- 238000004364 calculation method Methods 0.000 claims description 19
- 238000000034 method Methods 0.000 claims description 15
- 238000013439 planning Methods 0.000 claims description 9
- 238000010835 comparative analysis Methods 0.000 claims description 5
- 238000010276 construction Methods 0.000 claims description 5
- 230000010354 integration Effects 0.000 claims description 5
- 238000007781 pre-processing Methods 0.000 claims description 4
- 238000004458 analytical method Methods 0.000 claims description 3
- 230000009286 beneficial effect Effects 0.000 description 6
- 230000009471 action Effects 0.000 description 3
- 230000008901 benefit Effects 0.000 description 3
- 230000000052 comparative effect Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 230000015556 catabolic process Effects 0.000 description 1
- 238000006731 degradation reaction Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000005284 excitation Effects 0.000 description 1
- 238000013468 resource allocation Methods 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06312—Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02T90/10—Technologies relating to charging of electric vehicles
- Y02T90/12—Electric charging stations
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Entrepreneurship & Innovation (AREA)
- Marketing (AREA)
- General Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Tourism & Hospitality (AREA)
- Quality & Reliability (AREA)
- Game Theory and Decision Science (AREA)
- Operations Research (AREA)
- Development Economics (AREA)
- Health & Medical Sciences (AREA)
- Educational Administration (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Charge And Discharge Circuits For Batteries Or The Like (AREA)
Abstract
The invention relates to the technical field of new energy electric vehicles and discloses an intelligent scheduling management system for a charging pile of a new energy electric vehicle, which comprises an information acquisition module, an information arrangement module, a data analysis module, a data comparison module and an execution module, wherein the system can record and feed back real-time data of the charging pile through the information acquisition module, the arrangement module, the data analysis module and the data comparison module, so that a manager can better know the state and the requirement of the charging pile, thereby optimizing the use of the charging pile, improving the efficiency of the charging pile, reducing the working pressure of the charging pile, intelligently adjusting the use of the charging pile, ensuring that the charging pile is reasonably utilized in peak period and low peak period, and dynamically scheduling the charging pile according to the actual power pressure condition so as to ensure the normal running of a charging station and the charging requirement of a vehicle.
Description
Technical Field
The invention relates to the technical field of new energy electric vehicles, in particular to an intelligent scheduling management system for a new energy electric vehicle charging pile.
Background
The new energy electric automobile fills electric pile is the equipment that is used for charging electric automobile. They are typically installed in parking lots, gas stations, commercial buildings or personal homes, etc. for charging use by users of electric vehicles.
The intelligent scheduling management system matched with the new energy electric automobile charging pile is an intelligent management system aiming at electric automobile charging equipment, and the main aim of the intelligent scheduling management system is to optimize the use of the charging pile, improve the charging efficiency, ensure the reliability and convenience of charging service, and ensure that a general charging pile has two charging modes of fast charging and slow charging, and the charging mode of the charging head can be changed only by changing the voltage under the condition of adopting the same charging head.
However, the general system is mostly used for operation management, and the main purpose of the design is to ensure that the charging pile can normally supply power, charge and maintain, but when the charging pile is in a peak use state, the management system cannot well perform interventional scheduling management on the power consumption of the charging pile, so that when the charging pile is in a high-frequency use region, a basic slow charging state is still executed, and the charging pile is in a short supply state, thereby affecting the charging experience of users.
Disclosure of Invention
The invention provides an intelligent scheduling management system for a charging pile of a new energy electric automobile, which has the beneficial effect of scheduling and managing the power supply voltage of the charging pile according to the actual use state of the charging pile, and solves the problems that the prior management system cannot perform interventional scheduling and management on the power consumption of the charging pile well in the prior art, so that the charging pile still executes a basic slow charging state when the charging pile is in a high-frequency use interval, and the charging pile supply and demand are caused, thereby influencing the charging experience of users.
The invention provides the following technical scheme: the intelligent scheduling management system for the new energy electric automobile charging pile comprises an information acquisition module, an information arrangement module, a data analysis module, a data comparison module and an execution module:
the information acquisition module is used for planning the urban area so as to acquire basic information and dynamic information of charging stations and charging piles corresponding to the urban area in each area;
the information arrangement module is used for preprocessing the information acquired by the information acquisition module and respectively arranging the preprocessed data into a first data set and a second data set;
wherein the first data set includes the number of charging pilesThe second data set includes charging stake usageCharging performance of charging pileAnd peak charge traffic flow；
A data analysis module for analyzing the first data and the second dataThe groups are integrated and calculated to generate the efficiency coefficient of the charging pileAnd the working pressure coefficient of the charging pile；
The efficiency coefficient of the charging pile to be generatedWorking pressure coefficient of charging pileObtaining scheduling coefficients by performing secondary integration calculationThe specific formula is as follows:
wherein:andrespectively is the efficiency coefficient of the charging pileAnd the working pressure coefficient of the charging pileWherein，And (2) and，in order to correct the coefficient of the coefficient,、andis set by customer adjustment or is generated by an analytical function fit;
a data comparison module for comparing the calculated scheduling coefficientsWith a preset scheduling thresholdAnd (5) performing comparative analysis.
As an alternative scheme of the intelligent scheduling management system for the new energy electric automobile charging pile, provided by the invention, the intelligent scheduling management system comprises the following components: the information acquisition module comprises a dividing unit, and the cities are respectively divided into a plurality of areas according to the power grid and are marked as an area r1, an area r2, an area r3 and an area rn.
As an alternative scheme of the intelligent scheduling management system for the new energy electric automobile charging pile, provided by the invention, the intelligent scheduling management system comprises the following components: the information acquisition module also comprises an initial information acquisition unit for inquiring the number of charging piles in the urban construction planning collection area。
As an alternative scheme of the intelligent scheduling management system for the new energy electric automobile charging pile, provided by the invention, the intelligent scheduling management system comprises the following components: the information acquisition unit further comprises a dynamic information acquisition unit for accessing the charging pile to acquire the charging performance of the charging pile。
As an alternative scheme of the intelligent scheduling management system for the new energy electric automobile charging pile, provided by the invention, the intelligent scheduling management system comprises the following components: dynamic information acquisition unitAlso used for recording single day activation quantity of charging piles in charging stationAnd calculating the number of the charging piles in the charging station, wherein the number of the charging piles activated on a single day is calculatedTo obtain the utilization rate of the charging pileThe specific formula is as follows:
。
as an alternative scheme of the intelligent scheduling management system for the new energy electric automobile charging pile, provided by the invention, the intelligent scheduling management system comprises the following components: the dynamic information acquisition unit is also used for accessing the activation times of the charging piles, acquiring the time period of the highest activation frequency in a single day, and acquiring the traffic flow of the charging peak by acquiring the activation times of the charging piles in the time period of the highest activation frequency in the single day。
As an alternative scheme of the intelligent scheduling management system for the new energy electric automobile charging pile, provided by the invention, the intelligent scheduling management system comprises the following components: the efficiency coefficient of the charging pileThe method is obtained through calculation according to the following formula:
wherein:、andrespectively the number of the charging pilesCharging pile utilization rateCharging performance of charging pileWherein，，，In order to correct the coefficient of the coefficient,、、andis set by the customer adjustment or is generated by an analytical function fit.
As an alternative scheme of the intelligent scheduling management system for the new energy electric automobile charging pile, provided by the invention, the intelligent scheduling management system comprises the following components: the working pressure coefficient of the charging pileThe method is obtained through calculation according to the following formula:
wherein:、andrespectively is the efficiency coefficient of the charging pileCharging pile utilization ratePeak charge traffic flowWherein，，，In order to correct the coefficient of the coefficient,、、andis set by the customer adjustment or is generated by an analytical function fit.
As an alternative scheme of the intelligent scheduling management system for the new energy electric automobile charging pile, provided by the invention, the intelligent scheduling management system comprises the following components: the data comparison module compares the scheduling coefficientsWith a preset scheduling thresholdPerforming contrast analysis to obtain a comparison result:
when scheduling coefficientsWhen the scheduling threshold is less than or equal toThe charging pile in the representative charging station does not need to schedule power;
when scheduling coefficientsWhen > scheduling thresholdThe charging posts in the charging station are represented to need to schedule power.
As an alternative scheme of the intelligent scheduling management system for the new energy electric automobile charging pile, provided by the invention, the intelligent scheduling management system comprises the following components: the data module is also used for adjusting the scheduling coefficientWith scheduling thresholdObtaining a comparison difference by combining calculationWill compare the difference to a scheduling thresholdPerforming secondary comparison to obtain a comparison differenceThe method is obtained through calculation according to the following formula:
obtaining a result:
when the worse valueScheduling thresholdWhen the power pressure of the representative charging station is less than or equal to 10%, the power pressure of the representative charging station is in an acceptable range, power adjustment is not needed, and a quick and slow charging mode of the normal charging pile is maintained;
when 10% < worse valueScheduling thresholdWhen the power pressure of the charging station is less than or equal to 15%, 5% of the power pressure of the charging station exceeds the receiving range, performing scheduling operation for increasing the voltage by 10%, keeping more than one third of the charging piles in a quick charging state, and allowing the vehicle to enter charging;
when 15% < worse valueScheduling thresholdWhen the power pressure of the charging station is less than or equal to 25%, representing that the power pressure of the charging station exceeds 15% of the receiving range, executing dispatching operation for increasing the voltage by 30%, keeping more than three-fourths of charging piles in a quick charging state, and allowing the vehicle to enter charging;
when the worse valueScheduling thresholdWhen the power pressure of the charging station is more than 25%, the power pressure of the charging station is fully beyond the receiving range, the dispatching operation of increasing the voltage by 45% is carried out, all the charging piles are kept in a quick charging state, and the vehicle is guided to other areas for charging.
The invention has the following beneficial effects:
1. this intelligent scheduling management system for electric automobile fills electric pile through information acquisition, arrangement module, data analysis module and data comparison module, and the system can carry out record and feedback to the real-time data who fills electric pile, thereby makes the manager know more fully that state and demand of filling electric pile optimize the use of filling electric pile, improves the efficiency of filling electric pile to reduce the operating pressure who fills electric pile, the system can intelligently adjust the use of filling electric pile, thereby lets filling electric pile and all obtain rational utilization at peak time and low peak time.
2. The intelligent scheduling management system for the charging pile of the new energy electric vehicle can dynamically schedule the charging pile according to the actual power pressure condition so as to maintain the normal operation of a charging station, and then calculate and compare the difference value by combining the scheduling coefficient with the scheduling threshold valueThe system can evaluate the power pressure more accurately, can judge whether to schedule or not, and can execute power scheduling operations of different degrees according to the difference value so as to meet the power supply requirements under different conditions.
Drawings
FIG. 1 is a schematic diagram of a system flow structure according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
Referring to fig. 1, an intelligent scheduling management system for a new energy electric vehicle charging pile includes an information acquisition module, an information arrangement module, a data analysis module, a data comparison module and an execution module:
the information acquisition module is used for planning the urban area so as to acquire basic information and dynamic information of charging stations and charging piles corresponding to the urban area in each area;
the information arrangement module is used for preprocessing the information acquired by the information acquisition module and respectively arranging the preprocessed data into a first data set and a second data set;
wherein the first data set includes the number of charging pilesThe second data set includes charging stake usageCharging performance of charging pileAnd peak charge traffic flow；
The data analysis module is used for carrying out integration calculation on the first data and the second data set so as to generate the charging pile efficiency coefficientAnd the working pressure coefficient of the charging pile；
The efficiency coefficient of the charging pile to be generatedWorking pressure coefficient of charging pileObtaining scheduling coefficients by performing secondary integration calculationThe specific formula is as follows:
wherein:andrespectively is the efficiency coefficient of the charging pileAnd the working pressure coefficient of the charging pileWherein，And (2) and，in order to correct the coefficient of the coefficient,、andis set by customer adjustment or is generated by an analytical function fit;
a data comparison module for comparing the calculated scheduling coefficientsWith a preset scheduling thresholdAnd (5) performing comparative analysis.
In this embodiment: the information acquisition module is responsible for acquiring basic information and dynamic information of charging stations and charging piles in each area through urban area planning. This feature is beneficial to the data acquisition of the system and allows real-time knowledge of the status of the charging stations and the charging posts, including location, number and use.
The information arrangement module is used for preprocessing the data obtained by the information acquisition module and dividing the data into two data sets, namely a first data set and a second data set. The first data set comprises the number of charging pilesThe second data set includes charging stake usageCharging performance of charging pileAnd peak charge traffic flow。
The data analysis module comprehensively calculates the first data set and the second data set to generate the efficiency coefficient of the charging pileAnd the working pressure coefficient of the charging pile. The coefficients are calculated by weight valuesAndcorrection coefficientThe introduction of (3) enables the system to evaluate the effectiveness and working pressure of the charging pile more flexibly. This feature helps to improve the intelligence and data analysis capabilities of the system.
The data comparison module calculates the obtained scheduling coefficientWith a preset scheduling thresholdAnd (5) performing comparative analysis. This determines whether power scheduling is required. This feature allows for intelligent scheduling of the charging piles according to the actual situation to meet the charging demands in different situations.
Through information acquisition, arrangement module, data analysis module and data comparison module, the system can carry out record and feedback to the real-time data of filling the electric pile, thereby make the manager know the state and the demand of filling the electric pile better and optimize the use of filling the electric pile, improve the efficiency of filling the electric pile to reduce the operating pressure who fills the electric pile, the system can adjust the use of filling the electric pile intelligently, ensures to fill the electric pile and all obtain the rational utilization at peak time and low peak time.
Example 2
Referring to fig. 1, the information collecting module includes a dividing unit, and divides the city into a plurality of regions according to the power grid, and the regions are denoted as a region r1, a region r2, a region r3, a region rn.
The information acquisition module also comprises an initial information acquisition unit for inquiring the number of charging piles in the urban construction planning collection area。
The information acquisition unit further comprises a dynamic information acquisition unit for accessing the charging pile to acquire the charging performance of the charging pile。
The dynamic information acquisition unit is also used for recording the single-day activation quantity of the charging piles in the charging stationAnd calculating the number of the charging piles in the charging station, wherein the number of the charging piles activated on a single day is calculatedTo obtain the utilization rate of the charging pileThe specific formula is as follows:
。
the dynamic information acquisition unit is also used for accessing the activation times of the charging piles, acquiring the time period of the highest activation frequency in a single day, and acquiring the traffic flow of the charging peak by acquiring the activation times of the charging piles in the time period of the highest activation frequency in the single day。
In this embodiment: the information acquisition module introduces a dividing unit, and divides the city into a plurality of areas such as an area r1, an area r2 and the like according to the power grid. This feature helps the system to monitor charging station and charging stake conditions in different areas more finely, thereby providing more accurate data support, making management and scheduling more targeted.
The information acquisition module comprises an initial information acquisition unit, and collects the number of charging piles in each area by inquiring city construction planning. The method is beneficial to the comprehensive understanding of the scale of urban charging facilities by the system, and is beneficial to the reasonable planning of charging stations and the resource allocation of charging piles.
The information acquisition module also comprises a dynamic information acquisition unit which acquires the charging performance of the charging pile by accessing the charging pile. This feature enables the system to monitor the operating conditions and performance of the charging stake in real time to ensure that the charging stake is providing service in an optimal condition.
The state information acquisition unit records the single-day activation quantity of the charging piles in the charging stationAnd calculate the single daily excitation of the charging pileThe number of the active charge piles in the charging stationTo obtain the utilization rate of the charging pile. This feature helps the system evaluate the utilization of the charging piles for better scheduling and management.
The dynamic information acquisition unit is also used for accessing the activation times of the charging piles, acquiring the time period of the highest activation frequency in a single day, and acquiring the traffic flow of the charging peak by counting the activation times of the charging piles in the time period. This feature enables the system to better understand the peak hours of the charging station, helping to optimize the schedule to cope with the charging demands of the peak hours.
The regional division and basic information acquisition enable the system to be more comprehensive, the number of charging piles in each region of the city can be comprehensively known, and the construction and layout of the charging station can be planned. And secondly, the dynamic information acquisition unit is added to allow the system to monitor the performance and the service condition of the charging pile in real time, so that the efficiency of the charging pile is improved. In particular, by recording the number of activated charging piles and calculating the utilization rate, the system can accurately evaluate the peak traffic flow, thereby being beneficial to better scheduling charging pile resources and avoiding congestion and performance degradation.
Example 3
Referring to fig. 1, the efficiency coefficient of the charging pileThe method is obtained through calculation according to the following formula:
wherein:、andrespectively the number of the charging pilesCharging pile utilization rateCharging performance of charging pileWherein，，，In order to correct the coefficient of the coefficient,、、andis set by the customer adjustment or is generated by an analytical function fit.
The working pressure coefficient of the charging pileThe method is obtained through calculation according to the following formula:
wherein:、andrespectively is the efficiency coefficient of the charging pileCharging pile utilization ratePeak charge traffic flowWherein，，，In order to correct the coefficient of the coefficient,、、andis set by the customer adjustment or is generated by an analytical function fit.
In this embodiment: efficiency coefficient of charging pileIs introduced with a weight coefficientCorrection coefficientThe values of these coefficients may be adjusted by the customer or generated by an analytical function fit.
The calculation of the working pressure coefficient GZY of the charging pile also adopts a similar method, wherein a weight coefficient is introducedCorrection coefficient. This new feature allows the system to more flexibly evaluate the effectiveness and operating pressure of the charging stake according to actual needs and priorities.
The weight coefficient and the correction coefficient are introduced to enable the system to be more suitable for special requirements of different areas or scenes. The customer can adjust these coefficients as the case may be in order to better meet the objectives of their management and scheduling. Secondly, by introducing the weight coefficient, the system can control the number of the charging piles, the utilization rate and the weight of the charging performance more finely, so that the efficiency of the charging piles can be estimated more accurately. Finally, the new feature also improves the accuracy of the work pressure coefficient of the charging pile, so that the system is better suitable for the peak traffic flow and other dynamic factors.
Example 4
Referring to fig. 1, the data comparison module compares the scheduling coefficientsWith a preset scheduling thresholdPerforming contrast analysis to obtain a comparison result:
when scheduling coefficientsWhen the scheduling threshold is less than or equal toThe charging pile in the representative charging station does not need to schedule power;
when scheduling coefficientsWhen the scheduling threshold is not less thanThe charging posts in the charging station are represented to need to schedule power.
The data module is also used for adjusting the scheduling coefficientWith scheduling thresholdObtaining a comparison difference by combining calculationWill compare the difference to a scheduling thresholdPerforming secondary comparison to obtain a comparison differenceThe method is obtained through calculation according to the following formula:
obtaining a result:
when the worse valueScheduling thresholdWhen the power pressure of the representative charging station is less than or equal to 10%, the power pressure of the representative charging station is in an acceptable range, power adjustment is not needed, and a quick and slow charging mode of the normal charging pile is maintained;
when 10% < worse valueScheduling thresholdWhen the power pressure of the charging station is less than or equal to 15%, 5% of the power pressure of the charging station exceeds the receiving range, performing scheduling operation for increasing the voltage by 10%, keeping more than one third of the charging piles in a quick charging state, and allowing the vehicle to enter charging;
when 15% < worse valueScheduling thresholdWhen the power pressure of the charging station is less than or equal to 25%, representing that the power pressure of the charging station exceeds 15% of the receiving range, executing dispatching operation for increasing the voltage by 30%, keeping more than three-fourths of charging piles in a quick charging state, and allowing the vehicle to enter charging;
when the worse valueScheduling thresholdWhen the power pressure of the charging station is more than 25%, the power pressure of the charging station is fully beyond the receiving range, the dispatching operation of increasing the voltage by 45% is carried out, all the charging piles are kept in a quick charging state, and the vehicle is guided to other areas for charging.
In this embodiment: the data comparison module is responsible for comparing the calculated scheduling coefficient DDX with a preset scheduling threshold in the systemAnd performing comparative analysis, wherein the system can intelligently decide whether the charging pile needs power dispatching according to the dispatching coefficient. If it isLess than or equal toThe system judges that the charging pile in the charging station does not need power dispatching; and if itGreater thanThe system considers that the charging stake in the charging station requires power dispatch. This helps to optimize the allocation and utilization of power resources.
The data module further performs the scheduling of the coefficientsWith scheduling thresholdCombining the calculation to obtain a comparison difference value. The system will thenAnd (3) withAnd carrying out secondary comparison, and adopting different power scheduling measures according to different difference ranges. The advantage of this feature is that it enables the system to evaluate the power pressure conditions of the charging station more accurately and to take different degrees of scheduling according to the pressure level to meet the charging demands in different situations. This helps reducing the power waste and the congestion of the charging pile, improving the utilization efficiency of the charging pile.
When the worse valueScheduling thresholdWhen the power pressure of the representative charging station is less than or equal to 10%, the power pressure of the representative charging station is within the receiving range, the power adjustment is not needed, and the quick and slow charging mode of the normal charging pile is maintained. This feature has the advantage that it ensures that power is supplied at the time of supplyUnder the condition of sufficient charge, the charging pile can operate according to the normal charging speed, and high-quality charging service is provided.
10% < worse valueScheduling thresholdAnd when the power pressure of the charging station is less than or equal to 15 percent and exceeds 5 percent of the receiving range, the system executes scheduling operation for increasing the voltage by 10 percent, and more than one third of the charging piles are kept in a quick charging state, so that the vehicle is allowed to enter charging. This feature helps to ensure the usability of the charging stake under light power pressure and to ensure that the vehicle can be charged in a timely manner.
When 15% < worse valueScheduling thresholdAnd when the power pressure of the charging station is less than or equal to 25 percent and exceeds 15 percent of the receiving range, performing dispatching operation of increasing the voltage by 30 percent, keeping more than three-fourths of charging piles in a quick charging state, and allowing the vehicle to enter charging.
When the worse valueScheduling thresholdWhen the power pressure of the charging station is more than 25%, the system executes dispatching operation of increasing the voltage by 45% on the premise that the power pressure of the charging station is fully beyond the receiving range, keeps all charging piles in a quick charging state, and guides the vehicle to other charging stations for charging. The advantage of this feature is that it ensures that the charging peg in the charging station is in an efficient state of charge in the event of an extremely insufficient power supply and guides the vehicle to other available charging stations to meet the charging demand to the greatest extent.
The system can dynamically schedule the charging piles according to actual power pressure conditions to ensure normal operation of the charging station and charging requirements of the vehicle. Second, by combining the scheduling coefficients with the scheduling threshold to calculate the comparison difference BXZ, the system can more accurately assess the power pressure conditions. Whether scheduling is needed or not can be judged, and power scheduling operations with different degrees can be executed according to the difference value, so that requirements under different conditions can be met.
Examples:
taking a city as an example, dividing 3 areas in a city center, wherein the areas comprise an area r1, an area r2 and an area r3;
wherein the region r1 is internally provided with 20 charging piles, the region r2 is internally provided with 15 charging piles, and the region r3 is internally provided with 10 charging piles
DDX for region r1 is 0.75, DDX for region r2 is 0.45, DDX for region r3 is 0.3, and scheduling threshold DYZ is 0.5;
DDX of the region r1 is larger than the dispatching threshold DYZ, DDX of the region r2 is smaller than the dispatching threshold DYZ, and DDX of the region r3 is smaller than the dispatching threshold DYZ, so that the region r1 needs dispatching power;
the comparative difference BXZ of the region r1 is 40%, so that the condition that the comparative difference BXZ/the dispatch threshold DYZ > 25% is satisfied, a dispatch operation of increasing the voltage by 45% is performed, all the charging piles are kept in a quick charging state, and the vehicle is guided to the region r2 and the region r3 for charging.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
The foregoing is merely a preferred embodiment of the present invention, and it should be noted that it will be apparent to those skilled in the art that several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the scope of the invention.
Claims (4)
1. The utility model provides a new forms of energy electric automobile fills electric pile with intelligent scheduling management system, includes information acquisition module, information arrangement module, data analysis module, data comparison module and execution module, its characterized in that:
the information acquisition module is used for planning the urban area so as to acquire basic information and dynamic information of charging stations and charging piles corresponding to the urban area in each area;
the information acquisition module comprises an initial information acquisition unit for inquiring the number of charging piles in the urban construction planning collection area；
The information acquisition unit further comprises a dynamic information acquisition unit for accessing the charging pile to acquire the charging performance of the charging pile；
The dynamic information acquisition unit is also used for recording the single-day activation quantity of the charging piles in the charging stationAnd calculating the number of the charging piles which are activated in a single day and occupy the charging pile number in the charging station>Thereby obtaining the utilization rate of the charging pile +.>The specific formula is as follows:
；
the dynamic information acquisition unit is also used for accessing the activation times of the charging pileAcquiring the time period of the highest activation frequency in a single day, and acquiring the charging peak traffic flow by acquiring the activation times of the charging pile in the time period of the highest activation frequency in the single day；
The information arrangement module is used for preprocessing the information acquired by the information acquisition module and respectively arranging the preprocessed data into a first data set and a second data set;
wherein the first data set includes the number of charging pilesThe second data set comprises charging stake utilization +.>Charging performance of charging pile->And peak traffic flow->；
The data analysis module is used for carrying out integration calculation on the first data and the second data set so as to generate the charging pile efficiency coefficientAnd the working pressure coefficient of the charging pile +.>；
The efficiency coefficient of the charging pileThe method is obtained through calculation according to the following formula:
；
wherein:、/>and +.>The number of the charging piles is->Charging pile utilization rate->Charging performance of charging pileWherein>，/>，/>，/>For correction factor +.>、/>、/>And +.>Is set by customer adjustment or is generated by an analytical function fit;
the working pressure coefficient of the charging pileThe method is obtained through calculation according to the following formula:
；
wherein:、/>and +.>Respectively is the efficiency coefficient of the charging pile>Charging pile utilization rate->Peak charge traffic +.>Wherein>，/>，/>，/>For correction factor +.>、/>、/>And +.>Is set by customer adjustment or is generated by an analytical function fit;
the efficiency coefficient of the charging pile to be generatedThe working pressure coefficient of the charging pile +.>Performing secondary integration calculation to obtain scheduling coefficient +.>The specific formula is as follows:
；
wherein:and->Respectively is the efficiency coefficient of the charging pile>And the working pressure coefficient of the charging pile +.>Wherein，/>And->，/>For correction factor +.>、/>And +.>Is set by customer adjustment or is generated by an analytical function fit;
a data comparison module for comparing the calculated scheduling coefficientsAnd a preset scheduling threshold->And (5) performing comparative analysis.
2. The intelligent scheduling management system for the new energy electric automobile charging pile according to claim 1, wherein the intelligent scheduling management system is characterized in that: the information acquisition module comprises a dividing unit, and the cities are respectively divided into a plurality of areas according to the power grid and are marked as an area r1, an area r2, an area r3 and an area rn.
3. The intelligent scheduling management system for the new energy electric automobile charging pile according to claim 1, wherein the intelligent scheduling management system is characterized in that: the data comparison module compares the scheduling coefficientsAnd a preset scheduling threshold->Performing contrast analysis to obtain a comparison result:
when scheduling coefficientsThe scheduling threshold value is less than or equal to->The charging pile in the representative charging station does not need to schedule power;
when scheduling coefficientsScheduling threshold time->The charging posts in the charging station are represented to need to schedule power.
4. The intelligent scheduling management system for the new energy electric automobile charging pile according to claim 3, wherein: the data module is also used for adjusting the scheduling coefficientAnd scheduling threshold->Obtaining a comparison difference value by combining calculation>Will compare the difference with the scheduling threshold +.>Performing secondary comparison to obtain comparison difference +.>The method is obtained through calculation according to the following formula:
；
obtaining a result:
when the worse valueScheduling threshold->When the power pressure of the representative charging station is less than or equal to 10%, the power pressure of the representative charging station is in an acceptable range, power adjustment is not needed, and a quick and slow charging mode of the normal charging pile is maintained;
when 10% < worse valueScheduling threshold->When the power pressure of the charging station is less than or equal to 15%, 5% of the power pressure of the charging station exceeds the receiving range, performing scheduling operation for increasing the voltage by 10%, keeping more than one third of the charging piles in a quick charging state, and allowing the vehicle to enter charging;
when 15% < worse valueScheduling threshold->When the power pressure of the charging station is less than or equal to 25%, representing that the power pressure of the charging station exceeds 15% of the receiving range, executing dispatching operation for increasing the voltage by 30%, keeping more than three-fourths of charging piles in a quick charging state, and allowing the vehicle to enter charging;
when the worse valueScheduling threshold->When the power pressure of the charging station is more than 25%, the power pressure of the charging station is fully beyond the receiving range, the dispatching operation of increasing the voltage by 45% is carried out, all the charging piles are kept in a quick charging state, and the vehicle is guided to other areas for charging.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311340923.7A CN117077872B (en) | 2023-10-17 | 2023-10-17 | Intelligent scheduling management system for new energy electric automobile charging pile |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311340923.7A CN117077872B (en) | 2023-10-17 | 2023-10-17 | Intelligent scheduling management system for new energy electric automobile charging pile |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117077872A CN117077872A (en) | 2023-11-17 |
| CN117077872B true CN117077872B (en) | 2023-12-12 |
Family
ID=88706546
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311340923.7A Active CN117077872B (en) | 2023-10-17 | 2023-10-17 | Intelligent scheduling management system for new energy electric automobile charging pile |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117077872B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117644794B (en) * | 2024-01-26 | 2024-04-09 | 昱洁电气科技(无锡)有限公司 | Intelligent period control system based on charging pile |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106849109A (en) * | 2017-03-15 | 2017-06-13 | 国网江苏省电力公司连云港供电公司 | A kind of urban distribution network load control method accessed for scale charging pile |
| CN113370827A (en) * | 2021-07-12 | 2021-09-10 | 众源科技(广东)股份有限公司 | Intelligent switch management system and method based on urban Internet of things application |
| CN115366727A (en) * | 2022-09-14 | 2022-11-22 | 安徽普为智能科技有限责任公司 | Intelligent adjustment control system and method for new energy automobile charging pile |
-
2023
- 2023-10-17 CN CN202311340923.7A patent/CN117077872B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106849109A (en) * | 2017-03-15 | 2017-06-13 | 国网江苏省电力公司连云港供电公司 | A kind of urban distribution network load control method accessed for scale charging pile |
| CN113370827A (en) * | 2021-07-12 | 2021-09-10 | 众源科技(广东)股份有限公司 | Intelligent switch management system and method based on urban Internet of things application |
| CN115366727A (en) * | 2022-09-14 | 2022-11-22 | 安徽普为智能科技有限责任公司 | Intelligent adjustment control system and method for new energy automobile charging pile |
Non-Patent Citations (1)
| Title |
|---|
| 电动汽车充电桩信息维护管理***的设计与应用;吕海博;郭旗;刘国峰;;供用电(第03期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117077872A (en) | 2023-11-17 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN117077872B (en) | Intelligent scheduling management system for new energy electric automobile charging pile | |
| Zhao et al. | Quantifying flexibility of residential electric vehicle charging loads using non-intrusive load extracting algorithm in demand response | |
| Yan et al. | EV charging load simulation and forecasting considering traffic jam and weather to support the integration of renewables and EVs | |
| Wolbertus et al. | Benchmarking charging infrastructure utilization | |
| KR20190068358A (en) | Systems and methods for charge and discharge of electric vehicles | |
| CN109802412B (en) | Optimal configuration method for user side load aggregation quotient energy storage capacity | |
| CN106022530A (en) | Power demand-side flexible load active power prediction method | |
| CN110232219B (en) | Electric vehicle schedulable capacity verification method based on data mining | |
| CN115986798B (en) | Electric energy monitoring and adjusting method of electric vehicle charging station based on complementary coordination | |
| CN109871981A (en) | A kind of part throttle characteristics prediction technique counted and distributed generation resource and electric car influence | |
| US20220294224A1 (en) | Operation decision-making method for centralized cloud energy storage capable of participating in power grid auxiliary services | |
| CN112332433B (en) | Transferable load capacity analysis method for electric vehicle participated in valley filling auxiliary service | |
| CN112581313B (en) | Photovoltaic charging station resource distribution and adjustment method and system | |
| CN117172861A (en) | Mobile charging dynamic pricing method based on user load difference and space constraint | |
| Zhang | Charging schedule optimization of electric bus charging station considering departure timetable | |
| Graber et al. | A stochastic approach to size EV charging stations with support of second life battery storage systems | |
| CN116596203A (en) | Electric vehicle charging station site selection and volume determination method based on improved Bass evaluation model | |
| CN115829236A (en) | Technical support system for virtual power plant to participate in power market | |
| CN113595122A (en) | Aggregation response capability determination method for distributed energy storage system | |
| CN109636201B (en) | Charging service bicycle accounting method | |
| CN114239903B (en) | Method for calculating openability capacity of power distribution network based on equipment concurrency rate | |
| CN118014169B (en) | Energy network optimization method and device based on road lamp light storage and charging | |
| CN113012460B (en) | Single-line bus charging control system and method | |
| CN116468220A (en) | Vehicle network interaction optimization control method for balancing battery aging cost and electric power market income | |
| CN115394087B (en) | Parking resource supply gap evaluation method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |