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CN112477674A - Remote cluster charging control method, device and system for charging pile - Google Patents

Remote cluster charging control method, device and system for charging pile Download PDF

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Publication number
CN112477674A
CN112477674A CN202011276894.9A CN202011276894A CN112477674A CN 112477674 A CN112477674 A CN 112477674A CN 202011276894 A CN202011276894 A CN 202011276894A CN 112477674 A CN112477674 A CN 112477674A
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China
Prior art keywords
charging
data
charging pile
electric vehicle
pile
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Pending
Application number
CN202011276894.9A
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Chinese (zh)
Inventor
郭颖斯
程涛
王翔龙
马强骏
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Shenzhen Cosber Industrial Co ltd
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Shenzhen Cosber Industrial Co ltd
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Publication date
Application filed by Shenzhen Cosber Industrial Co ltd filed Critical Shenzhen Cosber Industrial Co ltd
Priority to CN202011276894.9A priority Critical patent/CN112477674A/en
Priority to LU502515A priority patent/LU502515B1/en
Priority to PCT/CN2021/079026 priority patent/WO2022099951A1/en
Publication of CN112477674A publication Critical patent/CN112477674A/en
Pending legal-status Critical Current

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L3/00—Electric devices on electrically-propelled vehicles for safety purposes; Monitoring operating variables, e.g. speed, deceleration or energy consumption
    • B60L3/12—Recording operating variables ; Monitoring of operating variables
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/60—Monitoring or controlling charging stations
    • B60L53/67—Controlling two or more charging stations
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/60—Monitoring or controlling charging stations
    • B60L53/62—Monitoring or controlling charging stations in response to charging parameters, e.g. current, voltage or electrical charge
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/60—Monitoring or controlling charging stations
    • B60L53/63—Monitoring or controlling charging stations in response to network capacity
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
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    • B60L53/60—Monitoring or controlling charging stations
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    • B60L53/60—Monitoring or controlling charging stations
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/60—Monitoring or controlling charging stations
    • B60L53/68—Off-site monitoring or control, e.g. remote control
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L58/00—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles
    • B60L58/10—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries
    • B60L58/12—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries responding to state of charge [SoC]
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2240/00—Control parameters of input or output; Target parameters
    • B60L2240/40—Drive Train control parameters
    • B60L2240/54—Drive Train control parameters related to batteries
    • B60L2240/547—Voltage
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2240/00—Control parameters of input or output; Target parameters
    • B60L2240/40—Drive Train control parameters
    • B60L2240/54—Drive Train control parameters related to batteries
    • B60L2240/549—Current
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2240/00—Control parameters of input or output; Target parameters
    • B60L2240/70—Interactions with external data bases, e.g. traffic centres
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2240/00—Control parameters of input or output; Target parameters
    • B60L2240/80—Time limits
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2260/00—Operating Modes
    • B60L2260/40—Control modes
    • B60L2260/44—Control modes by parameter estimation
    • 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
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/70—Energy storage systems for electromobility, e.g. batteries
    • 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
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/7072—Electromobility specific charging systems or methods for batteries, ultracapacitors, supercapacitors or double-layer capacitors
    • 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
    • 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
    • Y02T90/16—Information or communication technologies improving the operation of electric vehicles
    • 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
    • Y02T90/16—Information or communication technologies improving the operation of electric vehicles
    • Y02T90/167—Systems integrating technologies related to power network operation and communication or information technologies for supporting the interoperability of electric or hybrid vehicles, i.e. smartgrids as interface for battery charging of electric vehicles [EV] or hybrid vehicles [HEV]
    • 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
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S30/00—Systems supporting specific end-user applications in the sector of transportation
    • Y04S30/10—Systems supporting the interoperability of electric or hybrid vehicles
    • Y04S30/12—Remote or cooperative charging

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Sustainable Development (AREA)
  • Sustainable Energy (AREA)
  • Charge And Discharge Circuits For Batteries Or The Like (AREA)
  • Electric Propulsion And Braking For Vehicles (AREA)

Abstract

The invention provides a remote cluster charging control method of a charging pile, which comprises the following steps: collecting battery state related data of an electric vehicle to be charged; inquiring historical charging data of a charging pile corresponding to the electric vehicle to be charged; comparing and calculating the battery state related data of the electric vehicle to be charged with historical charging data of a charging pile to generate a preliminary charging parameter; inquiring all charging pile data stored in the center cloud and relevant data of the power distribution network; calculating the preliminary charging parameters, all charging pile data and relevant data of the power distribution network by adopting a genetic algorithm to obtain optimal values of the charging parameters; and sending the optimal value of the charging parameter to a charging pile, and charging the electric vehicle by the charging pile. The invention also provides a device and a system for remote cluster charging control of the charging pile. The invention can manage large-scale charging piles, solve the problems of unbalanced electric load and overhigh electricity price of a power grid, and ensure that the information of the charging piles is transmitted quickly and safely.

Description

Remote cluster charging control method, device and system for charging pile
Technical Field
The invention relates to the field of new energy and control engineering, in particular to a remote cluster charging control method, device and system for a charging pile.
Background
In order to solve the environmental and energy problems caused by the pollution caused by the exhaust emission of the traditional fuel oil vehicles and the excessive consumption of petroleum resources, Electric Vehicles (EVs) become one of the trends and hot spots of the international vehicle development nowadays due to the good environmental protection and energy saving characteristics of the electric vehicles. However, the impact of the access of a large number of electric vehicle loads to the power grid gradually draws attention of power grid operators and researchers. Research shows that the charging behavior of large-scale electric automobiles can bring influences such as local voltage drop of a system, transformer overload, load peak peaking and the like.
At present, the construction scale of the electric vehicle charging station is generally small, the configuration quantity of charging piles is generally 5-30, the communication data volume is not large, and the configuration of the monitoring system of the current charging station can completely meet the requirements. However, with the continuous promotion of the popularization speed of the electric automobile, the problems of unbalanced power load, overhigh electricity price and the like are obvious.
Therefore, a remote cluster charging control method for charging piles is needed to solve the above problems.
Disclosure of Invention
In view of this, an embodiment of the present invention provides a remote cluster charging control method, device and system for a charging pile, and aims to solve the problems of unbalanced electrical load and excessive electricity price in large-scale charging pile management in the prior art.
In order to achieve the above object, a first technical solution adopted by the present invention is to provide a remote cluster charging control method for a charging pile, including:
collecting battery state related data of an electric vehicle to be charged;
inquiring historical charging data of a charging pile corresponding to the electric vehicle to be charged;
comparing and calculating the battery state related data of the electric vehicle to be charged with historical charging data of a charging pile to generate a preliminary charging parameter;
inquiring data of all charging piles in the center cloud and related data of the power distribution network;
calculating the preliminary charging parameters, all charging pile data and relevant data of the power distribution network by adopting a genetic algorithm to obtain optimal values of the charging parameters;
and sending the optimal value of the charging parameter to a charging pile, and charging the electric vehicle by the charging pile.
Preferably, the calculating the preliminary charging parameter, all charging pile data and relevant data of the power distribution network by using a genetic algorithm to obtain the optimal value of the charging parameter comprises:
initializing time-of-use electricity price and power distribution network electricity load information;
acquiring relevant parameters of an electric vehicle to be charged;
initializing relevant parameters of a genetic algorithm;
generating an initialization population of the charging start time and the charging duration, and carrying out gene coding;
calculating the fitness value of each individual of the current charging starting time and the charging duration;
judging whether the iteration times reach a preset threshold value, if not, selecting a parent evolutionary individual by adopting a roulette algorithm, otherwise, selecting an optimal individual, and generating an optimal value of the charging parameter;
wherein, the gene code is Gray code, and the code number is 8.
Preferably, the selecting the optimal individual comprises:
and the minimum value of the fitness value of each individual of the current charging starting time and the charging duration is the optimal individual.
Preferably, the acquiring the battery state related data of the electric vehicle to be charged includes:
the related data is battery voltage and current data of the electric vehicle to be charged.
Preferably, the querying historical charging data of the charging pile corresponding to the electric vehicle to be charged further includes:
historical charging data are preset in the charging pile, and the data comprise charging time, charging duration and charging electricity price.
Preferably, the querying of all charging pile data in the center cloud and the related data of the power distribution network include:
fill electric pile data and include: charging state, charging duration and charging price;
the relevant data of the power distribution network comprises: current voltage, grid peak-valley time period, time-of-use electricity price.
In order to achieve the purpose, the second technical scheme adopted by the invention is as follows: the utility model provides a fill remote cluster charging control's of electric pile device includes:
a data acquisition module: the system is used for acquiring battery state related data of the electric vehicle to be charged;
a first query module: the charging system is used for inquiring historical charging data of a charging pile corresponding to the electric vehicle to be charged;
a first calculation module: the charging system is used for comparing and calculating the battery state related data of the electric vehicle to be charged with the historical charging data of the charging pile to generate a preliminary charging parameter;
a second query module: the system comprises a central cloud, a charging pile management system and a power distribution network, wherein the central cloud is used for storing charging pile data of a charging pile;
a second calculation module: the system comprises a data acquisition module, a data acquisition module and a data transmission module, wherein the data acquisition module is used for acquiring data of charging parameters of a power distribution network;
a sending module: and the optimal value of the charging parameter is sent to a charging pile, and the charging pile charges the electric vehicle.
In order to achieve the above object, the third technical solution adopted by the present invention is: the utility model provides a fill long-range cluster of electric pile charge control's system includes:
the system comprises a charging pile, a charging pile collector, a central cloud server, a power distribution network system and a device for realizing the modules;
the charging pile is connected with the charging pile collector through a wireless or wired network;
the charging pile collector is connected with a device for realizing the modules through a wireless or wired network;
the device for realizing the modules is connected with the central cloud server through a wireless network;
the device for realizing the module is connected with a power distribution network system through a wireless network.
In order to achieve the above object, the fourth technical solution adopted by the present invention is: provided is an electronic device including: the system comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the computer program to realize the steps of the method.
In order to achieve the above object, a fifth technical solution adopted by the present invention is: a readable storage medium is provided, on which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned method.
The invention provides a remote cluster charging control method of a charging pile, which comprises the steps of collecting battery state related data of an electric vehicle to be charged; inquiring historical charging data of a charging pile corresponding to the electric vehicle to be charged; comparing and calculating the battery state related data of the electric vehicle to be charged with historical charging data of a charging pile to generate a preliminary charging parameter; inquiring all charging pile data stored in the center cloud and relevant data of the power distribution network; calculating the preliminary charging parameters, all charging pile data and relevant data of the power distribution network by adopting a genetic algorithm to obtain optimal values of the charging parameters; and sending the optimal value of the charging parameter to a charging pile, and charging the electric vehicle by the charging pile, so that large-scale charging piles can be managed, and the problems of unbalanced power load and overhigh electricity price of a power grid are solved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the structures shown in the drawings without creative efforts.
Fig. 1 is a flowchart of a charging control method for a remote cluster of charging piles according to a first embodiment of the present invention;
FIG. 2 is a flow chart of a genetic algorithm according to a second embodiment of the present invention;
fig. 3 is a schematic block diagram of a charging control device of a remote cluster of charging piles according to a third embodiment of the present invention;
fig. 4 is a schematic structural diagram of a charging pile remote cluster charging control system according to a fourth embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device according to a fifth embodiment of the invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In addition, technical solutions between various embodiments may be combined with each other, but must be realized by a person skilled in the art, and when the technical solutions are contradictory or cannot be realized, such a combination should not be considered to exist, and is not within the protection scope of the present invention.
The invention is further described in detail below with reference to the figures and the specific embodiments.
Referring to fig. 1, fig. 1 is a flowchart of a method for controlling charging of a remote cluster of charging piles. In the embodiment of the invention, the method for controlling the remote cluster charging of the charging pile comprises the following steps:
step S11: collecting battery state related data of an electric vehicle to be charged;
specifically, the charging pile collector collects battery state related data of the electric vehicle to be charged, such as voltage, current and other data of the battery;
step S12: inquiring historical charging data of a charging pile corresponding to the electric vehicle to be charged;
specifically, the charging pile collector queries historical charging data of a charging pile corresponding to the electric vehicle to be charged, such as the last charging electric quantity and electricity price of the charging pile;
step S13: comparing and calculating the battery state related data of the electric vehicle to be charged with historical charging data of a charging pile to generate a preliminary charging parameter;
specifically, the battery state related data of the electric vehicle to be charged is compared with historical charging data of a charging pile for calculation, for example, if the last charging time and the current charging time are in the same time period, the last charging electricity price is used as the preliminary electricity price to be charged;
step S14: inquiring all charging pile data stored in the center cloud and relevant data of the power distribution network;
specifically, all charging pile data stored in a center cloud and relevant data of the power distribution network are inquired. For example, data such as charging states and charging durations of all charging piles in a center cloud and data such as power grid loads of a power distribution network are inquired;
step S15: calculating the preliminary charging parameters, all charging pile data and relevant data of the power distribution network by adopting a genetic algorithm to obtain optimal values of the charging parameters;
specifically, a genetic algorithm is adopted to calculate the preliminary charging parameters, all charging pile data and relevant data of the power distribution network, and the optimal value of the charging parameters is obtained. Referring to fig. 2, the specific process of the genetic algorithm is:
step S21: initializing time-of-use electricity price and power distribution network electricity load information;
step S22: acquiring relevant parameters of an electric vehicle to be charged;
step S23: initializing relevant parameters of a genetic algorithm;
specifically, for example, the population scale is set to be 20, the iteration number is 10000, and the variation probability is 1%;
step S24: generating an initialization population of the charging start time and the charging duration, and carrying out gene coding;
specifically, the gene coding is carried out by adopting a Gray code mode, and the number of coding bits is 8;
step S25: calculating the fitness value of each individual of the current charging starting time and the charging duration;
specifically, the larger the individual fitness value is, the lower the charging cost of the user is, and the smaller the peak-valley difference and the maximum peak value of the power grid are;
step S26: judging whether the iteration number reaches a preset threshold value, if not, entering a step S27, otherwise, entering a step S29;
step S27: selecting parent evolutionary individuals by adopting a roulette algorithm;
specifically, the parameters in the step S23 are selected to perform inheritance and large variation operation, and the population subjected to the large variation operation can effectively avoid the premature condition of the traditional genetic algorithm;
step S28: carrying out heredity and mutation on the selected individuals;
step S29: and selecting the optimal individual to generate the optimal value of the charging parameter.
Step S16: sending the optimal value of the charging parameter to a charging pile, and charging the electric vehicle by the charging pile;
specifically, the optimal value of the charging parameter is sent to a charging pile collector, the charging pile collector sends the charging parameter to a charging pile, and the charging pile charges the electric vehicle according to the charging parameter.
Referring to fig. 3, fig. 3 is a schematic block diagram of a charging control device of a remote cluster of charging piles. In an embodiment of the present invention, the charging pile remote cluster charging control apparatus includes:
the data acquisition module 300: the system is used for acquiring battery state related data of the electric vehicle to be charged;
specifically, data such as voltage, current and the like of the battery are collected;
the first query module 310: the charging system is used for inquiring historical charging data of a charging pile corresponding to the electric vehicle to be charged;
specifically, data such as the last charging electric quantity and the electricity price of the charging pile are inquired;
the first calculation module 320: the charging system is used for comparing and calculating the battery state related data of the electric vehicle to be charged with the historical charging data of the charging pile to generate a preliminary charging parameter;
specifically, for example, if the last charging time and the current time to be charged are in the same time period, the last charging electricity price is used as the preliminary electricity price to be charged;
the second query module 330: the system comprises a central cloud, a charging pile management system and a power distribution network, wherein the central cloud is used for storing charging pile data of a charging pile;
specifically, data such as charging states and charging durations of all charging piles in a center cloud and data such as power grid loads of a power distribution network are inquired;
the second calculation module 340: the system comprises a data acquisition module, a data acquisition module and a data transmission module, wherein the data acquisition module is used for acquiring data of charging parameters of a power distribution network;
specifically, a genetic algorithm is adopted to calculate the fitness value of each individual of the current charging starting time and the charging duration to obtain the optimal value of the charging parameter;
the sending module 350: the charging system is used for sending the optimal value of the charging parameter to a charging pile, and the charging pile charges the electric vehicle;
specifically, the optimal value of the charging parameter is sent to a charging pile collector, the charging pile collector sends the charging parameter to a charging pile, and the charging pile charges the electric vehicle according to the charging parameter.
Referring to fig. 4, fig. 4 is a schematic structural diagram of a charging pile remote cluster charging control system. In an embodiment of the present invention, a schematic structural diagram of the charging control system for remote cluster of charging piles includes:
the system comprises N charging piles, charging pile collectors 1-M, a charging pile remote cluster charging control device, a central cloud server and a power distribution network system;
the N charging piles are respectively connected with the charging pile collectors 1 to M through a wireless or wired network;
the charging pile collectors 1 to M are connected with a charging pile remote cluster charging control device through a wireless or wired network;
the charging pile remote cluster charging control device is connected with the central cloud server through a wireless network;
the charging pile remote cluster charging control device is connected with the power distribution network system through a wireless network;
in the system, the charging pile collectors 1 to M are equivalent to edge servers, and the central cloud server is equivalent to a cloud center. The edge server can not only request services and data from the cloud center, but also perform partial data calculation, so that the data volume uploaded to the cloud center is reduced, and the data processing efficiency is improved; the cloud center saves all relevant data such as charging states of the charging piles, can comprehensively know states of the charging piles managed, calculates optimal charging parameters of the current charging piles according to data such as power grid loads of a power distribution network, achieves a large-scale orderly charging function of the charging piles, can also perform centralized monitoring on the charging piles, and achieves an unmanned remote monitoring function.
Fig. 5 is a schematic structural diagram of an electronic device according to a fifth embodiment of the invention. The electronic device can be used for realizing the file uploading method in the embodiment. As shown in fig. 5, the electronic device mainly includes: a memory 501, a processor 502, a bus 503, and computer programs stored on the memory 501 and executable on the processor 502, the memory 501 and the processor 502 being connected by the bus 503. The processor 502, when executing the computer program, implements the file uploading method in the foregoing embodiments. Wherein the number of processors may be one or more.
The Memory 501 may be a high-speed Random Access Memory (RAM) Memory or a non-volatile Memory (non-volatile Memory), such as a disk Memory. The memory 501 is used for storing executable program code, and the processor 502 is coupled to the memory 501.
Further, an embodiment of the present application also provides a readable storage medium, where the readable storage medium may be provided in the electronic device in the foregoing embodiments, and the readable storage medium may be the memory in the foregoing embodiment shown in fig. 5.
The readable storage medium has stored thereon a computer program which, when executed by a processor, implements the file upload method in the foregoing embodiments. Further, the computer-readable storage medium may be various media that can store program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a RAM, a magnetic disk, or an optical disk.
The invention provides a remote cluster charging control method of a charging pile, which comprises the steps of collecting battery state related data of an electric vehicle to be charged; inquiring historical charging data of a charging pile corresponding to the electric vehicle to be charged; comparing and calculating the battery state related data of the electric vehicle to be charged with historical charging data of a charging pile to generate a preliminary charging parameter; inquiring all charging pile data stored in the center cloud and relevant data of the power distribution network; calculating the preliminary charging parameters, all charging pile data and relevant data of the power distribution network by adopting a genetic algorithm to obtain optimal values of the charging parameters; and sending the optimal value of the charging parameter to a charging pile, and charging the electric vehicle by the charging pile, so that large-scale charging piles can be managed, the problems of unbalanced power load and overhigh electricity price of a power grid are solved, and the information of each charging pile is ensured to be transmitted quickly and safely.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of modules is merely a division of logical functions, and an actual implementation may have another division, for example, a plurality of modules or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or modules, and may be in an electrical, mechanical or other form.
Modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical modules, may be located in one place, or may be distributed on a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
In addition, functional modules in the embodiments of the present application may be integrated into one processing module, or each of the modules may exist alone physically, or two or more modules are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode.
The integrated module, if implemented in the form of a software functional module and sold or used as a separate product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a readable storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method of the embodiments of the present application. And the aforementioned readable storage medium includes: various media capable of storing program codes, such as a U disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk.
It should be noted that, for the sake of simplicity, the above-mentioned method embodiments are described as a series of acts or combinations, but those skilled in the art should understand that the present application is not limited by the described order of acts, as some steps may be performed in other orders or simultaneously according to the present application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention, and all modifications and equivalents made by the contents of the specification and drawings or directly/indirectly applied to other related technical fields within the spirit of the present invention are included in the scope of the present invention.

Claims (10)

1. A remote cluster charging control method for a charging pile is characterized by comprising the following steps:
collecting battery state related data of an electric vehicle to be charged;
inquiring historical charging data of a charging pile corresponding to the electric vehicle to be charged;
comparing and calculating the battery state related data of the electric vehicle to be charged with historical charging data of a charging pile to generate a preliminary charging parameter;
inquiring data of all charging piles in the center cloud and related data of the power distribution network;
calculating the preliminary charging parameters, all charging pile data and relevant data of the power distribution network by adopting a genetic algorithm to obtain optimal values of the charging parameters;
and sending the optimal value of the charging parameter to a charging pile, and charging the electric vehicle by the charging pile.
2. The method of claim 1, wherein the calculating the preliminary charging parameters, all charging pile data and the related data of the distribution network by using a genetic algorithm to obtain the optimal value of the charging parameters comprises:
initializing time-of-use electricity price and power distribution network electricity load information;
acquiring relevant parameters of an electric vehicle to be charged;
initializing relevant parameters of a genetic algorithm;
generating an initialization population of the charging start time and the charging duration, and carrying out gene coding;
calculating the fitness value of each individual of the current charging starting time and the charging duration;
judging whether the iteration times reach a preset threshold value, if not, selecting a parent evolutionary individual by adopting a roulette algorithm, otherwise, selecting an optimal individual, and generating an optimal value of the charging parameter;
wherein, the gene code is Gray code, and the code number is 8.
3. The method of claim 2, wherein selecting the optimal individual comprises:
and the minimum value of the fitness value of each individual of the current charging starting time and the charging duration is the optimal individual.
4. The method of claim 1, wherein the collecting battery status related data of the electric vehicle to be charged comprises:
the related data is battery voltage and current data of the electric vehicle to be charged.
5. The method of claim 1, wherein before querying the historical charging data of the charging post corresponding to the electric vehicle to be charged, the method further comprises:
historical charging data are preset in the charging pile, and the data comprise charging time, charging duration and charging electricity price.
6. The method of claim 1, wherein the querying of all charging pile data in the central cloud and the relevant data of the power distribution network comprises:
fill electric pile data and include: charging state, charging duration and charging price;
the relevant data of the power distribution network comprises: current voltage, grid peak-valley time period, time-of-use electricity price.
7. An apparatus for remote cluster charging control of charging piles, the apparatus comprising:
a data acquisition module: the system is used for acquiring battery state related data of the electric vehicle to be charged;
a first query module: the charging system is used for inquiring historical charging data of a charging pile corresponding to the electric vehicle to be charged;
a first calculation module: the charging system is used for comparing and calculating the battery state related data of the electric vehicle to be charged with the historical charging data of the charging pile to generate a preliminary charging parameter;
a second query module: the system comprises a central cloud, a charging pile management system and a power distribution network, wherein the central cloud is used for storing charging pile data of a charging pile;
a second calculation module: the system comprises a data acquisition module, a data acquisition module and a data transmission module, wherein the data acquisition module is used for acquiring data of charging parameters of a power distribution network;
a sending module: and the optimal value of the charging parameter is sent to a charging pile, and the charging pile charges the electric vehicle.
8. The utility model provides a fill long-range cluster charging control's of electric pile system which characterized in that includes:
charging piles, charging pile collectors, central cloud servers, power distribution network systems and the apparatus of any of claims 1 to 7;
the charging pile is connected with the charging pile collector through a wireless or wired network;
the charging pile collector is connected with the device according to any one of claims 1 to 7 through a wireless or wired network;
the apparatus of any of claims 1 to 7 connected to a central cloud server via a wireless network;
the device of any one of claims 1 to 7 connected to a power distribution network system via a wireless network.
9. An electronic device, comprising: memory, processor and computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method of any one of claims 1 to 6 when executing the computer program.
10. A readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 6.
CN202011276894.9A 2020-11-16 2020-11-16 Remote cluster charging control method, device and system for charging pile Pending CN112477674A (en)

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