CN111391692B - Electric vehicle cluster ordered charging and discharging scheduling system and method based on vehicle cabin temperature whole-process differential control - Google Patents
Electric vehicle cluster ordered charging and discharging scheduling system and method based on vehicle cabin temperature whole-process differential control Download PDFInfo
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Abstract
The invention discloses an electric automobile ordered charging and discharging system and method based on cabin temperature difference control, wherein the electric automobile ordered charging and discharging system comprises: the system comprises a cloud monitoring and scheduling platform, a vehicle-mounted data acquisition control system, a charging station management system and a power distribution network data acquisition system. The method has the characteristics that the energy consumption of the air-conditioning battery in the whole process of dispatching is controlled and participated in is dispatched by detecting the temperature in the cabin and adjusting the set temperature of the vehicle-mounted air conditioner in a differentiation manner, so that the driving mileage of the electric vehicle is initiatively preconditioned, the ordered charging and discharging control variable of the electric vehicle is innovated, the ordered charging and discharging control boundary condition of the electric vehicle is expanded, the ordered charging and discharging dispatching of the electric vehicle cluster can be realized more finely and in a differentiation manner, the load of the power grid is served for ' peak clipping and valley filling ', and the load of the power grid is relieved from peak clipping and peak adding '.
Description
The technical field is as follows:
the invention belongs to the field of ordered charging and discharging of electric automobiles, and particularly relates to an ordered charging and discharging scheduling system and method of an electric automobile cluster based on differentiation control of the whole process of cabin temperature.
Background art:
the use of the traditional internal combustion engine automobile aggravates the global energy crisis and the environmental problem, and the development of a new energy automobile which is energy-saving, clean and high in conversion efficiency is an effective way. The electric automobile is considered to be the best substitute of the traditional automobile in the near term, not only has high energy conversion efficiency, but also can realize real zero emission due to the use of electric energy as power, and reduces the pollution of automobile exhaust to the environment. The electric automobile is one of important development directions of new energy automobiles, and related policies for promoting the development of the electric automobile are also successively issued by countries all over the world.
With the rapid development of electric vehicles, the related problems caused by the large-scale use of electric vehicles have come to the fore. On one hand, the mobility of the electric automobile brings randomness in distribution, and the large-scale uncertainty brings new challenges to power grid dispatching. If the electric automobile is charged disorderly, the peak-to-peak load of the power grid is caused, and the electric automobile is used as a large-scale distributed power supply, and can be reasonably dispatched and serve the power grid to perform the functions of peak clipping and valley filling; on the other hand, due to the limitation of energy storage technology, the specific energy and specific density of the battery are far lower than those of fossil energy, and further the endurance mileage worry has to be paid attention to. Particularly in summer and winter, due to the use of the vehicle-mounted air conditioner, the load of a power battery is increased, the endurance mileage of the electric vehicle is sharply reduced, and finally the load on the demand side of the power grid is increased. The method is an effective way for prolonging the endurance mileage by reducing the energy consumption of other loads except a power system. By expanding the charging range of the electric automobile in summer and winter and adopting reasonable path planning, the user satisfaction degree of the electric automobile can be increased, and the local overload of a power grid can be relieved.
The invention content is as follows:
the technical problem to be solved by the invention is as follows: the electric automobile cluster ordered charging and discharging scheduling system and method based on vehicle cabin temperature whole-process differentiation control increase the endurance mileage of the electric automobile by controlling the vehicle-mounted air conditioner consumption of the whole process of the electric automobile driving path planning through differentiation, enable the electric automobile to flexibly participate in ordered charging and discharging scheduling of a power grid, service the load of the power grid to carry out peak clipping and valley filling, and relieve the load of the power grid to carry out peak adding on the peak.
The technical scheme adopted by the invention for solving the technical problems is as follows:
electric automobile cluster is charging and discharging dispatch system in order based on cabin temperature overall process differentiation control, its characterized in that, this system contains a dispatch platform and three subsystem:
the cloud monitoring and scheduling platform: receiving and displaying the running data and states of the electric vehicle, the charging station and the power distribution network in real time, obtaining the temperature differential regulation and control and the ordered charging and discharging strategy of the electric vehicle through data processing, and issuing the strategy to the corresponding subsystem; monitoring the electric automobile participation power grid dispatching condition, monitoring the electric automobile distribution thermodynamic diagram, monitoring abnormity in electric automobile dispatching and warning;
vehicle-mounted data acquisition control system: acquiring and processing data of temperature change and mileage change in the cabin in the whole process of the participation and scheduling of the electric automobile, and uploading the processed driving data to a cloud monitoring and scheduling platform;
charging station management system: acquiring and processing the use condition of a charging pile of the charging station, the charging and discharging state of an electric automobile of the charging pile, the time of the electric automobile to be connected into the charging pile, the time of the electric automobile to leave the charging pile in anticipation and the expected electric quantity of the battery of the electric automobile, uploading the processed data to a cloud monitoring and scheduling platform, and receiving an ordered charging and discharging instruction issued by the cloud monitoring and scheduling platform;
distribution network data acquisition system: the method comprises the steps of collecting real-time load of a power grid, predicting a power grid load curve by combining historical load data of the power grid, and uploading the processed power grid load data to a cloud monitoring and dispatching platform.
Further, the cloud monitoring and scheduling platform comprises an electric vehicle ordered charging and discharging scheduling module, a communication module, a database and an interface display module;
the electric automobile orderly charging and discharging scheduling module: planning orderly charging and discharging of the electric automobile according to the collected data of the electric automobile, the charging pile and the power distribution network so as to deal with load change of the power distribution network; the planning of the ordered charging and discharging of the electric automobile comprises the following steps: the method comprises the steps that a vehicle-mounted air conditioner set temperature adjusting scheme is generated in a differentiated mode by combining the real-time load of a power grid, a power grid predicted load curve, the using state of a charging pile and the running state of the electric automobile and considering the remaining endurance mileage and the running destination of the electric automobile, so that the energy consumption of the whole automobile is reduced, the ordered charging and discharging planning range of the electric automobile is expanded, the running path from the electric automobile to a target charging pile is optimized, and the purpose of staggering the peak charging place and the charging time is achieved;
the communication module adopts power line carrier communication and a 4G/5G network to issue the temperature differential regulation and control and the ordered charging and discharging strategy of the electric automobile to the charging pile management system, so that the data communication between the cloud monitoring and scheduling platform and each subsystem is realized;
the database stores data uploaded by each subsystem and strategy data generated by the platform;
the interface display module realizes the visualization of the electric automobile participating in the power grid dispatching condition, the electric automobile distribution thermodynamic diagram, the monitoring of the abnormity in the electric automobile dispatching and the warning.
Furthermore, the vehicle-mounted data acquisition control system comprises a vehicle cabin internal and external temperature detection module, an infrared detection module, a driving data acquisition module, a data processing and control module and a communication module;
the vehicle cabin internal and external temperature detection module is used for detecting the current internal and external temperatures of the vehicle cabin of the electric vehicle for a period, and provides a reference basis for the subsequent differential regulation and control of the vehicle-mounted air conditioner temperature by combining the comfort temperature of a human body;
the infrared detection module detects the number of people in the current electric automobile and provides a reference basis for the subsequent calculation of the heat dissipation capacity of the human body;
the driving data acquisition module acquires the driving destination of the electric automobile, the residual electric quantity of the power battery, the running state of an air conditioner in the automobile, the position of the automobile and the speed of the automobile and provides data for the subsequent calculation of the ordered charging and discharging planning of the electric automobile;
the data processing and control module is used for calculating the remaining endurance mileage of the electric automobile by considering the current average power consumption of the whole automobile and providing data for the subsequent calculation of the ordered charging and discharging planning of the electric automobile; receiving an upper layer control instruction, executing differential adjustment of set temperature of the vehicle-mounted air conditioner, and providing planning information of an ordered charging and discharging path of the electric vehicle;
the communication module uploads the electric vehicle driving data to the cloud monitoring and scheduling platform by adopting a 4G/5G network, and receives the ordered charging and discharging temperature regulation and control and path planning instructions issued by the cloud monitoring and scheduling platform.
The electric vehicle cluster ordered charging and discharging scheduling method based on vehicle cabin temperature whole-process differential control is characterized by comprising the following steps of: the cloud monitoring and dispatching platform equivalently uses an electric automobile group as a mobile load and a distributed power supply, realizes control of whole automobile energy consumption and electric automobile endurance of the electric automobiles through differential regulation of the whole cabin temperature process, enlarges a control boundary and a power grid load bearing boundary of the electric automobile cluster ordered charging and discharging path planning, enables the electric automobiles to flexibly participate in peak clipping and valley filling of power grid load, and relieves peak-to-peak load adding of the power grid load;
according to the obtained data of the electric automobile, the charging station and the power distribution network, constructing an electric automobile cluster ordered charging and discharging scheduling model by taking minimum power grid daily load variance fluctuation as a scheduling target; the electric vehicle cluster ordered charging and discharging scheduling comprises planning of a driving path from an electric vehicle to a target charging station and differential control of the whole process of the vehicle cabin temperature considering the whole vehicle energy consumption of the electric vehicle;
forming a constraint condition of the electric automobile ordered charging and discharging scheduling model according to a preset electric automobile temperature controllable range, an electric automobile driving mileage range and an electric automobile electric quantity state; according to the real-time load of the power grid and the predicted load curve of the power grid, in combination with the use state of the charging pile and the running state of the electric vehicle, the temperature in the cabin is differentially regulated within the temperature controllable range to reduce the energy consumption of the whole vehicle, and the running path from the electric vehicle to a target charging station is optimized within the predicted range of the endurance mileage;
solving an optimal solution of the ordered charging and discharging scheduling model of the electric automobile according to the constraint conditions of the ordered charging and discharging scheduling model of the electric automobile; planning a running path of the electric automobile and differentially controlling the temperature in the cabin of the electric automobile according to the optimal solution under the constraint condition.
The ordered charging and discharging scheduling modeling steps of the electric automobile cluster based on the differentiation control of the whole process of the cabin temperature are as follows:
step S101, the whole process refers to a process that electric vehicle users participate in differentiated temperature control and path planning of ordered charging and discharging scheduling of a power grid, and differentiation is actually the temperature control difference of each electric vehicle caused by the difference of the users in cold and heat requirements, the difference of temperature change in an cabin and the difference of driving speed of the electric vehicle; electric steam is adjusted through differentiationTemperature T set by vehicle air conditioner i S (T), maintaining the temperature T of the electric automobile cabin i V (t) in a certain temperature range, controlling the power consumption of the air conditioner to reduce the average energy consumption of the electric automobile and increasing and changing the endurance mileage M of the electric automobile i (t) of (d). Constructing a temperature change model of the monomer electric automobile cabin:
wherein, T i V (t) represents the ith electric automobile cabin temperature; t is am (t) represents the ambient temperature and,
the air-conditioning cooling capacity of the ith electric automobile is expressed;
representing the human body heat dissipation of q individuals in the ith electric automobile;
the heat dissipation capacity of other equipment in the ith electric automobile cabin is represented; p i ac (t) represents the air-conditioning refrigeration energy efficiency ratio, COP represents the equivalent heat capacity, which is the product of the volume of the cabin and the air specific heat capacity, and R represents the equivalent heat resistance and is related to the heat conductivity coefficient of the cabin;
step S102, according to the cabin temperature change model constructed in the step S101, the electric automobile driving mileage evaluation model after the electric automobile air conditioner is used is as follows:
wherein, P i MT Represents the motor output power of the ith electric automobile, m represents the servicing mass, g represents the gravity acceleration, C D Representing the coefficient of air resistance, A representing the frontal area, v i Represents the vehicle speed of the ith electric vehicle, eta T Representing the efficiency of the drive train, f representing the coefficient of rolling resistance, M i (t) shows the mileage of the ith electric vehicle,. Epsilon bat Represents the battery loss coefficient of the electric vehicle, B i The battery capacity of the ith electric vehicle,
indicating the current state of charge, η, of the ith electric vehicle battery dis Represents the discharge efficiency, eta, of the battery M Denotes the motor efficiency, P i as Indicating auxiliary service power, eta, of the ith electric vehicle as Representing the auxiliary service efficiency of the ith electric automobile;
step S103, according to the model constructed in the steps S101 and S102, the constraint conditions of the charge and discharge of the electric automobile are as follows:
step S1031, the battery of the electric automobile cannot be overcharged and overdischarged, and the constraint is as follows:
wherein, the first and the second end of the pipe are connected with each other,
the lowest electric quantity of the early warning of the discharge of the battery of the electric automobile is represented,
representing the highest charge of the battery of the electric automobile;
step S1032, the electric quantity of the electric vehicle which is out of the network after charging and discharging needs to meet the customer demand, and the constraint is as follows:
wherein, the first and the second end of the pipe are connected with each other,
represents the charging electric quantity during the period that the electric automobile is connected into the charging pile,
represents the discharge electric quantity during the period of the electric automobile accessing the charging pile,
indicating the expected charge capacity of the electric vehicle user,
initial electric quantity when representing electric automobile inserts and fills electric pile, eta cha Representing the charging efficiency of the electric automobile;
step S1033, the mileage of the path planning cannot exceed the endurance mileage, and the constraint is:
0≤x total (t)≤M i (t) (7)
wherein x is total (t) represents a total driving distance of the electric vehicle path plan;
step S104, the minimum power grid daily load fluctuation variance model is as follows:
wherein, P base (t) represents the base load in the grid,
indicating new electric vehicle incorporationThe electric vehicle load that was already in the grid before the grid,
representing the charging load of the electric automobile newly added into the power grid at the time t through temperature control and path planning and scheduling,
representing the discharging load of the newly-accessed electric automobile scheduled by temperature control and path planning,
representing the average load of the grid.
Description of the drawings:
FIG. 1 is a schematic diagram of an electric vehicle orderly charging and discharging dispatching system according to the present invention
FIG. 2 is an equivalent circuit diagram of the electric vehicle cabin temperature variation according to the present invention
FIG. 3 is a flow chart of the electric vehicle cluster ordered charging and discharging scheduling based on the differentiation control of the overall process of the vehicle cabin temperature
The specific implementation mode is as follows:
the invention is described in further detail below with reference to the accompanying drawings:
as shown in fig. 1, the electric vehicle cluster ordered charging and discharging scheduling system based on the differentiation control of the whole vehicle cabin temperature process comprises a scheduling platform and three subsystems:
the cloud monitoring and scheduling platform: receiving and displaying the running data and states of the electric automobile, the charging station and the power distribution network in real time, obtaining an electric automobile temperature differential regulation and control and ordered charging and discharging strategy through data processing, and issuing the electric automobile temperature differential regulation and control and ordered charging and discharging strategy to corresponding subsystems; monitoring the condition that the electric automobile participates in power grid dispatching, monitoring the distribution thermodynamic diagram of the electric automobile, and monitoring abnormity and warning in electric automobile dispatching;
vehicle data acquisition control system: acquiring and processing data of temperature change and mileage change in the cabin in the whole process of the participation and scheduling of the electric automobile, and uploading the processed driving data to a cloud monitoring and scheduling platform;
charging station management system: acquiring and processing the use condition of a charging pile of a charging station, the charging and discharging state of an electric automobile of the charging pile, the time of the electric automobile accessing the charging pile, the time of the electric automobile leaving the charging pile in anticipation and the expected electric quantity of a battery of the electric automobile, uploading the processed data to a cloud monitoring and scheduling platform, and receiving an ordered charging and discharging instruction issued by the cloud monitoring and scheduling platform;
distribution network data acquisition system: the method comprises the steps of collecting real-time load of a power grid, predicting a power grid load curve by combining historical load data of the power grid, and uploading the processed power grid load data to a cloud monitoring and dispatching platform.
Furthermore, the vehicle-mounted data acquisition control system comprises a vehicle cabin internal and external temperature detection module, an infrared detection module, a driving data acquisition module, a data processing and control module and a communication module;
the vehicle cabin internal and external temperature detection module is used for detecting the current vehicle cabin internal and external temperatures of the electric vehicle in a period and providing a reference basis for subsequent differential regulation and control of the vehicle-mounted air conditioner temperature by combining the human body comfort temperature;
the infrared detection module detects the number of people in the current electric automobile and provides a reference basis for the subsequent calculation of the heat dissipation capacity of the human body;
the driving data acquisition module acquires the driving destination of the electric automobile, the residual electric quantity of the power battery, the running state of an air conditioner in the automobile, the position of the automobile and the speed of the automobile and provides data for the subsequent calculation of the ordered charging and discharging planning of the electric automobile;
the data processing and control module is used for calculating the remaining endurance mileage of the electric automobile by considering the current average power consumption of the whole automobile and providing data for the subsequent calculation of the ordered charging and discharging planning of the electric automobile; receiving an upper layer control instruction, executing differential adjustment of set temperature of the vehicle-mounted air conditioner, and providing planning information of an ordered charging and discharging path of the electric vehicle;
the communication module uploads the electric vehicle driving data to the cloud monitoring and scheduling platform by adopting a 4G/5G network, and receives the ordered charging and discharging temperature regulation and control and path planning instructions issued by the cloud monitoring and scheduling platform.
With reference to fig. 3, the electric vehicle cluster ordered charging and discharging scheduling method based on the differentiation control of the vehicle cabin temperature overall process of the invention comprises the following steps:
step S101, distributing a unique identification code for each electric vehicle participating in dispatching, so that the acquired electric vehicle related data can be issued to each vehicle accurately in an active traceable and ordered charging and discharging dispatching instruction;
step S102, the electric automobile data acquisition system detects whether the electric automobile is connected with the charging pile, if so, the electric automobile meeting the time constraint formula (18) goes to step S107; if not, go to step S103;
step S103, in order to realize the whole-process differential control of the temperature of the electric automobile, wherein the whole process refers to the process that electric automobile users participate in the differential temperature control and path planning of the ordered charging and discharging scheduling of the power grid, the differentiation is actually the temperature control difference of each electric automobile caused by the difference of the users in the cold and heat requirements, the difference of the temperature change in the cabin and the difference of the driving speed of the electric automobile, a vehicle-mounted electric automobile data acquisition system acquires the driving destination, the residual electric quantity of a power battery, the health state of the power battery, the running state and running parameters of an air conditioner, the temperature inside and outside the cabin, the position of the vehicle, the number of people in the vehicle and the speed of the vehicle of the electric automobile, and transmits the data to a cloud monitoring scheduling platform;
step S104, the cloud monitoring and scheduling platform receives relevant data from the electric automobile and informs a preferential policy to an electric automobile user, wherein the preferential policy specifies that the electric automobile participates in ordered charging and discharging: the charging electricity price discount rate is increased along with the increase of the driving distance, the destination deviation mileage and the total driving time after the user participates in temperature control, namely the electricity price after participating in differentiated temperature control scheduling and participating in path planning scheduling of driving to the target charging pile enjoys discount preferential policies on the basis of the original power grid electricity price, and the electricity price discount rate is as follows:
wherein x is offset An offset of a target charging station representing a user path plan relative to an initial destination;
step S1041, with reference to fig. 2, the data processing and controlling module of the vehicle-mounted data acquisition controlling system establishes a temperature variation model of the electric vehicle, which is:
wherein, T i V (t) represents the ith electric vehicle cabin temperature; t is am (t) represents the ambient temperature and,
the air-conditioning cooling capacity of the ith electric automobile is expressed;
representing the human body heat dissipation of q individuals in the ith electric automobile;
representing the heat dissipation capacity of other equipment in the ith electric automobile cabin; p i ac (t) represents the air-conditioning refrigeration energy efficiency ratio, COP represents the equivalent heat capacity, which is the product of the volume of the cabin and the air specific heat capacity, and R represents the equivalent heat resistance and is related to the heat conductivity coefficient of the cabin;
the difference of user on cold and hot demand leads to the difference of electric automobile cabin initial temperature, and the difference of the current number of people in electric automobile cabin leads to the difference in the cabin temperature variation process, and the electric automobile speed of travel difference can influence power battery's consumption difference, makes there is the difference in the control of cloud control dispatch center to cabin temperature. Therefore, the three influencing factors can cause the difference of the cloud monitoring and dispatching platform on the temperature control of the electric automobile cabin.
Step S1042, in order to predict the change of the driving range of the electric vehicle caused by the differential temperature control and predict the charging requirement of the electric vehicle, the data processing and control module of the vehicle-mounted data acquisition control system establishes a driving range change model caused by the temperature change of the electric vehicle as follows:
wherein, P i MT Represents the motor output power of the ith electric automobile, m represents the servicing mass, g represents the gravity acceleration, C D Representing the coefficient of air resistance, A representing the frontal area, v i Represents the vehicle speed of the ith electric vehicle, eta T Representing the efficiency of the drive train, f representing the coefficient of rolling resistance, M i (t) represents the mileage of the ith electric vehicle,. Epsilon bat Represents the battery loss coefficient of the electric vehicle, B i The battery capacity of the ith electric vehicle,
indicating the current state of charge, η, of the ith electric vehicle battery dis Represents the discharge efficiency, η, of the battery M Denotes the motor efficiency, P i as Indicating auxiliary service power, eta, of the ith electric vehicle as Representing the auxiliary service efficiency of the ith electric automobile;
step S1043, the constraint conditions of the electric vehicle charging and discharging are:
in step S10431, the battery of the electric vehicle cannot be overcharged or overdischarged, and the constraint is:
wherein the content of the first and second substances,
the lowest electric quantity of the early warning of the discharge of the battery of the electric automobile is represented,
representing the highest charge of the battery of the electric automobile;
step S10432, the electric quantity of the electric vehicle which is out of the network after charging and discharging needs to meet the customer demand, and the constraint is as follows:
wherein, W i cha (t) represents the amount of charge during the period when the electric vehicle is connected to the charging pile, W i dis (t) represents the discharge capacity during the period of the electric vehicle accessing the charging pile,
indicating the expected charge capacity of the electric vehicle user,
represents the initial electric quantity when the electric automobile is connected into the charging pile, eta cha Representing the charging efficiency of the electric automobile;
step S10433, the mileage of the path planning cannot exceed the endurance mileage, and the constraint is:
wherein x is total And (t) represents the total driving distance of the electric vehicle path planning.
Step S105, detecting whether the electric vehicle user is willing to participate in temperature regulation and control according to a preferential policy, if so, calculating a related result according to a model established by a data processing module of the vehicle-mounted electric vehicle data acquisition system in the step S104, wherein the user is supposed to participate in temperature control and is willing to participate in path planning and scheduling of ordered charging and discharging; if the user does not want to do, the continuation of journey mileage predicted by the vehicle-mounted system is directly adopted for subsequent calculation;
step S106, detecting whether the electric automobile user is willing to participate in ordered charging and discharging scheduling, if so, planning the running track of the electric automobile, and going to step S108; if the user does not want to charge the electric automobile, the electric automobile is charged disorderly;
step S107, detecting whether the electric automobile connected with the charging pile meets the time constraint formula (17)
Wherein, t off Time, t, when the electric vehicle is connected to the charging pile on Indicating the expected leaving time of the charging post set by the user of the electric vehicle,
represents the maximum charging power;
if so, go to 108; if not, the electric automobile is charged disorderly;
step S108, the cloud monitoring and scheduling platform receives and processes relevant data of the electric automobile, the charging pile and the power distribution network, combines a daily load prediction curve, takes the minimum daily load fluctuation variance of the power distribution network as a target function, and carries out ordered charging and discharging scheduling planning on the electric automobile, wherein the model is as follows:
wherein, P base (t) represents the base load in the grid,
indicating the electric vehicle load already in the grid before the new electric vehicle is incorporated into the grid,
new addition of temperature control and path planning scheduling at t momentThe charging load of the electric vehicle entering the power grid,
represents the electric vehicle discharging load of new network entry scheduled by temperature control and path planning,
representing the average load of the grid;
and step S109, the cloud monitoring and dispatching platform respectively issues the obtained ordered charging and discharging decision and command to the electric automobile and the charging station, so that the electric automobile participating in dispatching performs temperature control and driving according to a plan, and the charging station performs ordered charging and discharging operations on the on-grid electric automobile and the electric automobile to be networked according to the plan.
While the invention has been described in further detail with reference to specific preferred embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (5)
1. Electric automobile cluster is charging and discharging dispatch system in order based on cabin temperature overall process differentiation control, its characterized in that, this system contains a dispatch platform and three subsystem:
the cloud monitoring and scheduling platform: the method comprises the steps of receiving and displaying the running data and the states of the electric automobile, a charging station and a power distribution network in real time, obtaining the temperature differential regulation and control and the ordered charging and discharging strategy of the electric automobile through data processing and analysis, and issuing the strategy to corresponding subsystems; monitoring the condition that the electric automobile participates in power grid dispatching, monitoring the distribution thermodynamic diagram of the electric automobile, and monitoring abnormity and warning in electric automobile dispatching;
vehicle data acquisition control system: acquiring and processing data of temperature change and mileage change in the cabin in the whole process of the participation and scheduling of the electric automobile, and uploading the processed driving data to a cloud monitoring and scheduling platform;
charging station management system: acquiring and processing the use condition of a charging pile of the charging station, the charging and discharging state of an electric automobile of the charging pile, the time of the electric automobile to be connected into the charging pile, the time of the electric automobile to leave the charging pile in anticipation and the expected electric quantity of the battery of the electric automobile, uploading the processed data to a cloud monitoring and scheduling platform, and receiving an ordered charging and discharging instruction issued by the cloud monitoring and scheduling platform;
distribution network data acquisition system: collecting real-time load of a power grid, predicting a power grid load curve by combining historical load data of the power grid, and uploading the processed power grid load data to a cloud monitoring and scheduling platform;
the cloud monitoring and scheduling platform comprises an electric automobile ordered charging and discharging scheduling module, a communication module, a database and an interface display module;
the electric automobile ordered charging and discharging scheduling module comprises: planning orderly charging and discharging of the electric automobile according to the collected data of the electric automobile, the charging pile and the power distribution network so as to deal with load change of the power distribution network; the planning of the ordered charging and discharging of the electric automobile comprises the following steps: the method is characterized in that a vehicle-mounted air conditioner set temperature adjusting scheme is generated in a differentiated mode by combining the real-time load of the power grid, a power grid predicted load curve, the using state of the charging pile and the running state of the electric automobile and considering the remaining endurance mileage and the running destination of the electric automobile, so that the energy consumption of the whole automobile is reduced, the ordered charging and discharging planning range of the electric automobile is expanded, the running path from the electric automobile to the target charging pile is optimized, and the purpose of staggering the peak charging place and the charging time is achieved.
2. The electric vehicle cluster ordered charging and discharging scheduling system based on vehicle cabin temperature whole-process differentiation control of claim 1, characterized in that the vehicle-mounted data acquisition control system comprises a vehicle cabin inside and outside temperature detection module, an infrared detection module, a driving data acquisition module, a data processing and control module, and a communication module;
the temperature detection module inside and outside the vehicle cabin detects the temperature inside and outside the vehicle cabin of the electric vehicle by taking delta t as a period;
the infrared detection module is used for detecting the number of people in the electric automobile at present;
the driving data acquisition module is used for acquiring the driving destination of the electric automobile, the residual electric quantity of the power battery, the running state of an air conditioner in the automobile, the position of the automobile and the speed of the automobile;
the data processing and control module is used for calculating the remaining endurance mileage of the electric automobile by considering the current average power consumption of the whole automobile; receiving an upper layer control instruction, executing differential adjustment of set temperature of the vehicle-mounted air conditioner, and providing planning information of an ordered charging and discharging path of the electric vehicle;
the communication module uploads the electric vehicle driving data to the cloud monitoring and scheduling platform by adopting a 4G/5G network, and receives the ordered charging and discharging temperature regulation and control and path planning instructions issued by the cloud monitoring and scheduling platform.
3. An electric vehicle cluster ordered charging and discharging scheduling method based on vehicle cabin temperature whole-process differential control by using the system of any one of claims 1-2, characterized by comprising the following steps: the cloud monitoring and dispatching platform equivalently uses an electric automobile group as a mobile load and a distributed power supply, realizes control of whole automobile energy consumption and electric automobile endurance of the electric automobiles through differential regulation of the whole cabin temperature process, enlarges a control boundary and a power grid load bearing boundary of the electric automobile cluster ordered charging and discharging path planning, enables the electric automobiles to flexibly participate in peak clipping and valley filling of power grid load, and relieves peak-to-peak load adding of the power grid load;
according to the obtained data of the electric automobile, the charging station and the power distribution network, constructing an electric automobile cluster ordered charging and discharging scheduling model by taking minimum power grid daily load variance fluctuation as a scheduling target; the electric vehicle cluster ordered charging and discharging scheduling comprises planning of a driving path from an electric vehicle to a target charging station and differential control of the whole process of the vehicle cabin temperature considering the whole vehicle energy consumption of the electric vehicle;
forming a constraint condition of the electric automobile ordered charging and discharging scheduling model according to a preset electric automobile temperature controllable range, an electric automobile endurance mileage range and an electric automobile electric quantity state; according to the real-time load of the power grid and the predicted load curve of the power grid, in combination with the use state of the charging pile and the running state of the electric vehicle, the temperature in the cabin is differentially regulated within the temperature controllable range to reduce the energy consumption of the whole vehicle, and the running path from the electric vehicle to a target charging station is optimized within the predicted range of the endurance mileage;
solving an optimal solution of the ordered charging and discharging scheduling model of the electric automobile according to the constraint conditions of the ordered charging and discharging scheduling model of the electric automobile; and planning a running path of the electric automobile and differentially controlling the temperature in the cabin of the electric automobile according to the optimal solution under the constraint condition.
4. The electric vehicle cluster ordered charging and discharging scheduling method based on vehicle cabin temperature overall process differential control according to claim 3, wherein the electric vehicle cabin temperature control modeling step is as follows:
step S101, adjusting the temperature T set by the air conditioner of the ith electric automobile in a differentiation manner i S (T), maintaining the temperature T of the cabin of the electric vehicle i V (t) in a certain temperature range, controlling the power consumption of the air conditioner to reduce the average energy consumption of the electric automobile and increase the endurance mileage M of the electric automobile i (t), constructing a temperature change model of the monomer electric automobile cabin body:
wherein, T i V (t) represents the ith electric vehicle cabin temperature; t is am (t) represents the ambient temperature of the environment,
the air conditioning refrigeration capacity of the ith electric automobile is represented;
representing the human body heat dissipation of q individuals in the ith electric automobile;
representing the heat dissipation capacity of other equipment in the ith electric automobile cabin; p i ac (t) represents the refrigeration power of an air conditioner in the ith electric vehicle, COP represents the refrigeration energy efficiency ratio of the air conditioner, C represents the equivalent heat capacity which is the product of the volume of the cabin and the specific heat capacity of air, and R represents the equivalent heat resistance which is related to the heat conductivity coefficient of the cabin;
step S102, according to the cabin temperature change model constructed in the step S101, the electric automobile driving mileage evaluation model after the electric automobile air conditioner is used is as follows:
wherein, P i MT Indicating the i-th electric vehicle motor output power, M i (t) represents the mileage of the ith electric vehicle,. Epsilon bat Represents the battery loss coefficient of the electric vehicle, B i The battery capacity of the ith electric vehicle,
indicating the current state of charge, η, of the ith electric vehicle battery dis Represents the discharge efficiency, η, of the battery M Indicating motor efficiency, P i as Indicating auxiliary service power, eta, of the ith electric vehicle as Representing the auxiliary service efficiency of the ith electric automobile;
step S103, according to the models constructed in the steps S101 and S102, the constraint conditions of the charging and discharging of the electric automobile are as follows:
step S1031, the electric vehicle battery can not be over-charged and over-discharged, and the restraint is:
wherein, the first and the second end of the pipe are connected with each other,
the lowest electric quantity of the early warning of the discharge of the battery of the electric automobile is represented,
representing the highest charge of the battery of the electric automobile;
step S1032, the electric quantity of the electric vehicle which is out of the network after charging and discharging needs to meet the user requirement, and the constraint is as follows:
wherein, the first and the second end of the pipe are connected with each other,
represents the charging capacity of the electric automobile during the period of connecting the electric automobile into the charging pile,
represents the discharge electric quantity during the period of the electric automobile accessing the charging pile,
indicating the expected charge capacity of the electric vehicle user,
represents the initial electric quantity when the electric automobile is connected into the charging pile, eta cha Representing the charging efficiency of the electric automobile;
step S1033, the route planned by the route cannot exceed the cruising range, and the constraint is:
0≤x total (t)≤M i (t) (6) wherein x total And (t) represents the total driving distance of the electric vehicle path planning.
5. The electric vehicle cluster ordered charging and discharging scheduling method based on vehicle cabin temperature whole-process differential control as claimed in claim 3, wherein the minimum power grid daily load fluctuation variance model is:
wherein, P base (t) represents the base load in the grid,
indicating the electric vehicle load already in the grid before the new electric vehicle is incorporated into the grid,
representing the charging load of the electric automobile newly added into the power grid at the time t through temperature control and path planning and scheduling,
representing the discharging load of the newly-accessed electric automobile scheduled by temperature control and path planning,
representing the average load of the grid.
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