A charging control method for an orderly charging cloud platform based on multi-objective factors

Abstract

The present invention discloses a charging control method for an orderly charging cloud platform based on multi-objective factors. The present invention is based on an orderly charging cloud platform controlled by multi-objective factors, which solves the problem that the current orderly charging is limited to solving the problem that the charging power exceeds the power supply capacity, but cannot take into account other charging needs of users. It can pay attention to the guaranteed minimum charging power demand each time the user charges, and by taking the guaranteed minimum charging power demand as the highest charging priority, it is helpful to reduce the situation where electric vehicles completely lose power and cannot be used, and reduce the charging anxiety of electric vehicle owners. It can pay attention to the price and time-sensitive needs of different users, and through a control method that balances price and time, it can achieve the optimal charging cost or the optimal charging time, thereby improving the user experience.

Description

Technical Field

[0001] The present invention relates to the technical field of electric vehicle charging, and in particular to a charging control method of an orderly charging cloud platform based on multi-objective factors. Background Art

[0002] The rapid growth of electric vehicles has also brought about a rapid increase in electric vehicle charging load. Since electric vehicle charging load accounts for a large proportion of traditional loads, and charging load has great uncertainty in both time and space, and the growth of power cloud platform power supply capacity has always lagged behind the growth of peak loads under extreme conditions, the rapid growth of electric vehicle charging load has brought great challenges to power operation.

[0003] The long-term fixed-time peak-valley electricity price policy currently adopted by the power supply department to reduce the gap between peak and valley power load is likely to cause the charging load in a specific area to be concentrated in a specific area segment, causing pressure and operational risks on the power supply capacity of a specific area during a specific time period. To address this risk, various operation management cloud platforms generally adopt an orderly charging control strategy.

[0004] However, combined with the peak-valley electricity price policy, electric vehicle charging users have expected demands for charging costs, vehicle use time, vehicle mileage, etc., and hope to have their demands met at the same time. The current orderly charging strategy is generally limited to solving the problem of charging power exceeding the power supply capacity, and pays insufficient attention to other needs of electric vehicle charging users. Summary of the invention

[0005] The purpose of the present invention is to provide a charging control method for an orderly charging cloud platform based on multi-objective factors, which can simultaneously meet the matching of charging power and power supply capacity, and the user's personalized target requirements for charging costs, vehicle usage time, vehicle mileage, etc.

[0006] The present invention is implemented by the following technical solution: a charging control method of an orderly charging cloud platform based on multi-objective factors, comprising the following steps:

[0007] Obtain and calculate the charging power limit PL_H and charging price M_H of the charging station at different time periods in the future through manual setting or communication means;

[0008] When the user operates the charging pile to charge the electric vehicle or registers, the system requires the user to select and set the charging intention parameters that meet the user's personalized needs, including: the minimum charging power requirement ECmin, the maximum charging limit of the vehicle battery state of charge SOCmax, the maximum acceptable electricity price M_ECmin when charging within the minimum charging power requirement ECmin, the maximum acceptable electricity price M_ECels when charging after the minimum charging power requirement ECmin, the latest completion time period Hmax of this charging, the maximum charging power requirement ECmax of this time, or the maximum charging cost requirement MCmax of this time;

[0009] After the user confirms to start charging, the system performs orderly charging control based on the maximum charging power limit PL_H of the charging station, the charging price M_H, and the user's personalized charging intention parameters.

[0010] Furthermore, if the acceptable maximum electricity price M_ECmin set by the user is lower than the charging price of the charging station in all time periods before the latest completion time period Hmax of this charging within 24 hours, the user is reminded that the charging price set is invalid and needs to be reset, otherwise the operation cannot be confirmed to execute charging.

[0011] Furthermore, if all charging guns connected to the charged vehicle are charged at the maximum charging power, and the total charging power demand is not higher than the charging power limit PL_H for the period, then according to the rule that the charging price M_H for the period is not higher than the user's personalized parameter price M_ECmin, the charging vehicles that have not reached the minimum charging power demand ECmin are selected to be charged according to the electric vehicle charging demand power within the maximum power limit of the charging gun.

[0012] Furthermore, if all charging guns connected to the vehicle to be charged are charged at the maximum charging power, and the total charging power demand is not higher than the charging power limit PL_H for the period, then according to the rule that the charging price M_H for the period is not higher than the user's personalized parameter price M_ECels, the charging vehicle that has reached the minimum charging power demand ECmin is selected to charge according to the electric vehicle charging demand power within the maximum power limit of the charging gun.

[0013] Furthermore, if the total charging power demand of all charging vehicles that have not reached the minimum charging power demand ECmin exceeds the charging power limit PL_H of the period, the charging vehicles that have not reached the minimum charging power demand ECmin will be charged in the order of the user's charging request.

[0014] Furthermore, for vehicles that have not reached the minimum charging power demand ECmin and are being charged, if their total charging power demand is lower than the charging power limit PL_H for that period, then charging of the charging vehicles that have reached the minimum charging power demand ECmin will be started in the order of user charging requests.

[0015] Furthermore, when the charging time does not reach the latest completion time period Hmax of the user's personalized parameter, but the vehicle battery state of charge has reached the maximum charging limit SOCmax, or the charging power has reached the maximum charging power requirement ECmax, or the charging cost has reached the maximum charging cost requirement MCmax, stop charging immediately.

[0016] Furthermore, when the charging time has reached the latest completion time period Hmax of the user's personalized parameter, but the vehicle battery state of charge has not reached the maximum charging limit SOCmax, and the charging power has not reached the maximum charging power requirement ECmax, and the charging cost has not reached the maximum charging cost requirement MCmax, then charging will still be maintained until the maximum charging limit SOCmax, or the maximum charging power requirement ECmax, or the maximum charging cost requirement MCmax is reached.

[0017] Furthermore, in the charging power limit PL_H and charging price M_H of the charging station in different time periods, H represents a certain time period of a day, and the system generally sets the total number of time periods of a day to 48 or 96.

[0018] Furthermore, the charging power limit PL_H and charging price M_H of the system in different time periods in the future are known under normal operation. When the vehicle is connected, the status of all charging piles and connected charging vehicles in this charging station is also known. Therefore, after the user sets and completes the personalized charging parameters, the charging process according to the above is predictable and calculable. This calculation method is referred to as the "charging estimation algorithm" in the following description. The estimated result information of the user's charging this time can be calculated through the "charging estimation algorithm", including: the estimated time TCmin for charging with the minimum charging power requirement ECmin this time, the estimated cost MCmin for charging with the minimum charging power requirement ECmin this time, the estimated total power EC_Hmax of this charging before the latest completion time period Hmax, and the estimated total cost MC_Hmax of this charging before the latest completion time period Hmax.

[0019] Furthermore, when the user confirms the personalized parameters, the system immediately starts the "charging estimation algorithm". After the estimation calculation is completed, the estimated results TCmin, MCmin, EC_Hmax, and MC_Hmax of the user's charging this time are notified to the user through the user operation interface. If the user is not satisfied with the result, the personalized charging intention parameters can be readjusted to make corrections.

[0020] Furthermore, when the system is in a sudden "demand side response" state, if the future charging power limit PL_H and charging price M_H change, the system will reapply the "charging estimation algorithm" to calculate the estimated result information of the user's charging after the "demand side response" state, and notify the user of the latest M_H, TCmin, MCmin, EC_H, MC_H and their changes by means of user interface display, message notification or SMS notification.

[0021] Advantages of the present invention:

[0022] The present invention is based on an orderly charging cloud platform controlled by multiple objective factors, which solves the problem that the current orderly charging is limited to solving the problem that the charging power exceeds the power supply capacity, but cannot take into account other charging needs of users. It can pay attention to the guaranteed minimum charging power demand each time the user charges, and by taking the guaranteed minimum charging power demand as the highest charging priority, it is helpful to reduce the situation where electric vehicles completely lose power and cannot be used, and reduce the charging anxiety of electric vehicle owners. It can pay attention to the price and time-sensitive needs of different users, and through a control method that balances price and time, achieve the optimal charging cost or optimal charging time, thereby improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0024] Figure 1 This is a schematic diagram of the orderly charging cloud platform according to an embodiment of the present invention.

[0025] Figure 2 This is a flow chart of a charging control method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0026] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] An orderly charging cloud platform based on multi-objective factors (hereinafter referred to as the system) includes an intelligent terminal equipped with charging operation software, an intelligent charging pile, and a charging operation management business cloud platform.

[0028] Preferably, the intelligent terminal is a smart phone, a tablet computer, or a vehicle-mounted computer.

[0029] Preferably, the charging operation software is an APP or a mini program, which runs on a smart terminal. Through the operation interface of the smart terminal LCD screen, it can be connected to the charging operation management business platform in a communication manner to realize information interaction between the charging car owner and the remote charging operation management business platform.

[0030] Preferably, the smart charging pile can interact with the remote charging operation management business platform and accept communication control, and has a control interface and indicator light.

[0031] Preferably, the charging operation management business cloud platform can interact with smart terminals, smart charging piles, etc. through communication to achieve basic charging operation management functions.

[0032] Preferably, the charging operation management business cloud platform has the function of orderly charging of electric vehicles with multiple objective factors.

[0033] The present invention also provides a charging control method for an orderly charging cloud platform based on multi-objective factors, comprising the following steps:

[0034] Obtain and calculate the charging power limit PL_H and charging price M_H of the charging station at different time periods through manual setting or communication means;

[0035] When the user operates the charging pile to charge the electric vehicle or registers, the system requires the user to select the charging intention parameters that meet the user's personalized needs, including: the minimum charging power requirement ECmin, the maximum charging limit of the vehicle battery state of charge SOCmax, the maximum acceptable electricity price M_ECmin when charging within the minimum charging power requirement ECmin, the maximum acceptable electricity price M_ECels when charging after the minimum charging power requirement ECmin, the latest completion time period Hmax of this charging, the maximum charging power requirement ECmax of this time, or the maximum charging cost requirement MCmax of this time;

[0036] After the user confirms to start charging, the system performs orderly charging control based on the maximum charging power limit PL_H of the charging station, the charging price M_H, and the user's personalized charging intention parameters.

[0037] In this embodiment, if the acceptable maximum electricity price M_ECmin and the acceptable maximum electricity price M_ECels set by the user are both lower than the charging prices of all time periods of the charging station before the latest completion time period Hmax of this charging within 24 hours, the user is reminded that the set charging price is invalid and needs to be reset, otherwise the operation cannot be confirmed to execute charging.

[0038] In this embodiment, if all charging guns connected to the vehicle to be charged are charged at the maximum charging power, and the total charging power demand is not higher than the charging power limit PL_H for the period, then according to the rule that the charging price M_H for the period is not higher than the user's personalized parameter price M_ECmin, the charging vehicles that have not reached the minimum charging power demand ECmin are selected to start charging according to the electric vehicle charging demand power within the maximum power limit of the charging gun.

[0039] In this embodiment, if all charging guns connected to the vehicle to be charged are charged at the maximum charging power, and the total charging power demand is not higher than the charging power limit PL_H for the period, then according to the rule that the charging price M_H for the period is not higher than the user's personalized parameter price M_ECels, the charging vehicle that has reached the minimum charging power demand ECmin is selected to start charging according to the electric vehicle charging demand power within the maximum power limit of the charging gun.

[0040] In this embodiment, if the total charging power demand of all charging vehicles that have not reached the minimum charging power demand ECmin exceeds the charging power limit PL_H of the time period, the charging vehicles that have not reached the minimum charging power demand ECmin will be charged according to the order of user charging requests.

[0041] In this embodiment, if the total charging power demand of the vehicles that have not reached the minimum charging power demand ECmin and are being charged is lower than the charging power limit PL_H of the time period, then charging of the charging vehicles that have reached the minimum charging power demand ECmin will be started in the order of user charging requests.

[0042] In this embodiment, when the charging time does not reach the latest completion time period Hmax of the user's personalized parameter, but the vehicle battery state of charge has reached the maximum charging limit SOCmax, or the charging power has reached the maximum charging power requirement ECmax, or the charging cost has reached the maximum charging cost requirement MCmax, charging is stopped immediately.

[0043] In this embodiment, when the charging time has reached the latest completion time period Hmax of the user's personalized parameter, but the vehicle battery state of charge has not reached the maximum charging limit SOCmax, and the charging power has not reached the maximum charging power requirement ECmax, and the charging cost has not reached the maximum charging cost requirement MCmax, then charging will still be maintained until the maximum charging limit SOCmax, or the maximum charging power requirement ECmax, or the maximum charging cost requirement MCmax is reached.

[0044] In this embodiment, in the charging power limit PL_H and charging price M_H of the charging station in different time periods, H represents a certain time period of a day, and the system generally sets the total number of time periods of a day to 48 or 96.

[0045] In this embodiment, the charging power limit PL_H and charging price M_H of the system in different time periods in the future are known under normal operation. When the vehicle is connected, the status of all charging piles and connected charging vehicles in this charging station is also known. Therefore, after the user sets and completes the personalized charging parameters for this time, the charging process according to the above steps can be predicted and calculated. This calculation method is referred to as the "charging estimation algorithm" in the following description. The estimated result information of the user's charging this time can be calculated through the "charging estimation algorithm", including: the estimated time TCmin for charging with the minimum charging power requirement ECmin this time, the estimated cost MCmin for charging with the minimum charging power requirement ECmin this time, the estimated total power EC_Hmax of this charging before the latest completion time period Hmax, and the estimated total cost MC_Hmax of this charging before the latest completion time period Hmax.

[0046] In this embodiment, when the user confirms the personalized parameters, the system immediately starts the "charging estimation algorithm". After the estimation calculation is completed, the estimated results TCmin, MCmin, EC_Hmax, and MC_Hmax of the user's charging this time are notified to the user through the user operation interface. If the user is not satisfied with the result, the personalized charging intention parameters can be readjusted to make corrections.

[0047] The present invention is based on an orderly charging cloud platform controlled by multiple objective factors, which solves the problem that the current orderly charging is limited to solving the problem that the charging power exceeds the power supply capacity, but cannot take into account other charging needs of users. It can pay attention to the guaranteed minimum charging power demand each time the user charges, and by taking the guaranteed minimum charging power demand as the highest charging priority, it is helpful to reduce the situation where electric vehicles completely lose power and cannot be used, and reduce the charging anxiety of electric vehicle owners. It can pay attention to the price and time-sensitive needs of different users, and through a control method that balances price and time, achieve the optimal charging cost or optimal charging time, thereby improving the user experience.

[0048] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A charging control method for an orderly charging cloud platform based on multi-objective factors, characterized in that: The following steps are involved: Obtain and calculate the charging power limit PL_H and charging price M_H of the charging station at different time periods in the future through manual setting or communication means; When the user operates the charging pile to charge the electric vehicle or registers, the system requires the user to select the charging intention parameters that meet the user's personalized needs, including: the minimum charging power requirement ECmin, the maximum charging limit of the vehicle battery state of charge SOCmax, the maximum acceptable electricity price M_ECmin when charging within the minimum charging power requirement ECmin, the maximum acceptable electricity price M_ECels when charging after the minimum charging power requirement ECmin, the latest completion time period Hmax of this charging, the maximum charging power requirement ECmax of this time, or the maximum charging cost requirement MCmax of this time; After the user confirms to start charging, the system performs orderly charging control according to the charging power limit PL_H, charging price M_H of the charging station, and the user's personalized charging intention parameters; If the maximum acceptable electricity price M_ECmin for charging within the minimum charging power requirement ECmin set by the user is lower than the charging price of the charging station in all time periods before the latest completion time period Hmax of this charging within 24 hours, the user is reminded that the charging price set is invalid and needs to be reset, otherwise the operation cannot be confirmed to execute charging; If all charging guns connected to the vehicle to be charged are charged at the maximum charging power, and the total charging power demand is not higher than the charging power limit PL_H of the time period, then according to the rule that the charging price M_H of the time period is not higher than the highest acceptable electricity price M_ECmin when charging within the minimum charging power demand ECmin of the user's personalized parameter price, the charging vehicles that have not reached the minimum charging power demand ECmin are selected to start charging at the electric vehicle charging demand power within the maximum power limit of the charging gun; at the same time, according to the rule that the charging price M_H of the time period is not higher than the highest acceptable electricity price M_ECels when charging after the minimum charging power demand ECmin of the user's personalized parameter price, the charging vehicles that have reached the minimum charging power demand ECmin are selected to start charging at the electric vehicle charging demand power within the maximum power limit of the charging gun; For all charging vehicles that have not reached the minimum charging power demand ECmin, if their total charging power demand exceeds the charging power limit PL_H of the period, then charging of the charging vehicles that have not reached the minimum charging power demand ECmin will be started within the charging power limit PL_H according to the order of user charging requests; For vehicles that have not reached the minimum charging power demand ECmin and are being charged, if their total charging power demand is lower than the charging power limit PL_H of the period, then charging of the charging vehicles that have reached the minimum charging power demand ECmin will be started within the charging power limit PL_H according to the order of user charging requests; When the current charging time does not reach the latest completion time period Hmax of the current charging of the user personalized parameter, but the vehicle battery state of charge has reached the maximum charging limit SOCmax, or the current charging power has reached the maximum charging power requirement ECmax, or the current charging cost has reached the maximum charging cost requirement MCmax, stop charging immediately; when the current charging time has reached the latest completion time period Hmax of the current charging of the user personalized parameter, but the vehicle battery state of charge has not reached the maximum charging limit SOCmax, and the current charging power has not reached the maximum charging power requirement ECmax, and the current charging cost has not reached the maximum charging cost requirement MCmax, then keep charging until the maximum charging limit SOCmax, or the maximum charging power requirement ECmax, or the maximum charging cost requirement MCmax is reached; Under normal operating conditions, the charging power limit PL_H and charging price M_H of different time periods in the future are known. When the vehicle is connected, the status of all charging piles in this charging station and the connected charging vehicles are also known. The charging estimation algorithm can calculate the estimated result information of the user's charging this time, including: the estimated time TCmin for completing the charging with the minimum charging power requirement ECmin, the estimated cost MCmin for completing the charging with the minimum charging power requirement ECmin, the estimated total power EC_Hmax of this charging before the latest completion time period Hmax, and the estimated total cost MC_H of this charging before the latest completion time period Hmax max; when the user confirms the personalized parameters, the system immediately starts the charging estimation algorithm. After the estimation calculation is completed, the estimated result of the user's charging this time is given, including the estimated time TCmin for charging with the minimum charging power requirement ECmin, the estimated cost MCmin for charging with the minimum charging power requirement ECmin, the estimated total power EC_Hmax of this charging before the latest completion time period Hmax, and the estimated total cost MC_Hmax of this charging before the latest completion time period Hmax; the user is notified through the user operation interface. If the user is not satisfied with the result, the personalized charging intention parameters can be readjusted to make corrections.

2. According to claim 1, a charging control method for an orderly charging cloud platform based on multi-objective factors is characterized in that: In the charging power limit PL_H and charging price M_H of the charging station in different time periods, H represents a certain time period of a day, and the system generally sets the total number of time periods of a day to 48 or 96.

3. The charging control method of the orderly charging cloud platform based on multi-objective factors according to claim 1 is characterized in that: When the system is in a state of sudden demand-side response, if the future charging power limit PL_H and charging price M_H change, the system will re-apply the charging estimation algorithm to calculate the estimated result information of the user's charging after the demand-side response state, and notify the user of the latest charging price M_H, the estimated time TCmin for completing the charging with the minimum charging power requirement ECmin, the estimated cost MCmin for completing the charging with the minimum charging power requirement ECmin, the estimated total power EC_Hmax of this charging before the latest completion time period Hmax, and the estimated total cost MC_Hmax of this charging before the latest completion time period Hmax; and their changes, by means of user interface display, message notification or SMS notification.

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