A nighttime charging scheduling method for new energy pure electric buses

Abstract

The present invention proposes a nighttime charging scheduling method for new energy buses. The method is based on the remaining power, mileage, output power during charging, and charging scheduling schedule for the next day's operation based on the remaining power collected by the new energy bus and the on-board machine. According to the actual nighttime conditions of the bus station, the nighttime charging cost of the new energy bus to be charged is minimized and the nighttime charging workers are reasonably allocated and managed. At the same time, the charging scheduling can meet the operation needs of the new energy bus the next day, and the nighttime charging workers are more reasonably scheduled while ensuring the minimum charging time. The nighttime charging scheduling schedule is generated to facilitate the scheduling of charging scheduling personnel at the bus station. It saves manpower and meets the scheduling needs of the bus in the non-operation stage.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent management of charging of new energy pure electric buses, in particular to minimizing the nighttime charging cost of new energy buses to be charged and reasonably allocating, managing and scheduling charging workers at night. Background Art

[0002] As all sectors of society pay more and more attention to energy conservation and environmental protection, new energy represented by wind and light has gradually become popular in recent years, and its proportion in the total annual power generation has increased year by year, and new energy electric vehicles have been widely popularized. The proportion of new energy buses has continued to increase, and the trend of adopting pure electric buses has become stronger and stronger. However, due to the limited cruising range of pure electric buses, more vehicles need to be charged at night. In the past, the night charging method was to charge as soon as it arrived, which was disorderly charging. This would result in the failure to make good use of the advantage of lower electricity prices during the nighttime electricity price trough period, and would also result in the use of charging piles without reasonable maximum benefits. Insufficient charging at night makes it difficult to complete a day's operating tasks without charging when using pure electric buses in daily operations, and often cannot give full play to the operating capacity of pure electric buses. The existing technology is for dispatchers to judge whether it is necessary to charge the vehicle to complete the operation plan based on experience, while maintaining the principle of first-come-first-served charging. It cannot automatically calculate whether to charge and generate a scheduling plan based on the vehicle's next-day operation plan and the current remaining power of the vehicle, which is disorderly charging. Disorderly charging increases the workload of chargers at night and causes serious energy waste. It is impossible to guarantee the electricity required for the next day's operation plan, which affects the efficiency of bus operations.

[0003] The core of nighttime charging scheduling is to minimize charging costs and reasonably allocate and manage nighttime charging workers. Under dynamic power demand and fluctuating electricity prices, nighttime charging at valley prices has a great impact on the power cost of bus operation. Since electric bus charging stations consume a lot of electricity, it is crucial to reasonably arrange charging time to minimize power and labor costs.

[0004] Based on this, the problem arises of how to minimize the night charging cost of new energy buses to be charged and reasonably allocate and manage night chargers while meeting the operation needs of new energy buses the next day. Summary of the invention

[0005] In view of the deficiencies in the above-mentioned background technology, the present invention proposes a nighttime charging scheduling strategy for new energy buses, which solves the problems of disorderly charging, low efficiency, and unbalanced resource allocation in existing new energy bus charging stations.

[0006] The solution adopted by the present invention to solve its technical problems is: a night charging scheduling method for new energy pure electric buses, according to the vehicle-mounted machine recording the remaining SOC, the mileage of the day, and the power consumption of each bus, the buses entering the charging field are taken as evaluation objects in turn, and whether charging is needed is judged according to the remaining power of the vehicle, the charging scheduling next day scheduling plan and the mileage, and a night scheduling plan is generated. First, the basic data of the bus station, the output power of the charging pile and the battery capacity data of the bus are screened and preprocessed, that is, the null value abnormal data of the bus charging station are removed and filled, and then the charging time of each bus that needs to be charged at night at each charging gun is calculated, and the charging time matrix is ​​constructed. The scheduling plan is generated by the minimization charging scheduling logic algorithm; the algorithm model is deployed in the server, and a RESTFUL algorithm POST request service based on HTTP1.1 is constructed, and the charging scheduling algorithm is remotely called to obtain the night charging scheduling plan for the bus.

[0007] The steps include:

[0008] S1. The onboard device records the remaining SOC (state of charge, SOC), mileage of the day, and power consumption of each bus. The buses entering the charging station are evaluated one by one, and whether charging is needed is determined by the current remaining power, next day's schedule and mileage.

[0009] S2, parameter initialization, screening out buses that need to be charged, and calculating the time required for each bus to reach the expected SOC based on the output power of each charging gun per hour by formula (1), and constructing the charging matrix (2);

[0010]

[0011]

[0012] The input data is:

[0013] n is the total number of buses that need to be charged at night;

[0014] m is the total number of charging guns in bus stations;

[0015] k is the number of nighttime charging rounds k = int (n / m) + 1;

[0016] CAP i The battery capacity of the electric bus numbered i;

[0017] power j The power output by charging station j, j∈{1,2,…,m};

[0018] The total power required for the operation of the electric bus numbered i, i∈{1,2,…,n};

[0019] The first recorded remaining battery power percentage of the electric bus numbered j;

[0020] The constraints are:

[0021] minP j ≤Power j ≤maxP max Ensure that the charging power of each bus is within the allowed range of the charging pile.

[0022] S3. Input the SOC values ​​of the scheduled vehicles and sort them in descending order. The number of buses to be charged is n, and the number of available charging piles at the bus station is m. If n<=m, then the night charging is completed in one round. The minimum charging time of each vehicle at each charging pile is determined in turn, that is, to ensure that the bus that requires the maximum charging SOC value can be fully charged in the shortest time, and select the optimal charging pile output power; if n>m, execute S4.

[0023] S4, if n>m, and n%m! = 0, night charging is k rounds, the SOC values ​​of the scheduled vehicles are input, sorted in descending order, the first 0 to m vehicles are the first round of charging, and the minimum charging time of each vehicle at each charging pile is determined in turn, that is, to ensure that the bus with the maximum charging SOC value can be fully charged in the shortest time, select the optimal charging pile output power, and the second round of charging is the same as the first round of charging steps. Until the kth round, the number of vehicles to be dispatched is n%m, sorted in descending order, m*(k-1) to n buses are the kth round of charging, and the minimum charging time of each vehicle at each charging pile is determined in turn, that is, to ensure that the bus with the maximum charging SOC value can be fully charged in the shortest time, select the optimal charging pile output power, and output the charging schedule for each round of night charging in turn.

[0024] S5. If n>m, and the modulus of n and m is 0, there are k rounds of night charging. The SOC values ​​of the scheduled vehicles are input and sorted in descending order. The first 0 to m vehicles are the first round of charging. The minimum charging time of each vehicle at each charging pile is determined in turn, that is, to ensure that the bus that requires the maximum charging SOC value can be fully charged in the shortest time, and the optimal charging pile output power is selected. The second round of charging has the same steps as the first round until the end of the kth round, and the charging schedule for each round of night charging is output.

[0025] Furthermore, the server sets a time to collect the remaining SOC of the buses at the new energy bus station every day and the next day's operation schedule, and takes the remaining SOC of the buses at the charging station, the battery capacity, the output power of the charging pile and the next day's schedule as input, and the output is the night charging schedule. According to the actual situation of the bus station at night, the night charging cost of the new energy buses to be charged is minimized and the night chargers are reasonably allocated and managed, while meeting the operation needs of the new energy buses on the next day. Problems such as these are generated, ensuring the minimum charging time and making the night chargers' schedule more reasonable, and generating a night charging schedule to facilitate the dispatch of charging dispatchers at the bus station.

[0026] Beneficial effects of the present invention:

[0027] 1) The present invention integrates a new energy bus charging scheduling platform, including a bus on-board data acquisition module, a charging pile output power module, a charging scheduling next day operation scheduling plan module, a server night scheduling strategy module and an alarm module.

[0028] 2) Based on the remaining power, mileage, output power during charging, and the next day's operation schedule collected by the new energy bus and the on-board computer, the present invention ensures the minimization of the night charging cost of the new energy bus to be charged and the reasonable allocation and management of the night chargers according to the actual night conditions of the bus station, while meeting the operation needs of the new energy bus the next day. Problems such as these arise, ensure that the charging time is minimized, and at the same time, the night charger scheduling is more reasonable, and a night charging schedule is generated to facilitate the scheduling of charging dispatchers at the bus station. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 is a system block diagram of the present invention;

[0030] Figure 2 This is a nighttime charging scheduling flow chart of a new energy bus of the present invention;

[0031] Figure 3 This is the night charging schedule of the present invention. DETAILED DESCRIPTION

[0032] 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.

[0033] Embodiment 1: Provide a nighttime charging scheduling strategy for new energy pure electric buses. According to the vehicle-mounted machine recording the remaining SOC (state of charge, SOC), mileage of the day, and power consumption of each bus, the buses entering the charging field are evaluated in turn. It is determined whether charging is needed based on the remaining power of the vehicle, the next day's shift schedule, and the mileage, and a nighttime shift schedule is generated. It is applicable to the current nighttime charging scheduling plan of new energy bus charging stations in cities. Based on the remaining power, mileage, output power of the charging pile, and the next day's operation schedule collected by the new energy bus and the vehicle-mounted machine, a nighttime charging schedule is generated to facilitate the scheduling of charging dispatchers at bus stations.

[0034] Its system is Figure 1 As shown, it includes the vehicle-mounted machine module, the new energy bus charging dispatching platform, the bus scheduling algorithm generation schedule module, the charging pile power module, the server (night dispatching strategy) and the alarm module. Each module establishes a communication relationship with the new energy bus charging dispatching platform, and the new energy bus charging dispatching platform uploads data to the server and returns the dispatching schedule from the server.

[0035] The method comprises the following steps: Figure 2 shown.

[0036] S1. The onboard device records the remaining SOC, mileage of the day, and power consumption of each bus. The buses entering the charging station are evaluated one by one, and whether charging is needed is determined based on the current remaining power, next day's schedule, and mileage.

[0037] S2, parameter initialization, screening out buses that need to be charged, and calculating the time required for each bus to reach the expected SOC based on the output power of each charging gun per hour by formula (1), and constructing the charging matrix (2);

[0038]

[0039]

[0040] The input data is:

[0041] n is the total number of buses that need to be charged at night;

[0042] m is the total number of charging guns in bus stations;

[0043] k is the number of nighttime charging rounds k = int (n / m) + 1;

[0044] CAP i The battery capacity of the electric bus numbered i;

[0045] power jThe power output by charging station j, j∈{1,2,…,m};

[0046] The total power required for the operation of the electric bus numbered i, i∈{1,2,…,n};

[0047] The first recorded remaining battery power percentage of the electric bus numbered j;

[0048] The constraints are:

[0049] minP j ≤Power j ≤maxP max Ensure that the charging power of each bus is within the allowed range of the charging pile.

[0050] S3. Input the SOC values ​​of the scheduled vehicles and sort them in descending order. The number of buses to be charged is n, and the number of available charging piles at the bus station is m. If n<=m, then the night charging is completed in one round. The minimum charging time of each vehicle at each charging pile is determined in turn, that is, to ensure that the bus that requires the maximum charging SOC value can be fully charged in the shortest time, and select the optimal charging pile output power; if n>m, execute S4.

[0051] S4, if n>m, and the modulus of n and m is not 0, there are k rounds of night charging, and the SOC values ​​of the scheduled vehicles are input and sorted in descending order. The first 0 to m vehicles are the first round of charging, and the minimum charging time of each vehicle at each charging pile is determined in turn, that is, to ensure that the bus that needs the maximum charging amount SOC value can be fully charged in the shortest time, and the optimal charging pile output power is selected. The second round of charging is the same as the first round of charging steps. Until the kth round, the number of vehicles to be dispatched is n%m, and they are sorted in descending order. The buses from m*(k-1) to n are the kth round of charging, and the minimum charging time of each vehicle at each charging pile is determined in turn, that is, to ensure that the bus that needs the maximum charging amount SOC value can be fully charged in the shortest time, and the optimal charging pile output power is selected, and the charging schedule for each round of night charging is output in turn.

[0052] S5. If n>m, and the modulus of n and m is 0, there are k rounds of night charging. The SOC values ​​of the scheduled vehicles are input and sorted in descending order. The first 0 to m vehicles are the first round of charging. The minimum charging time of each vehicle at each charging pile is determined in turn, that is, to ensure that the bus that requires the maximum charging SOC value can be fully charged in the shortest time, and the optimal charging pile output power is selected. The second round of charging has the same steps as the first round until the end of the kth round, and the charging schedule for each round of night charging is output.

[0053] S6. The server sets a time to collect the remaining SOC of buses at new energy bus stations every day and the next day's operation schedule. The four pieces of information, namely the remaining SOC of buses at charging stations, battery capacity, output power of charging piles, and the next day's schedule, are used as input, and the output is a night charging schedule. According to the actual situation of the bus station at night, the night charging cost of new energy buses to be charged is minimized and the night chargers are reasonably allocated and managed. At the same time, the operation needs of new energy buses the next day are met, and other problems arise. The charging time is minimized, and the night chargers are more reasonably scheduled. A night charging schedule is generated to facilitate the dispatch of charging dispatchers at bus stations.

[0054] The design process of the present invention is as follows: First, the basic data of bus stations, charging pile output power and bus battery capacity data are screened and preprocessed, then the charging time of each bus that needs to be charged at night at each charging gun is calculated, and the charging time matrix is ​​constructed. The scheduling plan is generated by the scheduling logic algorithm. The algorithm model is deployed in the server, and the HTTP1.1 algorithm RESTFUL service is constructed using flask. The algorithm is called remotely, so that the bus night charging scheduling schedule can be obtained, such as Figure 3 .

[0055] 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 nighttime charging scheduling method for new energy pure electric buses, which records the remaining SOC, mileage of the day, and power consumption of each bus according to the vehicle-mounted machine, takes the buses entering the charging field as evaluation objects in turn, judges whether charging is needed according to the remaining power of the vehicle, the charging scheduling schedule for the next day, and the mileage, and generates a nighttime scheduling schedule, characterized in that: First, the basic data of bus stations, charging pile output power and bus battery capacity data, are screened and preprocessed, that is, the null value abnormal data of bus charging stations are removed and filled. Then, the charging time of each bus that needs to be charged at night at each charging gun is calculated, and the charging time matrix is ​​constructed. The scheduling plan is generated by the minimization charging scheduling logic algorithm. Deploy the algorithm model in the server, build a RESTFUL algorithm POST request service based on HTTP1.1, remotely call the charging scheduling algorithm, and obtain the bus night charging scheduling schedule; The steps include: S1. The onboard device records the remaining SOC, mileage of the day, and power consumption of each bus. The buses entering the charging station are evaluated one by one, and whether charging is needed is determined based on the current remaining power, next day's schedule, and mileage. S2, parameter initialization, screening out buses that need to be charged, and calculating the time required for each bus to reach the expected SOC based on the output power of each charging gun per hour by formula (1), and constructing the charging matrix (2); The input data is: n is the total number of buses that need to be charged at night; m is the total number of charging guns in bus stations; k is the number of nighttime charging rounds k = int (n / m) + 1; CAP i The battery capacity of the electric bus numbered i; power j The power output by charging station j, j∈{1,2,…,m}; The total power required for the operation of the electric bus numbered i, i∈{1,2,…,n}; The first recorded remaining battery power percentage of the electric bus numbered j; The constraints are: minP j ≤Power j ≤maxP max Ensure that the charging power of each bus is within the allowed range of the charging pile; S3, input the SOC values ​​of the scheduled vehicles and sort them in descending order. The number of buses to be charged is n, and the number of available charging piles at the bus station is m. If n<=m, then the night charging is completed in one round. The minimum charging time of each vehicle at each charging pile is determined in turn, that is, to ensure that the bus that requires the maximum charging SOC value can be fully charged in the shortest time, and select the optimal charging pile output power; if n>m, execute S4; S4, if n>m, and the modulus of n and m is not 0, and there are k rounds of night charging, the SOC values ​​of the input scheduled vehicles are sorted in descending order, and the first 0 to m vehicles are the first round of charging, and the minimum charging time of each vehicle at each charging pile is determined in turn, that is, to ensure that the bus that needs the maximum charging amount SOC value can be fully charged in the shortest time, and the optimal charging pile output power is selected. The second round of charging is the same as the first round of charging steps; until the kth round, the number of vehicles to be dispatched is n%m, and they are sorted in descending order, and m*(k-1) to n buses are the kth round of charging, and the minimum charging time of each vehicle at each charging pile is determined in turn, that is, to ensure that the bus that needs the maximum charging amount SOC value can be fully charged in the shortest time, and the optimal charging pile output power is selected, and the charging schedule for each round of night charging is output in turn; S5. If n>m, and the modulus of n and m is 0, there are k rounds of night charging. The SOC values ​​of the scheduled vehicles are input and sorted in descending order. The first 0 to m vehicles are the first round of charging. The minimum charging time of each vehicle at each charging pile is determined in turn, that is, to ensure that the bus that requires the maximum charging SOC value can be fully charged in the shortest time, and the optimal charging pile output power is selected. The second round of charging has the same steps as the first round until the end of the kth round, and the charging schedule for each round of night charging is output.

2. The nighttime charging scheduling method for new energy pure electric buses according to claim 1 is characterized in that: The server sets a time to collect the remaining SOC of buses at new energy bus stations every day and the next day's operation schedule. The four pieces of information, namely the remaining SOC of buses at charging stations, battery capacity, output power of charging piles and the next day's schedule, are used as input, and the output is a night charging schedule. According to the actual situation of the bus station at night, the night charging cost of new energy buses to be charged is minimized and the night chargers are reasonably allocated and managed. At the same time, the operation needs of new energy buses on the next day are met, and other problems arise. The charging time is minimized and the scheduling of night chargers is more reasonable. A night charging schedule is generated to facilitate the scheduling of charging dispatchers at bus stations.

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