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Fuzzy multi-objective charging scheduling algorithm for electric vehicle based on load balance
ZHOU Meiling, CHEN Huaili
Journal of Computer Applications    2021, 41 (4): 1192-1198.   DOI: 10.11772/j.issn.1001-9081.2020071013
Abstract246)      PDF (1148KB)(429)       Save
Three-phase imbalance and load peak-valley difference in the distribution network were caused by single-phase charging of Electric Vehicle(EV) in residential area. Therefore, amulti-objective charging scheduling strategy for EV considering load balance was proposed. Based on the three-phase network, the total delay time and charge balance were used as the objective function, and constraints such as load peak-valley difference and three-phase imbalance were taken into account to establish the scheduling model of EV charging for static and online scheduling problems. The multi-objective solution was obtained by the improved Non-dominated Sorting Genetic Algorithm-Ⅱ(NSGA-Ⅱ), and the results were optimized by designing crossover operators, adaptively adjusting mutation probability and local optimization. The Pareto optimal frontier was obtained by setting a certain volume of external archives and crowding distance, and the fuzzy membership method was used to obtain the compromise optimal solution. The influence of number of simultaneously active charging points and three-phase imbalance value on the optimization results was analyzed through an example.The proposed strategy was compared with the disorderly charging strategy so that the validity of the proposed model and strategy was proved.
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Distribution path planning and charging strategy for pure electric vehicles with load constraint
LIU Yuliang, CHEN Huaili
Journal of Computer Applications    2020, 40 (10): 2831-2837.   DOI: 10.11772/j.issn.1001-9081.2020020157
Abstract304)      PDF (899KB)(408)       Save
Due to the limitation of driving mileage of pure electric vehicles, it is difficult to realize the long-distance transportation service of pure electric vehicles in a short time to meet the commercial requirements. However, due to the characteristics such as small distribution area, small quantity per batch and large batch number of urban logistics, the pure electric vehicles can be considered to complete the urban distribution tasks. In order to meet the requirements of multiple distribution tasks of the vehicle on the same day and consider the specific impact of vehicle load on real-time energy consumption, a distribution model considering the impact of vehicle load on real-time energy consumption was established to meet the customers' service time requirements in a timely manner. Taking city A as an example, an ant colony algorithm was designed to solve the model, so as to make the reasonable path planning and charging strategy arrangement for the distribution tasks of pure electric vehicles. Finally, the feasibility of pure electric vehicles in urban distribution and logistics in the future was analyzed by comparing to the operation with fuel vehicles.
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