Title :
Modeling and optimization of electric vehicle charging load in a parking lot
Author :
Lidan Chen ; Chung, C.Y. ; Yongquan Nie ; Rongrong Yu
Author_Institution :
Dept. of Electr. Eng., Hong Kong Polytech. Univ., Hong Kong, China
Abstract :
Electric vehicle (EV) offers one of the most promising approaches towards reducing urban pollution. With EVs´ integration into power grid for charging batteries, they can potentially have a significant impact on the distribution grid. This paper discusses the modeling of a charging station for analysis of charging load demand in a residential parking lot with the assumption that EV arrivals follow Poisson distribution. Then, a simulation framework to generate the charging load profiles is proposed. Furthermore, Particle swarm optimization (PSO) algorithm is employed to obtain the stochastic feature parameter of charging start time, and an optimal charging strategy based on the model is developed to reduce the power fluctuation level caused by EV charging. Compared with results of the uncontrolled case, simulation results indicate that the proposed charging start time optimal algorithm not only slightly meets EV owners´ charging demand but also significantly reduces peak and filling valley, mitigating the impact of EV charging on the distribution network.
Keywords :
distribution networks; electric vehicles; particle swarm optimisation; power grids; secondary cells; stochastic processes; EV charging; PSO algorithm; Poisson distribution; charging batteries; charging load demand; charging station; distribution grid; distribution network; electric vehicle charging load; filling valley; optimal charging strategy; particle swarm optimization; power fluctuation level reduction; power grid; residential parking lot; stochastic feature parameter; urban pollution reduction; Batteries; Educational institutions; Load modeling; Power system stability; Stochastic processes; Vehicles; Electric vehicle load; Optimal charging; Particle swarm optimization; Residential parking lot;
Conference_Titel :
Power and Energy Engineering Conference (APPEEC), 2013 IEEE PES Asia-Pacific
Conference_Location :
Kowloon
DOI :
10.1109/APPEEC.2013.6837301