TY - GEN
T1 - Modeling and optimization of electric vehicle charging load in a parking lot
AU - Chen, Lidan
AU - Chung, C. Y.
AU - Nie, Yongquan
AU - Yu, Rongrong
PY - 2013/6
Y1 - 2013/6
N2 - 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.
AB - 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.
KW - Electric vehicle load
KW - Optimal charging
KW - Particle swarm optimization
KW - Residential parking lot
UR - http://www.scopus.com/inward/record.url?scp=84903974210&partnerID=8YFLogxK
U2 - 10.1109/APPEEC.2013.6837301
DO - 10.1109/APPEEC.2013.6837301
M3 - Conference article published in proceeding or book
AN - SCOPUS:84903974210
SN - 9781479925223
T3 - Asia-Pacific Power and Energy Engineering Conference, APPEEC
BT - Proceedings of 2013 IEEE PES Asia-Pacific Power and Energy Engineering Conference, APPEEC 2013
PB - IEEE Computer Society
T2 - 2013 IEEE PES Asia-Pacific Power and Energy Engineering Conference, APPEEC 2013
Y2 - 8 December 2013 through 11 December 2013
ER -