TY - GEN
T1 - Integration of plug-in electric vehicles in power systems using charging mode switching
AU - Li, Wen Tai
AU - Wen, Chao Kai
AU - Chen, Jung Chieh
AU - Teng, Jen Hao
AU - Ting, Pangan
PY - 2014
Y1 - 2014
N2 - In this paper, we develop an energy management algorithm for charging and discharging plug-in electric vehicles (PEVs). The algorithm considers both user convenience and electricity market factors. A performance metric, called 'user convenience', is formulated to measure the effective coordination of PEV charging. As a response to the electricity market, we address an economic dispatch problem by considering power flows, grid losses, voltage profile patterns, and vehicle-to-grid costs. Both of the concerned factors can be optimized by simply switching a PEV during charging, discharging, or in off-mode. The mode switch allows easy integrate of PEVs into power systems. The PEV state-decision problem can be efficiently solved by using convex optimization tools. Moreover, the problem can be solved in a decentralized manner, wherein each sub-aggregator can determine to charge, discharge, and turn to off-mode locally. Simulation results indicate that the proposed PEV energy management algorithm can obtain the same final state-of-charge of the batteries as those obtained by unconstraint cases. Meanwhile, the effect of PEV charging on the power system is significantly mitigated.
AB - In this paper, we develop an energy management algorithm for charging and discharging plug-in electric vehicles (PEVs). The algorithm considers both user convenience and electricity market factors. A performance metric, called 'user convenience', is formulated to measure the effective coordination of PEV charging. As a response to the electricity market, we address an economic dispatch problem by considering power flows, grid losses, voltage profile patterns, and vehicle-to-grid costs. Both of the concerned factors can be optimized by simply switching a PEV during charging, discharging, or in off-mode. The mode switch allows easy integrate of PEVs into power systems. The PEV state-decision problem can be efficiently solved by using convex optimization tools. Moreover, the problem can be solved in a decentralized manner, wherein each sub-aggregator can determine to charge, discharge, and turn to off-mode locally. Simulation results indicate that the proposed PEV energy management algorithm can obtain the same final state-of-charge of the batteries as those obtained by unconstraint cases. Meanwhile, the effect of PEV charging on the power system is significantly mitigated.
UR - https://www.scopus.com/pages/publications/84906715218
UR - https://www.scopus.com/pages/publications/84906715218#tab=citedBy
U2 - 10.1109/IPEC.2014.6869660
DO - 10.1109/IPEC.2014.6869660
M3 - Conference contribution
AN - SCOPUS:84906715218
SN - 9781479927050
T3 - 2014 International Power Electronics Conference, IPEC-Hiroshima - ECCE Asia 2014
SP - 677
EP - 681
BT - 2014 International Power Electronics Conference, IPEC-Hiroshima - ECCE Asia 2014
PB - IEEE Computer Society
T2 - 7th International Power Electronics Conference, IPEC-Hiroshima - ECCE Asia 2014
Y2 - 18 May 2014 through 21 May 2014
ER -