TY - GEN
T1 - Probabilistic modeling of electric vehicle charging load for probabilistic load flow
AU - Kong, Seongbae
AU - Cho, Hyung Chul
AU - Lee, Jong Uk
AU - Joo, Sung Kwan
PY - 2012
Y1 - 2012
N2 - With an increasing concern about environmental pollution and rising price of fossil fuels, electric vehicles (EVs) are becoming an important alternative energy source in a transportation sector. A rapid deployment of EVs may have significant impacts on demand for electricity in a power system. Also, a large-scale deployment of EVs can introduce greater uncertainty in EV charging patterns and loads. This paper presents a Stratified Latin Hypercube Sampling (SLHS)-based probabilistic load flow (PLF) method incorporating electric vehicle charging load. In this paper, probabilistic EV charging load is modeled by using the EV penetration level, hourly traffic patterns, and EV charging scenarios. The Monte Carlo Simulation (MCS)-based PLF requires a significant amount of computation time to obtain accurate results. In this paper, SLHS technique is also applied to reduce the computation time of the PLF. A numerical example is presented to show the performance of the proposed method.
AB - With an increasing concern about environmental pollution and rising price of fossil fuels, electric vehicles (EVs) are becoming an important alternative energy source in a transportation sector. A rapid deployment of EVs may have significant impacts on demand for electricity in a power system. Also, a large-scale deployment of EVs can introduce greater uncertainty in EV charging patterns and loads. This paper presents a Stratified Latin Hypercube Sampling (SLHS)-based probabilistic load flow (PLF) method incorporating electric vehicle charging load. In this paper, probabilistic EV charging load is modeled by using the EV penetration level, hourly traffic patterns, and EV charging scenarios. The Monte Carlo Simulation (MCS)-based PLF requires a significant amount of computation time to obtain accurate results. In this paper, SLHS technique is also applied to reduce the computation time of the PLF. A numerical example is presented to show the performance of the proposed method.
UR - http://www.scopus.com/inward/record.url?scp=84874417761&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84874417761&partnerID=8YFLogxK
U2 - 10.1109/VPPC.2012.6422755
DO - 10.1109/VPPC.2012.6422755
M3 - Conference contribution
AN - SCOPUS:84874417761
SN - 9781467309530
T3 - 2012 IEEE Vehicle Power and Propulsion Conference, VPPC 2012
SP - 1010
EP - 1013
BT - 2012 IEEE Vehicle Power and Propulsion Conference, VPPC 2012
T2 - 2012 IEEE Vehicle Power and Propulsion Conference, VPPC 2012
Y2 - 9 October 2012 through 12 October 2012
ER -