TY - GEN
T1 - Optimal control of PEVs for energy cost minimization and frequency regulation in the smart grid accounting for battery state-of-health degradation
AU - Cui, Tiansong
AU - Wang, Yanzhi
AU - Chen, Shuang
AU - Zhu, Qi
AU - Nazarian, Shahin
AU - Pedram, Massoud
N1 - Publisher Copyright:
© 2015 ACM.
PY - 2015/7/24
Y1 - 2015/7/24
N2 - Plug-in electric vehicles (PEVs) are considered the key to reducing the fossil fuel consumption and an important part of the smart grid. The plug-in electric vehicle-to-grid (V2G) technology in the smart grid infrastructure enables energy flow from PEV batteries to the power grid so that the grid stability is enhanced and the peak power demand is shaped. PEV owners will also benefit from V2G technology as they will be able to reduce energy cost through proper PEV charging and discharging scheduling. Moreover, power regulation service (RS) reserves have been playing an increasingly important role in modern power markets. It has been shown that by providing RS reserves, the power grid achieves a better match between energy supply and demand in presence of volatile and intermittent renewable energy generation. This paper addresses the problem of PEV charging under dynamic energy pricing, properly taking into account the degradation of battery state-of-health (SoH) during V2G operations as well as RS provisioning. An overall optimization throughout the whole parking period is proposed for the PEV and an adaptive control framework is presented to dynamically update the optimal charging/discharging decision at each time slot to mitigate the effect of RS tracking error. Experimental results show that the proposed optimal PEV charging algorithm minimizes the combination of electricity cost and battery aging cost in the RS provisioning power market.
AB - Plug-in electric vehicles (PEVs) are considered the key to reducing the fossil fuel consumption and an important part of the smart grid. The plug-in electric vehicle-to-grid (V2G) technology in the smart grid infrastructure enables energy flow from PEV batteries to the power grid so that the grid stability is enhanced and the peak power demand is shaped. PEV owners will also benefit from V2G technology as they will be able to reduce energy cost through proper PEV charging and discharging scheduling. Moreover, power regulation service (RS) reserves have been playing an increasingly important role in modern power markets. It has been shown that by providing RS reserves, the power grid achieves a better match between energy supply and demand in presence of volatile and intermittent renewable energy generation. This paper addresses the problem of PEV charging under dynamic energy pricing, properly taking into account the degradation of battery state-of-health (SoH) during V2G operations as well as RS provisioning. An overall optimization throughout the whole parking period is proposed for the PEV and an adaptive control framework is presented to dynamically update the optimal charging/discharging decision at each time slot to mitigate the effect of RS tracking error. Experimental results show that the proposed optimal PEV charging algorithm minimizes the combination of electricity cost and battery aging cost in the RS provisioning power market.
UR - http://www.scopus.com/inward/record.url?scp=84944111603&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84944111603&partnerID=8YFLogxK
U2 - 10.1145/2744769.2744882
DO - 10.1145/2744769.2744882
M3 - Conference contribution
AN - SCOPUS:84944111603
T3 - Proceedings - Design Automation Conference
BT - 2015 52nd ACM/EDAC/IEEE Design Automation Conference, DAC 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 52nd ACM/EDAC/IEEE Design Automation Conference, DAC 2015
Y2 - 8 June 2015 through 12 June 2015
ER -