Abstract:
Motivated by the potential of utilizing used electric vehicle (EV) batteries as the battery energy storage system (BESS) in EV charging stations, we study the joint sched...Show MoreMetadata
Abstract:
Motivated by the potential of utilizing used electric vehicle (EV) batteries as the battery energy storage system (BESS) in EV charging stations, we study the joint scheduling of EV charging and BESS operation in the presence of random renewable generation, EV arrivals, and electricity prices. We formulate cost-minimizing scheduling problem faced by an EV charging station operator as a dynamic program. We characterize an important priority rule for an optimal scheduling policy, and apply the established optimal policy characterization to improve the performance of existing heuristic policies. Numerical results demonstrate that optimal policy characterization established in this paper can significantly improve the performance of an least laxity first (LLF) policy. We also show by counter-intuitive examples that an optimal policy may charge the BESS and discharge an EV simultaneously, even when the EV's per-unit non-completion penalty is higher than the per-unit salvage value of the BESS and the highest possible electricity price.
Published in: 2018 IEEE Conference on Decision and Control (CDC)
Date of Conference: 17-19 December 2018
Date Added to IEEE Xplore: 20 January 2019
ISBN Information: