作者: Yorie Nakahira , Niangjun Chen , Lijun Chen , Steven H Low , None
关键词: Least slack time scheduling 、 Current time 、 Algorithm 、 Energy (signal processing) 、 Online algorithm 、 Power (physics) 、 Constraint (information theory) 、 Mathematical optimization 、 Engineering
摘要: We formulate EV charging as a feasibility problem that meets all EVs' energy demands before departure under rate constraints and total power constraint. propose an online algorithm, the smoothed least-laxity-first (sLLF) decides on current rates based only information up to time. characterize performance of sLLF algorithm analytically numerically. Numerical experiments with real-world data show it has significantly higher generating feasible than several other common algorithms.