Real-time Energy Management of Solar-integrated Electric Vehicles as-service-over Vehicular Fog

Ashfaq Ahmad, J. Khan
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Abstract

We investigate a real-time energy management technique for grid-connected photovoltaic (PV) integrated electric vehicles (EVs) as-service-over vehicular fog. Considering unknown dynamics of system inputs, we employ a virtual queue stability based Lyapunov optimization technique to minimize an average system cost through joint optimization of EV’s PV sufficiency, driving task scheduling delays, energy procurement cost, and EV battery (EVB) management. We obtain all solutions in closed forms which can be easily implemented in real-time EVs asservice-over vehicular fog. Results show that our propositions could achieve a daily EV’s PV sufficiency up to 44.25% and a monthly bill reduction up to 41.80%, while satisfying EV user’s delay and energy requirements.
汽车雾环境下太阳能集成电动汽车实时能源管理
我们研究了一种并网光伏(PV)集成电动汽车(ev)的实时能源管理技术。考虑系统输入的未知动态,我们采用基于虚拟队列稳定性的Lyapunov优化技术,通过联合优化电动汽车的光伏充分性、驾驶任务调度延迟、能源采购成本和电动汽车电池(EVB)管理来最小化平均系统成本。我们获得了所有封闭形式的解决方案,这些解决方案可以很容易地在实时电动汽车中实现。结果表明,在满足电动汽车用户延迟和能源需求的同时,我们的方案可以使电动汽车的日光伏充足率达到44.25%,月电费减少41.80%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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