Management of electric vehicle charging to mitigate renewable generation intermittency and distribution network congestion

A decision support method is developed for an EV Load Aggregator or Energy Service Company that controls the battery charging for a fleet of EVs and a hierarchical decision making methodology is proposed for hedging in the day-ahead market and for playing the real-time market in a manner that yields regulation service revenues and allows for negotiated discounts on the use of distribution network payments.

Abstract

We consider the management of electric vehicle (EV) loads within a market-based electric power system control area. EV load management achieves cost savings in both (i) EV battery charging and (ii) the provision of additional regulation service required by wind farm expansion. More specifically, we develop a decision support method for an EV load aggregator or energy service company (ESCo) that controls the battery charging for a fleet of EVs. A hierarchical decision making methodology is proposed for hedging in the day-ahead market and for playing the real-time market in a manner that yields regulation service revenues and allows for negotiated discounts on the use of distribution network payments. Amongst several potential solutions that are available, we employ a rolling horizon look-ahead stochastic dynamic programming algorithm and report some typical computational experience.