Energy exchange between electric vehicle load and wind generating utilities

This paper proposes a novel approach to energy exchange

between electric vehicle (EV) load and wind generation utilities

participating in the day-ahead energy, balancing, and regulation

markets. An optimal bidding/offering strategy model is developed

to mitigate wind energy and EV imbalance threats, and optimize

EV charging profiles. A new strategy model is based on optimizing

decision making of a wind generating company (WGenCO)

in selecting the best option among the use of the balancing or regulation

services, the use of the energy storage system (ESS) and

the use of all of them to compensate wind power deviation. Energy

imbalance is discussed using conventional systems, ESS, and

EV-Wind coordination; results are compared and analyzed. Stochastic

intra-hour optimization is solved by mixed-integer linear

programming (MILP). Uncertainties associated with wind forecasting,

energy price, and behavior of EV owners based on their

driving patterns, are considered in the proposed stochastic method

and validated through several case studies.