Abstract
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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.