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Energy reserves and clearing in stochastic power markets: The case of plug-in-hybrid electric vehicle battery charging

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2 Author(s)
Justin M. Foster ; Division of Systems Engineering, Boston University College of Engineering, MA, USA ; Michael C. Caramanis

Building on our previous work in plug-in-hybrid electric vehicle (PHEV) charging, we study the potential benefits of demand participating in precisely quantified quality of service trades. Given the equivalency of demand and generation modulation in effecting power system cost and stability, we consider demand and generation as market participants with equal rights who engage in a mix of energy and reserve market transactions that clear simultaneously. Using existing market practice in the clearing of energy and reserves, we formulate the optimal bidding strategy of a load aggregator responsible for the battery charging of a fleet of PHEVs as the solution to a stochastic dynamic program (SDP). We show that optimal PHEV energy and regulation service bids lower PHEV charging costs, mitigate local distribution network congestion constraints, and increase system-wide supply of regulation service and thus contribute to the efficient expansion of intermittent clean generation. We propose and implement a tractable approximate SDP solution and report on computational experience using ERCOT and CAISO data.

Published in:

49th IEEE Conference on Decision and Control (CDC)

Date of Conference:

15-17 Dec. 2010