Optimal coordinated bidding of a profit-maximizing EV aggregator under uncertainty

Yelena Vardanyan, Frederik Banis, S. Ali Pourmousavi, Henrik Madsen

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An aggregator acts as a middleman between the small customers and the system operator (SO) offering a mutually beneficial agreement to trade electric power, where each market player (system operator, aggregator and electric vehicle (EV owner) has its own economic incentives. The EV aggregator aims to maximize its profit while trading energy and providing balancing power in wholesale markets. This paper develops a stochastic and dynamic mixed integer linear program (SD-MILP) for optimal coordinated bidding of an EV aggregator to maximize its profit from participating in competitive day-Ahead and real-Time markets. Under uncertain day-Ahead and real-Time market prices as well as fleet mobility, the proposed SD-MILP model finds optimal EV charging/discharging plans for every EV. The degradation costs of EV batteries are modeled. To reflect the continuous clearing nature of the real-Time market, rolling planning is applied which allows re-forecasting and re-dispatching. The proposed SD-MILP is used to derive a bidding curve of an aggregator managing 1000 EVs.
Original languageEnglish
Title of host publicationProceedings of the 2018 IEEE International Energy Conference (ENERGYCON)
Number of pages6
Publication date2018
ISBN (Print)978-1-5386-1283-5
ISBN (Electronic)978-1-5386-3669-5
Publication statusPublished - 2018
Event2018 IEEE International Energy Conference - Limassol, Cyprus
Duration: 3 Jun 20187 Jun 2018


Conference2018 IEEE International Energy Conference


  • Coordinated bidding
  • Two-settlement market
  • EV aggregator
  • Stochastic programming

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