Journal
ELECTRIC POWER SYSTEMS RESEARCH
Volume 95, Issue -, Pages 309-318Publisher
ELSEVIER SCIENCE SA
DOI: 10.1016/j.epsr.2012.08.007
Keywords
Electric vehicles; Aggregator; Electricity market; Forecasting; Optimization; Operational management
Categories
Funding
- Fundacao para a Ciencia e Tecnologia (FCT) [SFRH/BD/33738/2009]
- European Union [241399]
- Fundação para a Ciência e a Tecnologia [SFRH/BD/33738/2009] Funding Source: FCT
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This paper addresses the bidding problem faced by an electric vehicles (EV) aggregation agent when participating in the day-ahead electrical energy market. Two alternative optimization approaches, global and divided, with the same goal (i.e. solve the same problem) are described. The difference is on how information about EV is modeled. The global approach uses aggregated values of the EV variables and the optimization model determines the bids exclusively based on total values. The divided approach uses individual information from each EV. In both approaches, statistical forecasting methods are formulated for the EV variables. After the day-ahead bidding, a second phase (named operational management) is required for mitigating the deviation between accepted bids and consumed electrical energy for EV charging. A sequential linear optimization problem is formulated for minimizing the deviation costs. This chain of algorithms provides to the EV aggregation agent a pathway to move to the smart-grid paradigm where load dispatch is a possibility. (C) 2012 Elsevier B.V. All rights reserved.
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