Global against divided optimization for the participation of an EV aggregator in the day-ahead electricity market. Part I: Theory

• Tipo: Artigo em Revista Científica Internacional
• Data: 2013

Autores

Ricardo Bessa (Autor) FEUP; Manuel Matos (Autor) FEUP

Revista

Título: Electric Power Systems Research

Vol. 95

Páginas: 309-318

ISSN: 0378-7796

Editora: Elsevier

Indexação

ISI Web of Knowledge - 67 Citações

ISI Web of Science

Scopus - 70 Citações

Classificação Científica

FOS: Ciências da engenharia e tecnologias > Engenharia electrotécnica, electrónica e informática

CORDIS: Ciências Tecnológicas > Engenharia > Engenharia electrotécnica

Outras Informações

ID Authenticus: P-002-0Z0

DOI: 10.1016/j.epsr.2012.08.007

Abstract (EN): 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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 10