Optimal trading of plug-in electric vehicle aggregation agents in a market environment for sustainability

• Type: Article in International Scientific Journal
• Date: 2016

Authors

Shafie khah, M (Author) Other; Heydarian Forushani, E (Author) Other; Golshan, MEH (Author) Other; Siano, P (Author) Other; Moghaddam, MP (Author) Other; Sheikh El Eslam, MK (Author) Other; Catalao, JPS (Author) FEUP

Journal

Title: Applied Energy

Vol. 162

Pages: 601-612

ISSN: 0306-2619

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 73 Citations

Scopus - 85 Citations

Other information

Authenticus ID: P-00G-T51

DOI: 10.1016/j.apenergy.2015.10.134

Abstract (EN): Ever since energy sustainability is an emergent concern, Plug-in Electric Vehicles (PEVs) significantly affect the approaching smart grids. Indeed, Demand Response (DR) brings a positive effect on the uncertainties of renewable energy sources, improving market efficiency and enhancing system reliability. This paper proposes a multi-stage stochastic model of a PEV aggregation agent to participate in day-ahead and intraday electricity markets. The stochastic model reflects several uncertainties such as the behaviour of PEV owners, electricity market prices, and activated quantity of reserve by the system operator. For this purpose, appropriate scenarios are utilized to realize the uncertain feature of the problem. Furthermore, in the proposed model, the PEV aggregation agents can update their bids/offers by taking part in the intraday market. To this end, these aggregation agents take part in Demand Response exchange (DRX), markets designed in the intraday session by employing DR resources. The numerical results show that DR provides a perfect opportunity for PEV aggregation agents to increase the profit. In addition, the results reveal that the PEV aggregation agent not only can increase its profit by participating in the DRX market, but also can become an important player in the mentioned market.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 12