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

• Type: Article in International Scientific Journal
• Date: 2013

Authors

Bessa, RJ (Author) Other; Manuel Matos (Author) FEUP

Journal

Title: Electric Power Systems Research

Vol. 95

Pages: 319-329

ISSN: 0378-7796

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 45 Citations

Scopus - 59 Citations

Other information

Authenticus ID: P-00R-205

DOI: 10.1016/j.epsr.2012.08.013

Abstract (EN): This paper presents numerical analysis of two alternative optimization approaches intended to support an EV aggregation agent in optimizing buying bids for the day-ahead electricity market. A study with market data from the Iberian electricity market is used for comparison and validation of the forecasting and optimization performance of the global and divided optimization approaches. The results show that evaluating the forecast quality separately from its impact in the optimization results is misleading, because a forecast with a low error might result in a higher cost than a forecast with higher error. Both bidding approaches were also compared with an inflexible EV load approach where the EV are not controlled by an aggregator and start charging when they plug-in. Results show that optimized bids allow a considerable cost reduction when compared to an inflexible load approach, and the computational performance of the algorithms satisfies the requirements for operational use by a future real EV aggregation agent.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 11