Suppliers´ optimal biding strategies in day-ahead electricity market using competitive coevolutionary algorithms

Author

Tiguercha, A. ; Ladjici, A.A. ; Boudour, Mohamed

Author_Institution

Lab. of Ind. & Electr. Syst. (LSEI), Univ. of Sci. & Technol. Houari-Boumediene, Algiers, Algeria

fYear

2013

fDate

29-31 Oct. 2013

Firstpage

821

Lastpage

826

Abstract

The present paper investigates the use of competitive coevolutionary algorithm in order to find supplier´s optimal strategies in a Day-Ahead Electricity Market. Market game was expressed as an optimization problem based on the definition of Nash Equilibrium strategies where the game is playing by evolutionary agents, adapting theirs strategies to maximize the profits in a competitive environment. Day-ahead market where the IS0 uses a daily load profile submitted by each Service Load to perform a DC-OPF to determine Location Marginal Price and quantities bids from each supplier generators. Market agents´ (suppliers) take part in the Day-ahead transactions and act strategically in order to increase their profits from each hourly transaction.

Keywords

evolutionary computation; power markets; tendering; Nash equilibrium strategies; competitive coevolutionary algorithms; daily load profile; day ahead electricity market; evolutionary agents; location marginal price; market game; optimal biding strategies; optimization problem; Biological system modeling; Electricity supply industry; Games; ISO; Nash equilibrium; Sociology; Statistics;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems and Control (ICSC), 2013 3rd International Conference on

Conference_Location

Algiers

Print_ISBN

978-1-4799-0273-6

Type

conf

DOI

10.1109/ICoSC.2013.6750952

Filename

6750952