Title :
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
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;
Conference_Titel :
Systems and Control (ICSC), 2013 3rd International Conference on
Conference_Location :
Algiers
Print_ISBN :
978-1-4799-0273-6
DOI :
10.1109/ICoSC.2013.6750952