An effective methodology for profit and benefit maximization of market participants by trading of electric energy under competitive environment

×

Error message

User warning: The following theme is missing from the file system: journalijdr. For information about how to fix this, see the documentation page. in _drupal_trigger_error_with_delayed_logging() (line 1138 of /home2/journalijdr/public_html/includes/bootstrap.inc).

International Journal of Development Research

An effective methodology for profit and benefit maximization of market participants by trading of electric energy under competitive environment

Abstract: 

The electricity market has since 1980’s been gradually evolving from a monopoly market into a liberalized one for encouraging competition and improving efficiency. This introduces the opportunity for market participants (Power suppliers and consumers) to make more profit and benefits in the trading process of electrical energy. Therefore, it has become a core interest for the market participants to develop optimal bidding strategies to maximize the profit and benefits while participating in a competitive energy market. In this paper an optimal bidding strategy for market participants associated with risk management is devised as a multi objective stochastic optimization problem and solved by Firefly algorithm. (FA). The Firefly Algorithm is a Meta heuristic, nature inspired, optimization algorithm which is based on the social flashing behavior of fireflies and has been introduced for the bidding problem to obtain the global optimal solution. The impact of risk on the GENCOs is analyzed by introducing the factor λ. The proposed FA approach effectively maximizes the GENCOs profit and benefit of large consumers. A numerical example with six suppliers and two large consumers is considered to illustrate the essential features of the proposed method and test results are tabulated. The simulation result shows that these approaches effectively maximize the Profit and Benefit of Power suppliers and Large Consumers, converge much faster and more reliable when compared with existing methods.

Download PDF: