Optimal Bidding of Market Participants in Restructured Power Market Adopting MBF Method

Presently, the generating firms throughout the world experience the critical problem of maximizing their own benefit while trading power to the market controller. Strategic bidding can be adopted for this purpose. For profit maximization, winning the auction in the hourly competitive power market to retail partially or entirely the total power demanded of a specific hour is of vital importance. A very recent optimization method acknowledged as Mouth Brooding Fish (MBF) has been suggested to get rid of the strategic bidding issue of the generating firms. The proposed optimization technique is adopted to find the bidding strategies in modern dynamic electric power market along with the power producing firms and bulk power consuming customers altering the MCP. The small power demanding market participants are in collective demand form. Normally, the hourly trading duration information of the rivals in the electric power market of the auction process with winning objective is unknown and an independent participant has to form his own strategy by predicting the other participant’s parameters out of the previous market history. The outcomes of the proposed MBF method evidence faster convergence and enhanced reliability to that obtained using TLBO and PSO methods. It is tested on an IEEE-30 Bus system incorporating 6 Power producing firms and 2 bulk power consumers. A new participant’s entry effect on the present market bidding behavior is also discussed in this work.