Optimizing the Bidding Data for power industry with elastic demand using hybrid Water Cycle Moth Flame Optimization Algorithm

Abstract

Strategic Optimal Bidding of the data is a compulsory duty for Independent System Operator (ISO) which is the most complicated task that maximizes the profit of the supplier by handling bidding coefficient strategically. This paper endorses a strategy of optimal bidding coefficient data to improve the profit value by latest optimizing technique named hybrid Water Cycle Moth Flame Optimization Algorithm, which achieves a heuristic search thereby obtaining a global search of a stream using Levy flight movement. This method is applied and tested on an Indian-75 Bus system to test and investigate the new strategy whether receiving best solution of profit in comparison with other conventional techniques explained widely. On adding it evaluates the efficacy of the proposed method on the mentioned system through assessing total profit obtained, revenue, power generation, Market Clearing Price and cost of the individual GENCO. In order to show the Statistical Analysis the Box-plot is done to perform the visual data representation of the proposed and conventional methods.