An adaptive technique based modeling of optimal bidding strategies for competitive electricity market

In this paper, an adaptive technique based modeling of the optimal bidding strategies for competitive electricity market is proposed. Here, Artificial Bees Colony (ABC) is an optimization tool, which is used in two phases, the employee bee and the onlooker bee to optimize the bidding parameters. From the optimized parameters the exact solution is predicted by the Cuckoo Search (CS) algorithm, which is replaced by the scout bee phase of the ABC. In the CS algorithm prediction function is based on the levy flight search. It is used to discover the exact parameters from more complicated problems with the use of probability. This action makes the ABC as an adaptive technique. The required demand of every period is identified by the learning and testing algorithm Neural Network (NN). Then the proposed adaptive technique maximizes the profit levels and meets the demand at minimum pricing levels. Finally the proposed method is implemented in the MATLAB/simulink platform and effectiveness is analyzed by using the comparison of different techniques like ABC, PSO, ABC_PSO. The comparison results are demonstrating the superiority of the proposed approach and confirm its potential to solve the problem.