Evolutionary Neural Network based hybrid architecture for strategic bidding in electricity market

In various electricity markets around the world, an advanced aggressive framework has emerged, altering the way electric companies generate profits. In this paper, a hybrid architecture of metaheuristic and supervised learning is proposed to attain an optimal bidding strategy in the electricity market. The proposed architecture is the combination of the Salp Swarm Algorithm (SSA) with Neural Network (NN). The proposed architecture is tested on the IEEE-14 bus system, IEEE-30 bus system, and 75-bus Indian Practical System and compared with results of SSA and Opposition-based SSA (OSSA). The results confirm the superiority of the proposed architecture to solve the bidding problem in Electricity Market(EM).