Energy storage based MG connected system for optimal management of energy: An ANFMDA technique

Abstract This paper proposes an efficient hybrid technique for the system modeling and the optimal energy management of the MG with low cost. The novelty of the proposed approach is the combination of the ANFIS and MDA named as ANFMDA that performs the decision making with the multi-objective problem. Moreover, the proposed method is the cost-effective power production of the microgrids and effective utilization of renewable energy sources without wasting the available energy. The strategy is worried about the mathematical optimization problems that include in excess of one objective function to be optimized at the same time. The MDA algorithm optimizes the MG configuration at minimum fuel cost to take care of the required load demand by using the inputs of MG like WT, PV array, MT, and ESS with corresponding cost functions. In the proposed approach, the ANFIS learning phase is employed to predict the load demand. Based on the predicted load demand the minimum annual fuel cost characteristics, the operation cost and also the replacement cost is decreased with all the subsequent points of the MDA. The performance of the proposed method is examined by comparison with the other techniques such as ABC algorithm, DA, and HOMER. The comparison results demonstrate the superiority of the proposed technique and confirm its potential to solve the problem.