A hybrid backtracking search algorithm for energy management in a microgrid

Abstract

Recently, due to the high penetration of distributed generators and storages, and the rapid growth of environmental concerns, energy optimisation plays a vital role in the operation of microgrids. In this paper, we propose a hybrid backtracking search matheuristic algorithm with a multiobjective indirect encoding (H-MOBSA) for the multiobjective mixed-integer nonlinear formulation of economic-emission dispatch in a grid-connected microgrid. In this approach, each partial discrete solution represented by the backtracking search algorithm is associated with a set of Pareto solutions of the related continuous subproblem where the fitness and diversity assignments are adapted to take into account all associated decoded solutions. The proposed algorithm aims to provide generation planning and the battery size that satisfy the trade-off between the total operating cost and pollutant emissions under equality and inequality constraints. To show the effectiveness of our approach, the proposed H-MOBSA is tested on typical MG and compared to other algorithms.