Multi-Objective Multi-Period Optimal Operation of a Microgrid with Renewable Resources and Energy Storage

Abstract

This paper presents the multi-objective economic-emission dispatch problem of a microgrid (MG) system comprising various types of distributed generation. The proposed MG includes a fuel cell (FC), micro-gas turbine (MT), renewable energy resources—specifically, a wind turbine (WT) unit and a photovoltaic (PV) unit—and a battery energy storage system to enhance the MG's independence from the main utility grid. Several operational scenarios are analyzed based on the MG’s operating modes and the allowable generation levels from renewable sources. A teaching-learning-based optimization (TLBO) algorithm is employed to manage and optimize the operation of the distributed energy resources within the MG system. The multi-objective problem is addressed using a scalarized weighted metric approach, converting it into a single-objective function through compromise programming. Additionally, the multi-objective feasibility enhanced particle swarm optimization (MOFEPSO) algorithm is applied to further evaluate the effectiveness of the proposed optimization strategy. Selection of the best solution from the available Pareto-optima are done using the fuzzy satisfying method.

Keywords: Multi-objective optimization, Micro-grid, Energy management, Renewable energy, TLBO algorithm, MOFEPSO algorithm