Hassan Ghasemi - School of Electrical & Computer Engineering University of Tehran Tehran, Iran
Amjad Anvari-Moghaddam - School of Electrical & Computer Engineering University of Tehran Tehran, Iran

In recent years, renewable energies have become one of the most important sources of electrical energy. Their social and environmental benefits as well as economic issues result in further utilization of these energy resources. Moreover, it has become a challenging task for many modern utilities and energy management systems to derive an optimal operational plan for better utilization of renewable resources of energy regarding to different objectives. In this paper, a Modified Particle Swarm Optimization (MPSO) algorithm based on a fuzzy self-adaptive mechanism is utilized and implemented to solve the energy management problem in a typical micro-grid considering cost and emission as objectives. The algorithm is tested via several scenarios and its superior performance is compared to those from other multi-objective evolutionary algorithms such as Non-dominated Sorting Genetic Algorithm (NSGA II) and standard PSO

Energy management, micro-grid, particle swarm optimization, fuzzy self adaptive mechanism