Multiobjective fireworks optimization framework for economic emission dispatch in microgrids

This paper proposes a new multi-objective optimization technique for economic emission dispatch in microgrids. This new technique is developed based of fireworks algorithm and is implemented in a microgrid with dispatachable microsources and non-dispatachable renewable energy resources such as solar generators. In this paper the multi-objective fireworks optimization is developed to find the most economic operating condition not only to minimize the fuel cost, but also to find the best environmentally friendly solution without violating any constraints. This method is a swarm intelligence algorithm which solves a multi-objective optimization problem much faster than other well-known algorithms with the help of a quality measure known as S-metric. The results of this new method are compared with the well-accepted methodology, non-dominated sorting genetic algorithm II (NSGA-II) as the benchmark.