Unlike conventional electrical networks, Microgrids are modern and flexible networks with specific parameters that can work in two modes, connected to general network and island mode. Distributed generations are one of the most important parts of Microgrids, so optimal placement of them requires special analysis because of the impact of placement in different electrical indexes, on the other hand on multi objective optimization a collection of answers will get that is called Pareto front and system operator couldn’t choose one of them. This paper presents a novel mixture of non-dominated sorting genetic algorithm and fuzzy method to minimize four objective functions such as cost, emission, power losses, and voltage deviation on a typical 34-bus test Microgrid to sizing six distributed generations and system operator can choose the best point between all of the points on Pareto front based on different conditions of operation of the system.
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