Abstract
This paper introduces a priority based Fuzzy Goal Programming (FGP) method for modelling and solving of microgrids using Genetic Algorithm (GA). The microgrid consider in this article consists of conventional and nonconventional power plants, such as wind and solar power plants. To incorporate the fluctuating outputs of solar and wind plants, the objectives of the problem are fuzzily described. In this article, optimal generation cost, total losses, and environmental ill-effect of power generation under the penetration of renewable energy resources (RES) are considered. In model formulation, the membership functions associated with fuzzy goals are transformed into membership goals and introducing under- and over-deviational variables to each of them. A GA scheme is used within the structure of FGP model to achieve the aspired levels of goals based on priorities in the decision environment. Then, a sensitivity analysis with variations of priority structure is performed and then the notion of Euclidean distance function is used to identify optimal power generation decision. To prove the usefulness of the intended method, three versions of a modified IEEE 30-bus and 6-generator system with renewable power generations are counted as the test systems. The model solution is also evaluated with the solutions obtained by using other approaches.
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