PROJECT TITLE :
Operational Strategy Optimization in an Optimal Sized Smart Microgrid
Recently, microgrids (MGs) have attracted considerable attention as a high-quality and reliable supply of electricity. During this paper, energy management in MGs is addressed in the sunshine of economic potency, environmental restrictions, and reliability improvement via: one) optimizing the kind and capability of distributed generation (DG) sources, moreover because the capacity of storage devices (SD); and a couple of) developing an operational strategy (OS) for energy management in MGs. A master-slave objective operate based mostly on net gift worth (as an economic indicator) is proposed. Such objective perform is solved using a hybrid optimization technique. This method includes two steps. In the first step, two-D slave object functions (SOFs), operating prices, and shopper outage price (as a reliability index) are minimized by quadratic programming and particle swarm optimization (PSO) algorithms, respectively. Then Pareto curve is drawn for SOF and fuzzy logic is employed to select the best SOF solution, OS, from Pareto curve. Within the second step, using the best OS from step one for any iteration, PSO algorithms used to resolve master objective function, and to see the optimum capacity and sort of DGs and SDs. The results show that the proposed framework will be thought-about as an efficient tool in coming up with and energy management of MGs.
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