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This paper presents an optimization procedure that enables the optimal dispatching of distributed generators and storage systems in a medium-voltage islanded microgrid. The network is assumed to be supplied by programmable (dispatchable) and nonprogrammable generators (i.e. nondispatchable, such as renewable energy sources-based units). The optimization goal is to minimize the overall microgrid operating cost and the pollutants emission of the programmable generators, assuming that all of the power made available by the renewable generators (photovoltaic and wind systems) is either directly injected into the network or stored in order to be subsequently delivered according to the proposed storage units' management strategy. The optimization is carried out by a niching evolutionary algorithm (NEA) that is able to find multiple optima and the variation of the objective function in their neighborhood. NEAs allow overcoming the performance of standard algorithms used for optimal power-flow calculations in power systems by avoiding falling into local optima. The optimization procedure is performed on a test microgrid and verified by computer simulations. The numerical results show that the solutions can always improve the microgrid performances irrespective of the network operating conditions in all of the considered cases.
Conti et al. (2012) studied this question.