A cost-efficient application of different battery energy storage technologies in microgrids considering load uncertainty

Abstract Dispersed application of Battery Energy Storages (BESs) can have many benefits in terms of voltage regulation and energy management in Active Distribution Networks (ADNs). The batteries are high-cost technologies, and they must be installed and managed optimally to benefit from their innumerable advantages. In addition, each battery technology has specific economic and technical attributes which can be appropriate or inappropriate in a particular condition and utilization. The purpose of this paper is that the optimal size and location of various battery technologies are specified in the distribution network to minimize total cost and maximize reliability index considering the uncertainty of load demand as well as the output power of the wind and solar. Also, multi-objective particle swarm optimization (MOPSO) algorithm is used to minimize two objective functions. Monte Carlo Simulation (MCS) is used to model the uncertainties of economic and technical characteristics of photovoltaic, wind power and load demand. The suggested planning scheme is tested on the modified IEEE 33-bus system. Finally, the different types of the battery technologies in one, five, ten, fifteen and twenty-year period are compared to present the optimum type.

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