期刊
ENERGY
卷 97, 期 -, 页码 444-459出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2015.12.122
关键词
BSOA (backtracking search optimization algorithm); PVT (photovoltaic thermal); Thermal PV model; Uncertainty; Tow PEM (point estimate method); Renewable MG
This paper aims to report the results of the research conducted to one thermal and electrical model for photovoltaic. Moreover, one probabilistic framework is introduced for considering all uncertainties in the optimal energy management of Micro-Grid problem. It should be noted that one typical Micro-Grid is being studied as a case, including different renewable energy sources, such as Photovoltaic, Micro Turbine, Wind Turbine, and one battery as a storage device for storing energy. The uncertainties of market price variation, photovoltaic and wind turbine output power change and load demand error are covered by the suggested probabilistic framework. The Micro-Grid problem is of nonlinear nature because of the stochastic behavior of the renewable energy sources such as Photovoltaic and Wind Turbine units, and hence there is need for a powerful tool to solve the problem. Therefore, in addition to the simulated thermal model and suggested probabilistic framework, a new algorithm is also introduced. The Backtracking Search Optimization Algorithm is described as a useful method to optimize the MG (micro grids) problem. This algorithm has the benefit of escaping from the local optima while converging fast, too. The proposed algorithm is also tested on the typical Micro-Grid. (C) 2016 Elsevier Ltd. All rights reserved.
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