|تعداد مشاهده مقاله||3,525,521|
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MILP based Optimal Design of Hybrid Microgrid by Considering Statistical Wind Estimation and Demand Response
|Journal of Operation and Automation in Power Engineering|
|دوره 10، شماره 1، تیر 2022، صفحه 54-65 اصل مقاله (1.29 M)|
|نوع مقاله: Research paper|
|شناسه دیجیتال (DOI): 10.22098/joape.2022.8271.1572|
|E. Naderi؛ A. Dejamkhooy* ؛ S.J. SeyedShenava؛ H. Shayeghi|
|Department of Electrical Engineering, University of Mohaghegh Ardabili, Ardabil, Iran|
|Recently due to technical, economical, and environmental reasons, penetration of renewable energy resources has increased in the power systems. On the other hand, the utilization of these resources in remote areas and capable regions as isolated microgrids has several advantages. In this paper, a hybrid microgrid, which includes photovoltaic (PV)/wind/energy storage, is investigated. It has been located in Iran-Khalkhal. The purposes of this study are optimal energy management and sizing of the microgrid. Since the magnitude of the harvested renewable energy deals severely and complexly with season and climate issues, planning of the system based on their specific values is an oversimplification. Therefore, in addition to conventional constraints such as environmental and operational ones, estimation of the wind speed at the site is considered. The Monte Carlo method is employed to model and estimate wind behavior. Also, for regulating production and demand in the microgrid the Demand Response (DR) program is conducted to improve the contribution of the renewable energy resources. The planning is constructed as an optimization problem. It is formulated as a Mixed Integer Linear Programming (MILP). By solving it, the size and production magnitude of energy sources, as well as storage conditions, are determined. Finally, the proposed method is simulated by GAMS for all seasons of two scenarios. The results show desirable energy management and cost reduction in the studied grid.|
|Hybrid Microgrid؛ Wind speed model؛ Monte Carlo method؛ Mixed integer linear programming؛ Demand Response|
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