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Hassan Bevrani

Hassan Bevrani

Academic rank: Professor
ORCID:
Education: PhD.
ScopusId: 55913436700
Faculty: Faculty of Engineering
Address: Dept. Of Electrical and Computer Eng, University of Kurdistan, Allameh Hamdi Blvd, Sanandaj PO Box 416, P. C: 66177-15175, Kurdistan, Iran
Phone: +98-87-33624001

Research

Title
Optimum storage sizing in a hybrid wind-battery energy system considering power fluctuation characteristics
Type
JournalPaper
Keywords
,Battery lifetime estimation ,Optimum battery sizing ,Power intermittency ,Wind power dispatching Wind-battery system
Year
2022
Journal Journal of Energy Storage
DOI
Researchers Hassan Bevrani ، Navid Rezaei ، Kolsoom Shahyari ، Mehrdad Gholami

Abstract

Power dispatching is one of the important requirements for wind power systems. Using energy storage systems, especially the battery energy storage system (BESS) is one of the more effective solutions for overcoming this problem. The required battery capacity depends on the fluctuation level of the output power, which is affected by several factors. In this paper, the object is to estimate the required battery capacity based on wind speed data and turbines position in the design phase of a wind farm. An analytical method is presented to estimate the short-term fluctuation of wind farm power considering wake effect, turbulence, and spatial smoothing. Then, a method for estimating the optimum battery capacity, based on the statistical characteristics of wind farm power including average value and standard deviation over a long-term period, is presented. In addition, a new model is presented to estimate the battery lifetime in the case of non-uniform charge/discharge cycles. The numerical results for a case study, over one-year wind speed data, are presented and the results show the effectiveness of the proposed approach in determining the optimum battery capacity.