Optimal Sizing of Energy Storage System for Operation of Wind Farms Considering Grid-Code Constraints

Bui Van-Hai, Xuan Quynh Nguyen, Akhtar Hussain and Wencong Su
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Bui Van-Hai: College of Engineering and Computer Science, University of Michigan-Dearborn, Dearborn, MI 48128, USA
Xuan Quynh Nguyen: College of Electrical and Information Engineering, Hunan University, Changsha 410082, China
Akhtar Hussain: Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB T6G 2G2, Canada
Wencong Su: College of Engineering and Computer Science, University of Michigan-Dearborn, Dearborn, MI 48128, USA

Energies, 2021, vol. 14, issue 17, 1-19

Abstract: Transmission system operators impose several grid-code constraints on large-scale wind farms to ensure power system stability. These constraints may reduce the net profit of the wind farm operators due to their inability to sell all the power. The violation of these constraints also results in an imposition of penalties on the wind farm operators. Therefore, an operation strategy is developed in this study for optimizing the operation of wind farms using an energy storage system. This facilitates wind farms in fulfilling all the grid-code constraints imposed by the transmission system operators. Specifically, the limited power constraint and the reserve power constraint are considered in this study. In addition, an optimization algorithm is developed for optimal sizing of the energy storage system, which reduces the total operation and investment costs of wind farms. All parameters affecting the size of the energy storage systems are also analyzed in detail. This analysis allows the wind farm operators to find out the optimal size of the energy storage systems considering grid-code constraints and the local information of wind farms.

Keywords: grid-code constraints; optimization; sizing of energy storage system; wind farm operation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
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