Optimal sizing of a wind-energy storage system considering battery life

Ye Liu, Xiaogang Wu, Jiuyu Du, Ziyou Song and Guoliang Wu

Renewable Energy, 2020, vol. 147, issue P1, 2470-2483

Abstract: A battery energy storage system (BESS) can smooth the fluctuation of output power for micro-grid by eliminating negative characteristics of uncertainty and intermittent for renewable energy for power generation, especially for wind power. By integrated with lithium battery storage system the utilization and overall energy efficiency can be improved. However, this target could be obtained only if the BESS is optimal matched. For this issue, the degradation of battery capacity has a significant impact on the operating costs of Wind-ESS system. The research focus on the optimal method for components sizing of BESS in Wind-ESS system with independent system operators. We present an operating cost model for the hybrid energy storage system considering capacity fading of lithium battery in the cycle life. For the optimal objective of component sizing, the global optimization method of dynamic programming (DP) is adopted by setting operating costs and capacity degradation as optimal objectives under the constrains of performance for lithium battery and requirement for grid operation. Based on the DP algorithm and capacity degradation of battery model, the optimal output of the wind power is obtained. The rule based method and genetic algorithm are also be used for simulation. The simulation results show that compared with other two optimal approaches, capacity degradation and operation cost of energy storage for wind power generation system are significantly reduced.

Keywords: Battery storage plants; Wind energy; Wind power generation; Dynamic programming(DP) (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (19)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:147:y:2020:i:p1:p:2470-2483

DOI: 10.1016/j.renene.2019.09.123

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