Optimal allocation of battery energy storage systems in distribution networks with high wind power penetration. Issue 8 (20th May 2016)

• Record Type: Journal Article
• Authors: Zhang, Yongxi; Dong, Zhao Yang; Luo, Fengji; Zheng, Yu; Meng, Ke; Wong, Kit Po
• Is Part Of: IET renewable power generation. Volume 10:Issue 8(2016)
• Page Start: 1105
• Page End: 1113
• Publication Date: 2016-05-20
• Subjects: battery storage plants -- wind power plants -- power distribution planning -- Monte Carlo methods -- stochastic programming -- evolutionary computation; battery energy storage systems -- BESS -- distribution networks -- wind power penetration -- renewable power generation intermittencies -- stochastic planning -- wind power utilisation -- wind power uncertainties -- Monte Carlo simulation -- stochastic optimisation model -- differential evolution algorithm -- radial distribution system; Renewable energy sources -- Periodicals; 333.79405
• DOI: 10.1049/iet-rpg.2015.0542
• Languages: English
• ISSNs: 1752-1416

Abstract

Abstract : In recent years, the battery energy storage system (BESS) has been considered as a promising solution for mitigating renewable power generation intermittencies. This study proposes a stochastic planning framework for the BESS in distribution networks with high wind power penetrations, aiming to maximise wind power utilisation while minimise the investment and operation costs. In the proposed framework, the uncertainties in wind power output and system load are modelled by the Monte–Carlo simulation, and a chance‐constrained stochastic optimisation model is formulated to optimally determine the location and capacity of BESS while ensuring wind power utilisation level. Then, the Monte–Carlo simulation embedded differential evolution algorithm is used to solve the problem. Simulation studies performed on a 15‐bus radial distribution system prove the efficiency of the proposed method.