Investment optimization of grid-scale energy storage for supporting different wind power utilization levels

• DOI: 10.1007/s40565-019-0530-9
• Publication Date: 2019-05-23T16:50:32Z
• Authors: Yunhao Li; Jianxue Wang; Chenjia Gu; Jinshan Liu; Zhengxi Li
• Keywords: TK1001-1841; Energy storage; 0211 other engineering and technologies; TJ807-830; 02 engineering and technology; 7. Clean energy; Renewable energy sources; Power system planning; Production of electric energy or power. Powerplants. Central stations; Chance constraint; Wind power; Capacity investment

With the large-scale integration of renewable generation, energy storage system (ESS) is increasingly regarded as a promising technology to provide sufficient flexibility for safe and stable operation power systems under uncertainty. This paper focuses on grid-scale ESS planning problems in transmission-constrained considering uncertainties wind load. A scenario-based chance-constrained approach proposed address joint multiple technologies ESS. Specifically, chance constraints curtailment are designed ensure certain level utilization each farm decision-making. Then, an easy-to-implement variant Benders decomposition (BD) algorithm developed solve resulting mixed integer nonlinear programming problem. Our case studies IEEE test indicate that can co-optimize types ESSs flexible schemes achieve economic power. In addition, BD improve computational efficiency solving this kind problems.