Distributed energy storage planning method considering multi-point aggregation effect

ABSTRACT

The economic performance and utilization rate have become the key factors limiting the development of energy storage systems (ESS). From the perspective of the aggregation effect manifested by multi-point ESS, an inspired concept of “aggregation configuration, decentralized location” is proposed. Based on this concept, this paper proposes a planning method using two-stage optimization including sizing, siting and operational optimization for distributed energy storage (DES). The first-stage optimization aims to maximize the net present value (NPV) of aggregate ESS, while the second stage aims to mitigate the voltage fluctuation after the integration of distributed PV generation. In addition, the operational optimization for both the aggregate ESS and individual DES units are considered to better achieve the objectives of the two-stage optimization, and the particle swarm optimization (PSO) algorithm is employed to solve the planning problem. Case studies show that the proposed method helps to ensure the global NPV over the lifespan of aggregate ESS by considering operational optimization and depth of charge (DOD). Compared with the centralized ESS solution, the proposed multi-point DES solution can improve the overall voltage fluctuation mitigation capability by more than 40%. With the PV capacity penetration rate varying from 0 ~ 210%, sensitivity analysis reveals that when the penetration rate is close to 100%, the aggregate ESS has better economic performance and voltage fluctuation mitigation capability.

KEYWORDS:

• Distributed energy storage
• aggregation effect
• optimal sizing
• site selection
• multi-point
• two-stage optimization

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Disclosure statement

No potential conflict of interest was reported by the author(s).

Author contributions

The individual contributions of the authors are specified as follows: Conceptualization, L.Z. and M.W.; Methodology, L.Z.; Software, J.Z.; Validation, Q.Z., J.Z. and L.Z.; Formal analysis, M.W.; Writing—original draft preparation, D.M. and J.Z.; Writing—review and editing, L.Z. and Q.Z.; Supervision, D.W. All authors have read and agreed to the published version of the manuscript.

Data availability statement

All data is available in publicly accessible repositories.

Additional information

Funding

This work was supported by State Grid Gansu Electric Power Co., Ltd. Science and Technology Project (No. 52272219100F) “Research and analysis based on the income of distributed energy storage in Gansu.”

Notes on contributors

Mingsong Wang

Wang Mingsong obtained his master's degree from Xi'an Jiaotong University in 2013. He currently works at Power Grid Technology Department, Electric Power Research Institute of State Grid Gansu Electric Power Company, Gansu, China. His main research direction is new energy power generation and grid-connected technology.

Long Zhao

Zhao Long obtained his master's degree from Huazhong University of Science and Technology in 2009. He currently works at Power Grid Technology Department, Electric Power Research Institute of State Grid Gansu Electric Power Company, Gansu, China. His main research direction is new energy power generation and grid-connected technology.

Qiang Zhou

Zhou Qiang obtained his master's degree from Zhejiang University in 2010. He currently works at Power Grid Technology Department, Electric Power Research Institute of State Grid Gansu Electric Power Company, Gansu, China. His main research direction is new energy power generation and grid-connected technology.

Jinping Zhang

Zhang Jinping obtained his master's degree from Hunan University in 2011. He currently works at Power Grid Technology Department, Electric Power Research Institute of State Grid Gansu Electric Power Company, Gansu, China. His main research direction is new energy power generation and grid-connected technology.

Dingmei Wang

Wang Dingmei obtained his master's degree from Wuhan University in 2010. She currently works at Power Grid Technology Department, Electric Power Research Institute of State Grid Gansu Electric Power Company, Gansu, China. Her main research direction is new energy power generation and grid-connected technology.