Stochastic optimal allocation for a battery energy storage system in high renewable-penetrated distribution networks

Author:

Zhang Changjun,Li Zhongzhong,Ma Lihong,Li Sifan,Fu Linbei,Zhou Hang,Wang Haisheng,Wu Yufen

Abstract

As the penetration of renewable distributed generation (RDG) continues to grow, the stochastic and intermittent nature of its output imposes significant challenges on distribution networks (DNs), such as source–load mismatch and voltage fluctuations, which seriously affects the safety and reliability of the system. Thus, this paper presents a stochastic optimal allocation method for a battery energy storage system (BESS) in the DN, with the consideration of annual load growth, BESS degradation, and DN operation, aiming to minimize the overall cost of DNs and harvest more renewable energy. Based on the rainflow-counting concept, BESS degradation is efficiently modeled and linearized to improve solvability. Additionally, to address the uncertainties of RDG outputs and loads, a stochastic optimization (SO) method is adopted. Furthermore, considering that a large number of integer variables of the BESS allocation model may cause a heavy computational burden, a feasibility pump-based solution algorithm is introduced to accelerate the solving speed. Finally, the effectiveness of the proposed BESS allocation method and the solution algorithm is verified on a 33-bus DN system through comparative analyses, showing high efficiency and performance.

Publisher

Frontiers Media SA

Reference38 articles.

1. Optimize configuration of multi-energy storage system in a standalone Microgrid;Chen;Front. Energy Res.,2023

2. Joint planning of electric vehicle charging station and energy storage system in the distribution network;Cheng,2023

3. A practical scheme to involve degradation cost of lithium-ion batteries in vehicle-to-grid applications;Farzin;IEEE Trans. Softw. Eng.,2016

4. The feasibility pump;Fischetti;Math. Program.,2005

5. What drives capacity degradation in utility-scale battery energy storage systems? The impact of operating strategy and temperature in different grid applications;Gräf;J. Energy Storage,2022

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