A Two-Tier Planning Approach for Hybrid Energy Storage Systems Considering Grid Power Flexibility in New Energy High-Penetration Grids

Wei Huang, Dongbo Qu, Chen Wu, Kai Hu, Tao Qiu, Weidong Wei, Guanhui Yin and Xianguang Jia ()
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Wei Huang: School of Electrical Engineering, Chongqing University, Chongqing 400044, China
Dongbo Qu: Qujing Power Supply Bureau, Yunnan Power Grid Co., Ltd., Qujing 655000, China
Chen Wu: Grid Planning Research Center, Yunnan Power Grid Co., Ltd., Kunming 650000, China
Kai Hu: Qujing Power Supply Bureau, Yunnan Power Grid Co., Ltd., Qujing 655000, China
Tao Qiu: Qujing Power Supply Bureau, Yunnan Power Grid Co., Ltd., Qujing 655000, China
Weidong Wei: Qujing Power Supply Bureau, Yunnan Power Grid Co., Ltd., Qujing 655000, China
Guanhui Yin: Qujing Power Supply Bureau, Yunnan Power Grid Co., Ltd., Qujing 655000, China
Xianguang Jia: School of Transportation Engineering, Kunming University of Science and Technology, Kunming 650000, China

Energies, 2025, vol. 18, issue 18, 1-25

Abstract: This paper proposes a flow battery-lithium-ion battery hybrid energy storage system (HESS) bi-level optimization planning method to address flexibility supply-demand balance challenges in regional power grids with high renewable penetration at 220 kV and above voltage levels. The method establishes a planning-operation coordination framework: Upper-level planning minimizes total lifecycle investment and operation-maintenance costs; Lower-level operation incorporates multiple constraints including flexibility gap penalties, voltage fluctuations, and line losses, overcoming single-timescale limitations. The approach enhances global search capability through the Improved Weighted Average Algorithm (IWAA) and optimizes power allocation accuracy using adaptive Variational Mode Decomposition (VMD). Validation using grid data from Southwest China demonstrates significant improvements across five comparative schemes. Results show substantial reductions in total investment costs, penalty costs, voltage fluctuations, and line losses compared to benchmark solutions, enhancing grid power supply stability and verifying the effectiveness of the model and algorithm.

Keywords: bi-level optimization; HESS; renewable energy integration; VMD; weighted adaptive algorithm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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