Coordinated Planning for Multiarea Wind-Solar-Energy Storage Systems That Considers Multiple Uncertainties

Weijie Wu, Yixin Li, Shu Wang (), Zheng Wang, Shucan Zhou, Yining Zhang and Minjia Zheng
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Weijie Wu: Guangdong Power Grid Planning Research Center, Guangdong Power Grid Corporation, Guangzhou 510062, China
Yixin Li: Guangdong Power Grid Planning Research Center, Guangdong Power Grid Corporation, Guangzhou 510062, China
Shu Wang: National Key Laboratory of Renewable Energy Grid-Integration, China Electric Power Research Institute, Beijing 100192, China
Zheng Wang: National Key Laboratory of Renewable Energy Grid-Integration, China Electric Power Research Institute, Beijing 100192, China
Shucan Zhou: Guangdong Power Grid Planning Research Center, Guangdong Power Grid Corporation, Guangzhou 510062, China
Yining Zhang: Guangdong Power Grid Planning Research Center, Guangdong Power Grid Corporation, Guangzhou 510062, China
Minjia Zheng: Guangdong Power Grid Planning Research Center, Guangdong Power Grid Corporation, Guangzhou 510062, China

Energies, 2024, vol. 17, issue 21, 1-24

Abstract: As the scale of renewable energy sources (RESs) expands, it is essential to optimize the configuration of wind, solar, and storage resources across different areas. Nevertheless, the unavoidable uncertainties associated with both energy supply and demand present significant challenges for planners. This study aims to address the challenge of coordinated planning for multiarea wind-solar-energy storage systems considering multiple uncertainties. First, uncertainties related to future peak demand, thermal generation output boundaries, demand variability, and stochastic unit production are analyzed and modeled on the basis of robust optimization and stochastic programming techniques. Then, a hierarchical coordinated planning model that incorporates both system-wide (SW) and local area (LA) planning models is proposed. The SW planning model is designed to manage the optimal capacity configuration of RESs and energy storage systems (ESSs) within each LA, as well as the operational boundary of LAs. The LA planning models aim to further optimize the capacities of RESs and ESSs and minimize the economic cost within each LA on the basis of local resource characteristics. To achieve the optimal solution, the analytical target cascading (ATC) algorithm is integrated with the column-and-constraint generation (C&CG) algorithm. The simulation results validate the effectiveness and reasonableness of the proposed coordinated planning model, which not only outperforms independent planning approaches but also effectively manages the uncertainties.

Keywords: coordinated planning; renewable energy source; energy storage system; robust optimization; stochastic programming; uncertainty (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: 2024
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