Multi-Scenario Pumped Storage Capacity Timeline Configuration Method Adapted to New Energy Development

Danwen Hua, Linjun Shi (), Lingkai Zhu, Ziwei Zhong, Zhiqiang Gong, Junshan Guo and Wei Zheng
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Danwen Hua: School of Electrical and Power Engineering, Hohai University, Nanjing 211100, China
Linjun Shi: School of Electrical and Power Engineering, Hohai University, Nanjing 211100, China
Lingkai Zhu: State Grid Shandong Electric Power Research Institute, Jinan 250003, China
Ziwei Zhong: State Grid Shandong Electric Power Research Institute, Jinan 250003, China
Zhiqiang Gong: State Grid Shandong Electric Power Research Institute, Jinan 250003, China
Junshan Guo: State Grid Shandong Electric Power Research Institute, Jinan 250003, China
Wei Zheng: State Grid Shandong Electric Power Research Institute, Jinan 250003, China

Sustainability, 2025, vol. 17, issue 17, 1-20

Abstract: Traditional pumped storage capacity configuration uses static, year-targeted approaches, leading under-capacity in the early planning stages—wasting renewable energy—and over-capacity in later stages, thus wasting resources. In order to solve the above problems, this article innovatively proposes a dynamic, time-sequenced construction timeline and annual capacity configuration strategy, synchronized with new energy and load development, enhancing sustainability through optimized investment allocation and efficient resource utilization. It presents a two-layer model that considers multiple scenario operational dispatch. The upper layer aims to minimize the curtailment of wind and solar energy, providing a planning scheme to the lower layer, which focuses on multi-scenario economic dispatch, taking into account the peak-valley difference indicators. The models co-iterate: lower-layer operational outcomes feed back to refine the upper-layer’s capacity plan. This process continues until the predicted curtailment calculated by the upper layer aligns closely with that observed in the lower-layer operational simulations, or until capacity changes stabilize, ultimately determining the optimal time-phased capacity configuration. Simulations on a provincial power grid during three typical scenarios in winter, transitional seasons, and summer, as well as extreme weather scenarios, confirm that timely, dynamic configuration strategy significantly enhances renewable absorption, proving the model’s effectiveness.

Keywords: pumped storage; renewable energy absorption; capacity configuration; timeline; two-layer model; multiple scenarios; improved GWO algorithm (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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