Stochastic Bidding for Hydro–Wind–Solar Systems in Cross-Provincial Forward–Spot Markets: A Dimensionality-Reduced and Transmission-Aware Framework

Yan Zhang, Xue Hu, Xiangzhen Wang, Xiaoqian Zhou, Yuyang Liu, Bohan Zhang and Yapeng Li ()
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Yan Zhang: Hubei Key Laboratory of Intelligent Yangtze and Hydroelectric Science, China Yangtze Power Co., Ltd., Yichang 443000, China
Xue Hu: Institute of Hydropower & Hydroinformatics, Dalian University of Technology, Dalian 116024, China
Xiangzhen Wang: Institute of Hydropower & Hydroinformatics, Dalian University of Technology, Dalian 116024, China
Xiaoqian Zhou: Hubei Key Laboratory of Intelligent Yangtze and Hydroelectric Science, China Yangtze Power Co., Ltd., Yichang 443000, China
Yuyang Liu: Institute of Hydropower & Hydroinformatics, Dalian University of Technology, Dalian 116024, China
Bohan Zhang: Hubei Key Laboratory of Intelligent Yangtze and Hydroelectric Science, China Yangtze Power Co., Ltd., Yichang 443000, China
Yapeng Li: Institute of Hydropower & Hydroinformatics, Dalian University of Technology, Dalian 116024, China

Energies, 2025, vol. 18, issue 16, 1-22

Abstract: Integrated hydro–wind–solar power generators (IPGs) in China face multi-timescale bidding challenges across provincial forward–spot markets, which are further compounded by hydropower nonconvexity and transmission constraints. This study proposes a stochastic optimization model addressing uncertainties from wind–solar generation and spot prices through scenario-based programming, integrating three innovations: average-day dimensionality reduction to harmonize monthly–hourly decisions, local generation function approximation to linearize hydropower operations, and transmission-aware coordination for cross-provincial allocation. Validation on a southwestern China cascade hydropower base transmitting power to eastern load centers shows that the model establishes hydropower-mediated complementarity with daily “solar–daytime, wind–nighttime” and seasonal “wind–winter, solar–summer” patterns. Furthermore, by optimizing cross-provincial power allocation, strategic spot market participation yields 46.4% revenue from 30% generation volume. Additionally, two transmission capacity thresholds are found to guide grid planning: 43.75% capacity marks the economic optimization inflection point, while 75% represents technical saturation. This framework ensures robustness and computational tractability while enabling IPGs to optimize profits and stability in multi-market environments.

Keywords: multi-timescale bidding; hydro–wind–solar integration; cross-provincial electricity markets; hydropower scheduling; stochastic optimization; transmission capacity thresholds (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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