Capacity Configuration Method for Hydro-Wind-Solar-Storage Systems Considering Cooperative Game Theory and Grid Congestion

Integrated hydro-wind-solar-storage (HWSS) bases are pivotal for advancing new power systems under the low carbon goals. However, the independent decision-making of diverse generation investors, coupled with limited transmission capacity, often leads to a dilemma in which individually rational decisions lead to collectively suboptimal outcomes, undermining overall benefits. To address this challenge, this study proposes a novel cooperative game-based method that seamlessly integrates grid congestion into capacity allocation and benefit distribution. First, a bi-level optimization model is developed, where a congestion penalty is explicitly embedded into the cooperative game’s characteristic function to quantify the maximum benefits under different coalition structures. Second, an improved Shapley value model is introduced, incorporating a comprehensive correction factor that synthesizes investment risk, congestion mitigation contribution, and capacity scale to overcome the fairness limitations of the classical method. Third, a case study of a high-renewable-energy base in Qinghai is conducted. The results demonstrate that the proposed cooperative model increases total system revenue by 20.1%, while dramatically reducing congestion costs and wind/solar curtailment rates by 86.2% and 79.3%, respectively. Furthermore, the improved Shapley value ensures a fairer distribution, appropriately increasing the profit shares for hydropower (from 28.5% to 32.1%) and energy storage, thereby enhancing coalition stability. This research provides a theoretical foundation and practical decision-making tool for the collaborative planning of HWSS bases with multiple investors.

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Publication Details

Journal
Energies
Published
2025-12-14
DOI
https://doi.org/10.3390/en18246543
Citations
1
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
0.73

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article

Capacity Configuration Method for Hydro-Wind-Solar-Storage Systems Considering Cooperative Game Theory and Grid Congestion

Xuming Mao, Jing Qian, Danning Tian, Haoyan Zhang et al.
1 citations
Energies
Integrated Energy Systems Optimization
0.73
article

Capacity Configuration Method for Hydro-Wind-Solar-Storage Systems Considering Cooperative Game Theory and Grid Congestion

Xuming Mao, Jing Qian, Danning Tian, Haoyan Zhang, Lei Cao
article en
1 citations

Abstract

Integrated hydro-wind-solar-storage (HWSS) bases are pivotal for advancing new power systems under the low carbon goals. However, the independent decision-making of diverse generation investors, coupled with limited transmission capacity, often leads to a dilemma in which individually rational decisions lead to collectively suboptimal outcomes, undermining overall benefits. To address this challenge, this study proposes a novel cooperative game-based method that seamlessly integrates grid congestion into capacity allocation and benefit distribution. First, a bi-level optimization model is developed, where a congestion penalty is explicitly embedded into the cooperative game’s characteristic function to quantify the maximum benefits under different coalition structures. Second, an improved Shapley value model is introduced, incorporating a comprehensive correction factor that synthesizes investment risk, congestion mitigation contribution, and capacity scale to overcome the fairness limitations of the classical method. Third, a case study of a high-renewable-energy base in Qinghai is conducted. The results demonstrate that the proposed cooperative model increases total system revenue by 20.1%, while dramatically reducing congestion costs and wind/solar curtailment rates by 86.2% and 79.3%, respectively. Furthermore, the improved Shapley value ensures a fairer distribution, appropriately increasing the profit shares for hydropower (from 28.5% to 32.1%) and energy storage, thereby enhancing coalition stability. This research provides a theoretical foundation and practical decision-making tool for the collaborative planning of HWSS bases with multiple investors.

EnergiesVol. 18(24)
Kunming University of Science and Technology (CN), New York University (US)
National Natural Science Foundation of China
Openalex Percentile: Top 21%
Integrated Energy Systems Optimization
0.73
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