Risk-aware cooperative planning of energy storage in multi-regional power systems under extreme weather: CVaR-based transfer pricing and contribution-based Nash bargaining

The increasing integration of renewable generation highlights the need for cross-regional resource sharing, especially during extreme-weather events that cause renewable droughts and supply shortages. However, regional differences in renewable profiles, load characteristics, flexibility resources, storage investment potential, and risk exposure make sustained cooperation difficult. System-level cost minimization can lead to uneven support obligations, risk burdens, and benefits among autonomous regions. This paper proposes a risk-aware cooperative energy storage planning framework for multi-regional power systems. The framework first introduces a physical planning model that jointly optimizes the siting and sizing of short- and long-duration energy storage, as well as cross-regional operations under both normal and extreme-weather scenarios. A risk-adjusted transfer-pricing rule combines a load-weighted conditional shadow-price signal with an average conditional value-at-risk (CVaR) allocation charge. The resulting recipient-side prices are used to value outward emergency support and determine contribution-based weights for asymmetric Nash bargaining, which allocates the cooperative surplus under individual-rationality and internal budget-balance constraints. A three-level C&CG–AOP–ADMM procedure is developed for distributed planning and exchange coordination, with exchange valuation and surplus allocation based on regional optimization outputs. Numerical studies on a four-region IEEE RTS-24 system show that cooperation reduces system physical cost by 29.14% and expected load shedding by 48.64% relative to independent regional planning, while the proposed allocation links regional surplus shares to recipient-valued support contributions and satisfies individual rationality and internal budget balance.

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Publication Details

Journal
Applied Energy
Published
2026-10-13
DOI
https://doi.org/10.1016/j.apenergy.2026.128987
Primary Topic
Electric Power System Optimization
Type
article
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article

Risk-aware cooperative planning of energy storage in multi-regional power systems under extreme weather: CVaR-based transfer pricing and contribution-based Nash bargaining

Suhua Lou, Aoli Huang, Tao Xiong
Applied Energy
Electric Power System Optimization
article

Risk-aware cooperative planning of energy storage in multi-regional power systems under extreme weather: CVaR-based transfer pricing and contribution-based Nash bargaining

Suhua Lou, Aoli Huang, Tao Xiong
article en

Abstract

The increasing integration of renewable generation highlights the need for cross-regional resource sharing, especially during extreme-weather events that cause renewable droughts and supply shortages. However, regional differences in renewable profiles, load characteristics, flexibility resources, storage investment potential, and risk exposure make sustained cooperation difficult. System-level cost minimization can lead to uneven support obligations, risk burdens, and benefits among autonomous regions. This paper proposes a risk-aware cooperative energy storage planning framework for multi-regional power systems. The framework first introduces a physical planning model that jointly optimizes the siting and sizing of short- and long-duration energy storage, as well as cross-regional operations under both normal and extreme-weather scenarios. A risk-adjusted transfer-pricing rule combines a load-weighted conditional shadow-price signal with an average conditional value-at-risk (CVaR) allocation charge. The resulting recipient-side prices are used to value outward emergency support and determine contribution-based weights for asymmetric Nash bargaining, which allocates the cooperative surplus under individual-rationality and internal budget-balance constraints. A three-level C&CG–AOP–ADMM procedure is developed for distributed planning and exchange coordination, with exchange valuation and surplus allocation based on regional optimization outputs. Numerical studies on a four-region IEEE RTS-24 system show that cooperation reduces system physical cost by 29.14% and expected load shedding by 48.64% relative to independent regional planning, while the proposed allocation links regional surplus shares to recipient-valued support contributions and satisfies individual rationality and internal budget balance.

Applied EnergyVol. 427
State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology (CN)
Openalex Percentile: Top 23%
Electric Power System Optimization
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