Work

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

Year: 2026

Type: article

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.

Source: Applied Energy

DOI: 10.1016/j.apenergy.2026.128987

Authors: Aoli Huang, Suhua Lou, Tao Xiong

Institutions: State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology

Language: English

Topic: Electric Power System Optimization

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Climate action, Industry, innovation and infrastructure

Open Access status: hybrid

Estimated APC paid: $4,430