Minimax Regret Robust Co-Planning of Transmission and Energy Storage Systems With Mixed Integer Recourse
The growing penetration of renewable energy sources, with intermittent and uncertain nature, brings new challenges to the secure and efficient operation of power systems. Expanding transmission networks and utilizing energy storage (ES) have been introduced as effective solutions to address these challenges. This paper presents a minimax regret robust co-planning model with mixed integer recourse for transmission and ES systems, designed from the perspective of a central planner. The model considers a polyhedral uncertainty set for future peak load growth, while uncertainties in wind farm expansion are addressed through internal scenario analysis. This approach will guarantee the robustness of investment decisions and provide the central planner with a clear picture of the maximum regret among all possible scenarios. Furthermore, the proposed minimax regret framework facilitates strategic planning for ES installation after the resolution of long-term uncertainties. In this paper, we reformulate the model into a standard min-max-min problem, in which the maximization level is only over uncertainties. Subsequently, a five-level solution strategy based on a modified nested column and constraint generation decomposition technique is represented to deal with the intractability and complexity of the problem caused by binary variables of transmission lines and ES blocks. The model is finally evaluated through comprehensive simulation studies to verify its tractability, practicality, and effectiveness.
Authors
- Moein Moeini‐Aghtaie (ORCID: https://orcid.org/0000-0002-7656-6807)
- Mehdi Ehsan (ORCID: https://orcid.org/0000-0002-1178-5750)
- Mohammad Shahidehpour (ORCID: https://orcid.org/0000-0002-8994-1688)
- Hossein Saber (ORCID: https://orcid.org/0000-0001-9363-5571)
- Ehsan Barkom (ORCID: https://orcid.org/0000-0001-6538-5587)
Institutions
- Sharif University of Technology (IR)
- Illinois Institute of Technology (US)
Publication Details
- Journal
- IEEE Transactions on Sustainable Energy
- Published
- 2025-03-04
- DOI
- https://doi.org/10.1109/tste.2025.3547836
- Citations
- 3
- Primary Topic
- Optimal Power Flow Distribution
- Type
- article
- Field-Weighted Citation Impact
- 2.19