Toward Climate-Adaptive Low-Carbon Power System Planning: A Multistage Stochastic Framework Considering Climate Uncertainties

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Authors: Chenjia Gu, Jiaqi RUAN, Yiwei Qiu, Tianlei Zang, Shi Chen, Zhao Xu, Fushuan Wen, Pei Zhang, Zhao Yang Dong, Peng Wang
Cited by: 4
References: 26

Abstract

Climate change is progressively reshaping the spatiotemporal dynamics of renewable energy sources such as wind and solar, intensifying the complexity and uncertainty of long-term power system planning. Existing planning frameworks are largely focused on climate mitigation strategies but often overlook the critical dimension of climate adaptation, limiting their efficacy in managing evolving climatic risks. In response, this article proposes a multistage stochastic low-carbon planning framework that incorporates climate-related uncertainties into system planning decision-making. By embedding climate evolution trajectories into the planning horizon, the proposed approach determines optimal stage-wise planning pathways that jointly accommodate mitigation goals and adaptation imperatives under long-term climate uncertainties. First, a systematic climate uncertainty modeling approach is developed to capture both scenario uncertainty and climate response uncertainty through the construction of a representative scenario tree. Second, to reconcile the temporal mismatch between coarse-resolution climate projections and the finegrained requirements of power system planning, a climate-consistent temporal downscaling method is proposed to transform long-term climate projections into high-resolution, hourly level data. Third, to address the computational complexity inherent in the multistage planning problem, a tailored decomposition-based stochastic dual dynamic programming algorithm is developed, which operates on a stage-wise clustered scenario tree to leverage the tree’s structural compactness for accelerated convergence and scalable optimization under climate-related uncertainties. Numerical studies demonstrate that the proposed climate-adaptive planning framework enhances the power system’s ability to manage climate-induced risks while maintaining cost-effectiveness across a wide range of plausible climate futures.

Fields of Study & Subjects

Electric Power System Optimization Integrated Energy Systems Optimization Water-Energy-Food Nexus Studies

Publication details

Journal / source
IEEE Transactions on Industrial Informatics
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Volume
22
Issue
5
Pages
3938–3949
Publication date
12 March 2026