A Resilience-Oriented Multi-Stage Adaptive Distribution System Planning Considering Multiple Extreme Weather Events

• Published in: IEEE transactions on sustainable energy Vol. 14; no. 2; pp. 1 - 11
• Main Authors: Wang, Siyuan, Bo, Rui
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.04.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptation models; Adaptive systems; Algorithms; Climate change; Decisions; distribution system resilience; Energy storage; Extreme weather; Investment; Investments; Meteorological satellites; Meteorology; mobile energy storage; multi-stage adaptive optimization; multiple extreme weather events; Planning; Renewable energy sources; Resilience; resilience-oriented planning; Stochasticity; Uncertainty; Weather
• ISSN: 1949-3029; 1949-3037
• DOI: 10.1109/TSTE.2023.3234916

Climate change may increase the risk of an area being hit by multiple extreme weather events, which brings significant challenges for distribution system planners in an increasing renewable penetration era. There is an urgent need for planning approaches to be more flexible and allow for adaptive adjustments in the future to hedge against high uncertainties in extreme weather event scenarios. In this work, we propose a resilience-oriented distribution system planning approach that considers multiple extreme weather events. A multi-stage hybrid-stochastic-and-robust formulation is developed to model decisions not only for initial investments, but also for adaptive investments and emergent operations in response to particular extreme events, meanwhile considering both long-term and short-term uncertainties. Our model is solved by a novel progressive hedging algorithm that is embedded with a nested column-and-constraint generation method. Case studies demonstrate the benefits of the proposed approach in making flexible and affordable planning decisions to protect distribution systems against multiple extreme weather events.