A Risk-Driven Probabilistic Approach to Quantify Resilience in Power Distribution Systems
Jul 4, 2022·
,,·
0 min read
Abodh Poudyal
Shiva Poudel
Anamika Dubey
Abstract
It is of growing concern to ensure resilience in power distribution systems to extreme weather events. However, there are no clear methodologies or metrics available for resilience assessment that allows system planners to assess the impact of appropriate planning measures and new operational procedures for resilience enhancement. In this paper, we propose a resilience metric using parameters that define system attributes and performance. To represent extreme events (tail probability), the conditional value-at-risk of each of the parameters are combined using Choquet Integral to evaluate the overall resilience. The effectiveness of the proposed resilience metric is studied within the simulation-based framework under extreme weather scenarios with the help of a modified IEEE 123-bus system. With the proposed framework, System operators will have additional flexibility to prioritize one investment over the others to enhance the resilience of the grid.
Type
Publication
2022 17th International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)
Distribution System Resilience
Monte-Carlo Simulation
Multi-Criteria Decision-Making
Resilience Metric
Risk Analysis
Authors
Sr. Software Power Systems Engineer
Abodh Poudyal is a Senior Software Power Systems Engineer at Electric Power Engineers, where he leads efforts in developing automated solutions for grid modernization, resilience, and reliability.
Abodh is passionate about advancing the future of power systems through innovative software solutions. With over nine years of experience, Abodh specializes in automating grid operations and developing scalable tools for utilities.
His expertise spans power system analysis, operations research, machine learning, high-performance computing, and software develpoment. Before joining EPE, Abodh worked as a researcher with the National Renewable Energy Laboratory (now known as the National Laboratory of the Rockies). He is also actively involved as a secretary of the IEEE Modern and Future Distribution Systems Planning Working Group.
His expertise spans power system analysis, operations research, machine learning, high-performance computing, and software develpoment. Before joining EPE, Abodh worked as a researcher with the National Renewable Energy Laboratory (now known as the National Laboratory of the Rockies). He is also actively involved as a secretary of the IEEE Modern and Future Distribution Systems Planning Working Group.
Authors
Authors