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Researchers in EAEI focus on three broad areas: Energy Markets, Policy, and Infrastructure; Energy and Environmental Systems Analysis; and Appliance and Equipment Energy Efficiency Standards.

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Proceedings of the Annual Hawaii International Conference on System Sciences: Data-Driven Power System Optimal Decision Making Strategy under Wildfire Events

Publication Type

Conference Paper

Date Published

01/2022

Authors

Hong, Wanshi, Bin Wang, Mengqi Yao, Duncan S Callaway, Larry L Dale, Can Huang

Tertiary Author

Bui, Tung

DOI

10.24251/HICSS.2022.00010.24251/HICSS.2022.436

Abstract

Wildfire activities are increasing in the western United States in recent years, causing escalating threats to power systems. This paper developed an optimal and data-driven decision-making framework that improves power system resilience under wildfire risks. An optimal load shedding plan is formulated based on optimal power flow analysis. To avoid power system cascading failure caused by wildfire, we added additional transmission line flow constraints based on the identification of power lines with high ignition risk. Finally, a data-driven method is developed, leveraging multiple machine learning techniques, to model the complex correlations between input wildfire scenarios and the output power management strategy with significantly reduced computational complexities. The proposed data-driven decision-making framework can reduce the safety impacts on the electricity consumers, improve power system resilience under wildfire events.

Journal

Hawaii International Conference on System Sciences - Proceedings of the 55th Hawaii International Conference on System Sciences

Year of Publication

2022