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Stochastic Optimization of Power System Dynamics for Grid Resilience
Item Summary
Title: | Stochastic Optimization of Power System Dynamics for Grid Resilience |
Authors: | Arguello, Bryan Stewart, Nathan Hoffman, Matt |
Keywords: | Resilient Networks dynamic stochastic optimziation grid stability optimal power flow resilience |
Date Issued: | 05 Jan 2021 |
Abstract: | When faced with uncertainty regarding potential failure contingencies, prioritizing system resiliency through optimal control of exciter reference voltage and mechanical torque can be arduous due to the scope of potential failure contingencies. Optimal control schemes can be generated through a two-stage stochastic optimization model by anticipating a set of contingencies with associated probabilities of occurrence, followed by the optimal recourse action once the contingency has been realized. The first stage, common across all contingency scenarios, co-optimally positions the grid for the set of possible contingencies. The second stage dynamically assesses the impact of each contingency and allows for emergency control response. By unifying the optimal control scheme prior and post the failure contingency, a singular policy can be constructed to maximize system resiliency. |
Pages/Duration: | 9 pages |
URI: | http://hdl.handle.net/10125/71023 |
ISBN: | 978-0-9981331-4-0 |
DOI: | 10.24251/HICSS.2021.408 |
Rights: | Attribution-NonCommercial-NoDerivatives 4.0 International https://creativecommons.org/licenses/by-nc-nd/4.0/ |
Appears in Collections: |
Resilient Networks |
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