Optimal mitigation and control over power system dynamics for stochastic grid resilience

被引:0
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作者
Nathan Stewart
Bryan Arguello
Matthew Hoffman
Bethany Nicholson
Richard Garrett
机构
[1] Sandia National Laboratories,
来源
关键词
Power system dynamics; Control optimization; Stochastic optimization; Generalized disjunctive programming;
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摘要
Optimal mitigation planning for highly disruptive contingencies to a transmission-level power system requires optimization with dynamic power system constraints, due to the key role of dynamics in system stability to major perturbations. We formulate a generalized disjunctive program to determine optimal grid component hardening choices for protecting against major failures, with differential algebraic constraints representing system dynamics (specifically, differential equations representing generator and load behavior and algebraic equations representing instantaneous power balance over the transmission system). We optionally allow stochastic optimal pre-positioning across all considered failure scenarios, and optimal emergency control within each scenario. This novel formulation allows, for the first time, analyzing the resilience interdependencies of mitigation planning, preventive control, and emergency control. Using all three strategies in concert is particularly effective at maintaining robust power system operation under severe contingencies, as we demonstrate on the western system coordinating council 9-bus test system using synthetic multi-device outage scenarios.
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页码:911 / 940
页数:29
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