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Risk Assessment and Mitigation of Cascading Failures Using Critical Line Sensitivities

Yitian Dai, Matthias Noebels, Robin Preece, Mathaios Panteli, Ian Dobson

2023IEEE Transactions on Power Systems33 citationsDOIOpen Access PDF

Abstract

Security concerns have been raised about cascading failure risks in evolving power grids. This article reveals, for the first time, that the risk of cascading failures can be increased at low network demand levels when considering security-constrained generation dispatch. This occurs because critical transmission corridors become very highly loaded due to the presence of centralized generation dispatch, e.g., large thermal plants far from demand centers. This increased cascading risk is revealed in this work by incorporating security-constrained generation dispatch into the risk assessment and mitigation of cascading failures. A security-constrained AC optimal power flow, which considers economic functions and security constraints (e.g., network constraints, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$N - 1$</tex-math></inline-formula> security, and generation margin), is used to provide a representative day-ahead operational plan. Cascading failures are simulated using two simulators, a quasi-steady state DC power flow model, and a dynamic model incorporating all frequency-related dynamics, to allow for result comparison and verification. The risk assessment procedure is illustrated using synthetic networks of 200 and 2,000 buses. Further, a novel preventive mitigation measure is proposed to first identify critical lines, whose failures are likely to trigger cascading failures, and then to limit power flow through these critical lines during dispatch. Results show that shifting power equivalent to 1% of total demand from critical lines to other lines can reduce cascading risk by up to 80%.

Topics & Concepts

Cascading failureReliability engineeringElectric power transmissionEconomic dispatchElectric power systemComputer scienceCritical infrastructureMargin (machine learning)Electricity generationPower (physics)EngineeringComputer securityElectrical engineeringPhysicsQuantum mechanicsMachine learningOptimal Power Flow DistributionPower System Optimization and StabilityElectric Power System Optimization