Abstract
Networked power grid systems are susceptible to a phenomenon known as Coherent Swing Instability (CSI), in which a subset of machines in the grid lose synchrony with the rest of the network. We develop network level evaluation metrics to (i) identify community substructures in the power grid network, (ii) determine weak points in the network that are particularly sensitive to CSI, and (iii) produce an engineering approach for the addition of transmission lines to reduce the incidences of CSI in existing networks, or design new power grid networks that are robust to CSI by their network design. For simulations on a reduced model for the American Northeast power grid, where a block of buses representing the New England region exhibit a strong propensity for CSI, we show that modifying the network’s connectivity structure can markedly improve the grid’s resilience to CSI. Our analysis provides a versatile diagnostic tool for evaluating the efficacy of adding lines to a power grid which is known to be prone to CSI. This is a particularly relevant problem in large-scale power systems, where improving stability and robustness to interruptions by increasing overall network connectivity is not feasible due to financial and infrastructural constraints.
Highlights
Disruptions of power grid systems can have a severe, negative impact on performance and lead to Coherent Swing Instability (CSI) (Susuki and Mezic 2011; Susuki et al 2011; Susuki and Mezic 2012), whereby a subset of machines in the grid lose synchrony with the rest of the network, shutting the entire network down and leading to unacceptable blackouts
We propose a computational framework for the analysis of the network level dynamics and stability of power system disturbances
By systematically parametrizing disturbances according to the temporal parameters τ1 and τ2, we can assess the effect of each node on the overall stability of the power grid network
Summary
Disruptions of power grid systems can have a severe, negative impact on performance and lead to Coherent Swing Instability (CSI) (Susuki and Mezic 2011; Susuki et al 2011; Susuki and Mezic 2012), whereby a subset of machines in the grid lose synchrony with the rest of the network, shutting the entire network down and leading to unacceptable blackouts. In this work we seek to capitalize on this property by applying a dynamics-focused community detection perspective to simulation data generated by a realistic, machine-level power grid model. While this approach has previously been applied to steady-state systems (Baldick et al 2009), its use for grid disturbances has generally been dismissed as infeasible due to the combinatorially large search space of possible faults and network structures (Hines et al 2010).
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