An Algorithm Suite for Computational Nonlinear Analysis of Power Systems

University Of Illinois At Urbana-Champaign, Urbana IL

Investigators

Abstract

An Algorithm Suite for Computational Nonlinear Analysis of Power Systems This effort targets the original development of CNAPS, an innovative suite of numerical algorithms for continuation analysis of multi-segment trajectories in large-scale, nonlinear dynamical systems with multiple slow and fast timescales, coupled components, and with triggers, resets and switches. Continuation methods have proven very successful for analyzing system behavior of low-dimensional systems. In CNAPS, we aim to dramatically scale continuation methods to complex networked systems with hybrid system trajectories and tens of thousands of states, by developing new multiscale, multisegment, trajectory-discretization algorithms based on asynchronous collocation methods; developing new mesh adaptation algorithms suitable for the asynchronous collocation methods, which accommodate segment-specific discretization error bounds; and constructing domain decomposition methods particular to the network topology and the asynchronous collocation formulation, which enable efficient parallel execution. The core application of CNAPS considered in this multidisciplinary effort is modern power systems that include renewable sources of generation, specifically wind power, and newer forms of load, characterized by multiple coexisting time scales and trigger-induced switching behavior. Analysis of large-disturbance dynamic phenomena in such systems currently relies almost exclusively on forward simulation. While such tools may reveal complex behavior, they offer little help in the design process required to address unacceptable behavior, especially emerging phenomena associated with the increased use of power electronic converters. The development of CNAPS enables intelligent and efficient exploration of transient and steady-state responses of complex power systems, aimed at quantifying design and uncertainty margins for stable, faultless operation.