Rethinking Power System Protection Analysis and Setting: Introducing Bayesian Analysis and Decision Theory

Abstract

Reliability of future renewable-driven power systems may be compromised under present operation and planning paradigms. Given the identified failures of existing protection functions in the vicinity of grid-connected converters, protection function reliability will become an important factor in overall system reliability. Current protection analyses and suggested improvements offer practical insights for specific test systems, but fail to quantify protection performance. Therefore, this paper proposes a framework for probabilistic protection analysis and setting, to quantify the upper limit on protection function performance and steering protection performance to a desired reliability level. Four case studies are considered to demonstrate setting protections to achieve a desired system reliability, quantifying limits on protection function performance and tuning controllable fault current infeed for improving protection performance. Future work will focus on exploring additional insights in protection functions and application of the framework to more complex settings.