Role of Statistical and Machine Learning Methods in Special Protection Scheme Logic Design and Failure Assessment

Abstract

With tremendous growth in variable renewable generation and uncertainties in power system operations, there has been lot of installations of special protection schemes in many parts of the world. A special protection scheme, also termed a remedial action scheme, is the high-end last line of defense mechanism to relieve the system from catastrophic consequences under highly stressed conditions. This article delineates the special protection scheme logic design process and, with the help of a Nordic grid case study, proposes a new paradigm of special protection scheme failure assessment and logic design process, namely the “system-view” framework. In this context, the article also demonstrates the application of decision tree-based methods to derive special protection scheme operational logic and provides a pathway to use efficient statistical sampling techniques for implementing the system-view special protection scheme failure assessment method, thereby advancing the logic redesign process.