Application of machine learning techniques for asset management and proactive analysis in power systems

Abstract

Today, the generation, transmission, and distribution business of power systems are suffering essential and fast changes in their operative and management strategies worldwide. Some decades ago, the liberalization of the electricity markets introduced a new significant competition factor within the sector, followed by increasing demand for quality of service from customers and public administrations. More recently, the digitalization of power systems and new concepts about Smart Grids allow the collection of more and more information about the power system components. This enables recording data in a more orderly and reliable way that can be used for better operation and maintenance and, ultimately, better management of the available resources in power systems, the main idea of the Asset Management concept.