Transmission and Distribution Equipment: Providing Intelligent Maintenance

Abstract

One of the cornerstones of a reliable transmission and distribution grid operation are fully functional components that can operate robustly and with a low outage rate under all specified operating conditions. Dependable maintenance strategies are thus indispensable and are applied by grid operators around the world. One of the present key challenges in most countries with a widely developed transmission and distribution (T&D) grid system are aging components that reach their anticipated end of life. Asset management faces the question if the lifetime of components could be prolonged, and the replacement could be delayed. For this, the health of the components needs to be assessed and is ideally continuously monitored. In addition to this, the currently ongoing transition of the entire energy system leads to a change and increase of the stress to the T&D equipment. The integration of new renewable energy sources on all voltage levels leads to bi‐directional power‐flows and increased variability. The higher demand for electric power not only increases the power flow levels on average, but in particular also the peak flows. The result of this changed and increased stress on the equipment is an accelerated component aging and the need for maintenance strategies to be adopted to this new situation. Recent developments in low‐cost and low‐power data acquisition technology and machine learning based algorithms, combined with rapidly increasing decentralized embedded computing power, offer the opportunity to develop improved and intelligent maintenance strategies based on continuous monitoring and real‐time health evaluation of the equipment. This paradigm changes the prospects in equipment maintenance, offering significantly reduced costs in asset management. The lifetime of properly dimensioned equipment is expected to be several decades, sometimes as much as 40 to 60 years. Most maintenance checks therefore only confirm the excellent condition of the component and would have not been necessary at this point in time. Thus, not only delaying the replacement, but also delaying a maintenance interval based on the health condition would be very welcome. Hence, the most commonly used maintenance concepts are changed from time‐based checks to a new and more intelligent approach, oriented towards a just‐in‐time service. This article aims to introduce the concepts of intelligent maintenance strategies, trends, and challenges of T&D equipment condition monitoring, as well as the automatic estimation of equipment health.