Grant: Discovery Grants Program - Individual

Canada has set targets to drastically reduce emissions by 2030 and achieve net zero by 2050 (Powering Canada Forward. Natural Resources Canada, 2023). To achieve this goal, the electric power system will need to more than double its current generation capacity to meet the demand for clean, reliable, and affordable electric power in 2050. The safe, stable, and reliable operation of an electrical system heavily relies on its insulation system, composed of solid, liquid, and/or gaseous materials that isolate energized components from each other and from the ground. In high voltage environments, the integrity of the insulation system is crucial, as insulation failure can lead to catastrophic consequences including widespread blackouts, infrastructure damage, and human injury or death. During its operation, an insulation system undergoes electrical stress, which, combined with harsh environmental conditions, can have a significant deteriorating impact on its health. Moreover, modern power electronics used in electrification and renewables operate at high frequencies, intensifying the stress on insulation materials due to rapid voltage switching. A stressed insulating system can experience phenomena such as dielectric breakdown, erosion, or partial discharge (PD). Partial discharge is a localized breakdown that could be a symptom of aging or poor design. The presence of PD, or an increase in its level, could be an indication of accelerated deterioration of the material condition, requiring inspection and/or mitigation to avert catastrophic failures. The focus of the proposed research program is to detect, classify, and identify PD to assess insulation aging, predict its failure, and avoid disruptions and outages. Together with my HQP, we will develop novel PD sensing hardware and establish time-domain techniques for their characterization. Accurate simulation models for various power system components will be developed that are capable of simulating the propagation of PD. We will develop intelligent PD analysis algorithms based on machine learning techniques for diagnosing high voltage insulation systems, forming the core of a smart PD analysis system. These new techniques will be capable of identifying the cause of discharge activities, which is an important factor in risk management and decision-making for asset managers. The development of new and improved sensing equipment and insulation diagnostics for high voltage power systems will enhance Canadian power security by contributing to the minimization of power outages and disruptions due to sudden equipment failure. These techniques will be essential to the development of a smart grid for future transmission and distribution of electric power and will support the planned rapid growth of electrification. This research will train 11 HQP, who will have advanced theoretical and hands-on training in insulation systems and will serve an essential future role in the Canadian power system industry.