Managing Powerline Distribution Networks: From Conventional Methods to Digital Twin

Electricity is a pivotal sector that prioritizes reliability and safety within power systems. Traditional power network monitoring evolved with integration of sensors and satellite/aerial imagery. Nevertheless, persistent threats due to unpredictable environment changes and suboptimal maintenance are causing power outages. Simultaneously, advancements in AI enabled comprehensive analysis of inspection data, yet current approaches struggle to proactively evaluate surrounding risks. Consequently, we propose leveraging digital-twin (DT) to revolutionize powerline monitoring and response to outages. By creating virtual replicas of physical assets and integrating simulations/real data, DTs offer unparalleled insights into operational response efficiency to outages. However, applying DTs to overhead powerline monitoring remains underexplored. Here, we focus on deploying DTs to monitor and analyze overhead powerline environment. We aim to provide accurate short- and medium-term predictions of outages and responses. Hence, we proactively identify the risks and enhance the infrastructure’s resilience and sustainability, particularly in the face of climate change.

Faculty Supervisor:

Wael Jaafar;Rami Langar

Student:

Partner:

Hydro-Quebec

Discipline:

Computer science

Sector:

Construction and infrastructure; Professional, scientific and technical services; Utilities

University:

École de technologie supérieure

Program: