SPEAKER:
Saeed Nusri, Data Analytics Lead, Innovation Team, ATCO Electricity Global Business Unit
ABSTRACT:
Weather impacts are one of the main causes of outages. To mitigate impacts of such outages, a cascaded classification model is proposed to predict outages. It aims to allow distribution system operators to achieve more precise prediction and optimize real time operations and maintenance scheduling. The model leverages geo-specific current weather conditions and grid topology data to predict weather related cause codes across ATCO’s service territories in Alberta.
SPEAKER’s BIO:
Saeed Nusri has double major in science and engineering and has completed his Master’s from University of Alberta. He has worked with several startups in the area of e-commerce, engineering operations, and asset management and has deployed commercial Artificial Intelligence technologies that have positively impacted multi-million dollar investments. As Data Scientist and Advanced Analytics Lead with ATCO, he is currently leading analytics in the Global Electricity Business Unit Innovation Team. Some of his current work involves leveraging machine learning algorithms and big data analytics in the space of predictive maintenance, smart homes, distributed energy management, outage managements systems and energy trading.