Long-term forecasting of peak demand, electric vehicles and distributed energy resources

Initially, a multivariate regression model provided a system-wide base forecast. A Monte-Carlo simulation was used to account for variability from weather and economic conditions. Historical trends were analyzed to forecast how changes in system peak load would affect the non-coincident TS bus peaks. Four additional scenarios were overlaid onto the TS bus forecast: data centres, electric vehicles, conservation and demand management, and distributed energy resources.

The analysis led to a comprehensive load forecasting model that predicts peak load growth across the utility’s service area at both the bus-level and system-wide. Ultimately, this model equipped the utility with capacity planning insights to meet the electricity demands of Ontario’s residents and businesses over the next 25 years.