Forecasting and Mathematical Modeling for Renewable Energy: 2023-2026

Wind and solar energy are expected to be the primary sources of electricity in the future world. Both wind and solar power are stochastic and intermittent as they are weather driven. The main purpose of this CRG is to develop meso, submeso and micro scale forecast methods for wind and solar power and create quantitative tools to support a wide range of decision-making problems related to design and operation of the wind and solar power systems and their integration to the power grid and electricity markets.



  • Adam Monahan, University of Victoria
  • Ayse Deniz Sezer, University of Calgary
  • David Wood, University of Calgary
  • Slim Ibrahim, University of Victoria


This CRG is envisioned as a platform to create long term collaborations among a diverse group of scientists and engineers including mathematicians, statisticians, experts on wind and solar energy, meteorology, atmospheric sciences, fluid dynamics and power system engineers. Key topics include but are not limited to: Spatio-temporal processes, atmospheric boundary layer, hierarchical Bayesian models, optimization, computational and theoretical fluid dynamics, power system control and design, stochastic modeling and analysis of wind and solar energy market data, machine learning.