Spatio-temporal Processes for Meso and Sub-meso Scale Modeling of Wind Speed

Assoc. Prof. Ayşe Deniz Sezer

Department of Mathematics and Statistics, University of Calgary

15 August 2023 Tuesday, 14:00-15:00
B33, Merkezi Derslik A Binası, Maslak

 

Abstract:

In this talk, I am going to give an overview of various methodologies used by my research team for meso and sub-meso scale problems related to wind power. Meso scale research focuses on probabilistic modeling of wind power produced at wind farms distributed across a large geographical region such as a province to make inferences about the aggregate wind power and applications to power system planning and management. Sub-meso scale modeling involves resolving finer features of the wind flow that can affect wind production in nearby farms.

Specifically, at the meso level, I will talk about the hierarchical framework that we use to model the joint statistics of wind speed observations at multiple sites conditional on a given large scale atmospheric pattern and the highlights of various applications of this approach to Alberta specific wind data. At the sub-meso level, I will talk about modelling of vortices and their joint dynamics with the large-scale flow using stochastic differential equations.

Bio: 

Deniz Sezer holds a Ph.D. in Operations Research from Cornell University and currently is an Associate Professor in Mathematics and Statistics at the University of Calgary, Alberta, Canada. Prior to joining U Calgary, Dr. Sezer was a postdoctoral fellow at York University and the Fields Institute. Her research is in probability theory, spatio-temporal processes, and applications. Dr. Sezer’s current focus is on renewable energy applications, and she is leading a research team called MathForWind+ at the University of Calgary. Dr. Sezer is also a lead organizer for the Collaborative Research Group on Forecasting and Mathematical Modeling for Renewable Energy awarded by the Pacific Institute for the Mathematical Sciences, Canada.