Improved wind speed forecasts can help urban : vimarsana.com

Researchers at Concordia University present a new wind speed forecasting model that they say can help urban microgrids plan and manage electricity generation. Navid Shirzadi Ph.D. used data from a Weibull probability distribution and numerical weather prediction models and fed it into a recurrent neural network. He says his model improves forecasting by over 30 percent over a 48-horizon.

Related Keywords

Montreal , Quebec , Canada , Germany , Canadian , Pilar Monsalvete , Anton Kaifel , Ursula Eicker , Ramanunni Menon , Fuzhan Nasiri , Recurrent Neural Networks , Gina Cody School Of Engineering , Centre For Solar Energy , Department Of Building , International Energy Agency , Hydrogen Research In Stuttgart , Canada Excellence Research , Agency Institutional Program Secretariat , Concordia University , Method Of Research , Generation Cities Institute , Environmental Engineering , Gina Cody School , Computer Science , Navid Shirzadi , Long Short Term Memory , Next Generation Cities Institute , Net Zero Emissions , Canada Excellence Research Chair , Resilient Cities , Solar Energy , Hydrogen Research , Tri Agency Institutional Program , Urban Wind Power Forecasting , Integrating Weibull Distribution , Numerical Weather ,