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Improved wind speed forecasts can help urban

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.
Pilar Monsalvete Anton Kaifel Ursula Eicker Ramanunni Menon Fuzhan Nasiri Recurrent Neural Networks

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