Emerging technologies of short-term wind power forecasting / prepared for Natural Resources Canada, CanmetENERGY-Ottawa ; prepared by Dr. Liuchen Chang, Professor Emeritus, University of New Brunswick. : M154-154/2024E-PDF

"The increased production of renewable wind energy is an effective decarbonization pathway to meet Canada's net-zero targets. However, due to the natural variability of wind, the integration of wind energy into electrical power systems is challenging. The main objectives of this publication is to evaluate and improve short-term wind forecasts from Environment and Climate Change Canada's wind forecasting models. Researchers developed a desktop wind forecast package which includes various wind power production forecasting functions, ramp events and forecasting and performance assessments for historical data. When compared with one of the existing reputable commercial wind forecasting service vendors, a noticeable degree of improvement of the wind forecasting performance can be found in the newly developed model"--Provided by publisher.

Lien permanent pour cette publication :
publications.gc.ca/pub?id=9.921329&sl=1

Renseignements sur la publication
Ministère/Organisme Canada. Natural Resources Canada, issuing body.
CanmetENERGY (Canada), issuing body.
Titre Emerging technologies of short-term wind power forecasting / prepared for Natural Resources Canada, CanmetENERGY-Ottawa ; prepared by Dr. Liuchen Chang, Professor Emeritus, University of New Brunswick.
Type de publication Monographie
Langue [Anglais]
Format Électronique
Document électronique
Note(s) "March 15, 2022."
Includes bibliographical references (pages 49-52).
Information sur la publication [Ottawa] : Natural Resources Canada = Ressources naturelles Canada, 2022.
©2023
Auteur / Contributeur Chang, Liuchen, 1960- author.
Description 1 online resource (53, that is, 52 pages) : illustrations (chiefly colour)
ISBN 9780660482095
Numéro de catalogue
  • M154-154/2024E-PDF
Descripteurs Wind forecasting -- Mathematical models.
Wind power -- Forecasting.
Vents -- Prévision -- Modèles mathématiques.
Énergie éolienne -- Prévision.
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