00000nam 2200000zi 4500 9.921329 CaOODSP 20240215151205 m o d f cr mn||||||||| 230328t20222023onca ob f000 0 eng d 9780660482095 CaOODSP eng rda CaOODSP M154-154/2024E-PDF Chang, Liuchen, 1960- author. 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. [Ottawa] : Natural Resources Canada = Ressources naturelles Canada, 2022. ©2023 1 online resource (53, that is, 52 pages) : illustrations (chiefly colour) text txt rdacontent computer c rdamedia online resource cr rdacarrier "March 15, 2022." Includes bibliographical references (pages 49-52). "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. Wind forecasting Mathematical models. Wind power Forecasting. Vents Prévision Modèles mathématiques. Énergie éolienne Prévision. Canada. Natural Resources Canada, issuing body. CanmetENERGY (Canada), issuing body. Technologies émergentes de prévision d'énergie éolienne à court terme. (CaOODSP)9.921331 PDF 3.54 MB https://publications.gc.ca/collections/collection_2024/rncan-nrcan/M154-154-2024-eng.pdf HTML N/A https://doi.org/10.4095/331672