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TitleEmerging technologies of short-term wind power forecasting
LicencePlease note the adoption of the Open Government Licence - Canada supersedes any previous licences.
AuthorChang, L
Source 2022, 54 pages, Open Access logo Open Access
PublisherNatural Resources Canada
Mediadigital; on-line
File formatpdf
SubjectsNature and Environment; Science and Technology; energy resources; energy; Wind energy; Wind
ProgramEnergy Innovation Program
Released2022 03 15; 2023 05 15
Due to the increasing energy demand and pressing environmental issues, wind energy as one of the fastest growing renewable energy sources of electricity in Canada has been significantly developed in recent years. However, due to the natural variability of wind, the integration of wind energy into electrical power systems is challenging. Variable and fluctuating wind power causes numerous problems in power quality, system stability, and energy dispatch. These problems become more severe as the penetration level of wind energy increases. Therefore, the demand for accurate and reliable wind power forecasts has continued to grow in the electric power industry. Utilities, system operators and regional transmission organizations become increasingly reliant on these forecasts to efficiently operate power systems with large wind power penetrations. Accordingly, the University of New Brunswick (UNB) was contracted by Natural Resources Canada (NRCan) to conduct a project on development and validation of advanced and integrated wind forecasting methods, aiming for applications in utilities and wind farms. The main objectives of this project are:
To evaluate and improve short term wind forecasts from the Environment Canada (EC) wind forecast model;
To develop and implement icing forecasting methods using the EC's forecasting model;
To develop and test a wind ramp forecasting algorithm that can be combined with the EC wind forecast model to form a comprehensive wind forecasting package; and
To study the benefit of bulk energy storage for wind plant operation to alleviate residual forecast error and uncertainty.
In accordance with these objectives, all required research tasks including data collection and acquisition, assessment of EC wind forecasting model, assessment of wind power production based on EC wind forecast model, development of icing forecasting model, development of wind power ramp forecasting method, study of bulk energy storage for wind plant operation, an interim report detailing the methodology and approach for the wind power forecasting technologies, and development, assessment and demonstrations of an integrated wind power forecasting package have been successfully completed in this project by March 31, 2022. This white paper primarily focuses on the short-term wind power production forecast and wind power ramp forecast, providing a review of the state-of-the-art of forecasting methods, detailing the methodologies and performance of wind forecasting technologies developed by the UNB team during this project, and discussing on challenges and opportunities of wind forecast in future grid operation.
Summary(Plain Language Summary, not published)
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.

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