Background, Description, Delivery and Learning Objective: As part of a collaboration project with Natural Resources Canada, the Meteorological Service of Canada (MSC) is working on improving ramp and icings forecasts for wind and solar energy. The more accurate and reliable those forecasts will be, the more efficient will the integration of renewables and associated energy storage solutions become. To this effect, 2.5 km resolution gridded forecasts over the Gaspé peninsula and the Maritimes, as well as 1km resolution forecasts over a smaller area, are run 4 times a day, where wind and radiation variables are output every 3 minutes to better predict the onset and end of ramps. High-resolution icing gridded forecasts are also produced. These baseline forecasts are made available freely to the public through a WMS server analog to the MSC’s GeoMet API for geospatial web services, where they can be visualized. Python scripts are also made available to facilitate the extraction of the actual forecasts. With such scripts, users can access time series of variables at the location of their choice without the need to download large and process large files themselves.
This is a first step towards making more forecast products available on many grids in Canada where wind and solar energy installations are or planned to be located. In doing so, high quality baseline high-resolution (in time and space) forecasts adapted to renewable energies are becoming available to the small companies, the public as well communities that would not have the means to hire consultant firms to produce such detailed forecasts.
We will present the range of forecasts available and how to visualize them, and we will demonstrate how Python scripts can be used to extract these data.
By attending this session, individuals, communities and small companies will become aware of the availability of free baseline forecasts from the Meteorological Service of Canada adapted to renewable energies like wind and solar, and about how to easily visualize and extract these forecasts using scripts. These products can be used to help them forecast the production of their renewable energy installations.
