Climate risks for wind energy production

Among renewable sources, wind energy emerges as a vital solution due to its relatively low cost of production, small physical footprint and near-zero carbon emissions during operation. While wind energy currently contributes only to ~6% of Canada’s electricity production, the growing demand for renewable energy, and uncertainty in future hydropower production, mark wind energy as a vital source for achieving Canada’s carbon reduction targets.

However, wind resources are highly variable across temporal and spatial scales, with these fluctuations expected to intensify under climate change, posing significant challenges to the reliability and consistency of this energy source. This project introduces multiple innovations to address these challenges, from identifying optimal wind farm sites to enhancing operational practices related to wind energy production. For example, it would be ideal for a wind production site to have a stable prevailing wind. In addition, higher wind does not necessarily mean higher wind energy, as wind turbines work only within an operational range: there needs to be enough wind speed for turbines to be able to operate (> 4 m/s), but not too much either (< 25 to 30 m/s), or the turbines shut down to avoid damage. When assessing the potential for power generation at a site, it is important to understand how often the wind speed at the prevailing wind direction falls within the operational range.

But the wind direction data is sparse in many publicly available in-situ climate data; in addition, wind turbines are operating way above in-situ stations which measure the near surface wind. Moreover, given the existing heightened climate variability and change, it is important to assess the feasibility of the production facilities under future climate and to support the operation of wind farms with a short-term weather prediction system at a fine temporal and spatial scales.

The main aim of this project, whose full title is Assessing Climate Risks to Wind Energy Production in Canada and Québec, is to address the gaps in historical in-situ wind data and available modeling technologies for projecting and predicting wind using a number of innovations that enables (1) identifying ideal sites for power production based on historical climate, (2) determining challenges and opportunities for Canadian wind power production under climate change, and (3) informing operation of wind farm by providing improved short-term forecasts. It will be the first Canadian study to put these three aspects in one integrated project.

A key scientific contribution will be the identification of the causes driving variations in wind speed and direction, attributing them to natural climate variability and anthropogenic climate change. This will deepen our understanding of climate dynamics and their influence on wind production. Current wind projections are at coarse spatiotemporal resolutions, not readily available for decision-making. The project will develop new methodologies and algorithms for spatiotemporal downscaling of wind speed and direction under changing climate, which improves long-term planning for wind energy production. In addition, the development of new ML/AI (Machine Learning / Artificial Intelligence) algorithms will enhance wind forecasting at fine temporal and spatial resolutions, boosting the operational efficiency of wind energy facilities. Elmira Hassanzadeh, principal investigator, focuses in her research on enhancing understanding, evaluating, and representing climate change impact on key variables—covering hydroclimatic elements such as precipitation and floods, as well as heatwaves and sea level. In the project team, she is seconded by Julie Carreau (Polytechnique), a climate and hydrology specialist with growing expertise on deep learning methods, and Ali Nazemi (Concordia University), a hydroclimatology and mathematical modeling expert involved in developing new algorithms and methodologies for diagnosing, describing and assessing climate-related variability and change. The interdisciplinary collaboration between these researchers will enhance technological transfer to the broader community, ensuring that advancements made in this project are accessible and applicable.