Vaisala is predicting that wind energy performance is expected to remain below normal in most regions into the fourth quarter (Q4). The company said earlier this year there were record low wind anomalies that challenged many wind operators, and due to a persistent El Niño that is forecast to remain in effect throughout the end of the year wind production will be lower than average.
The wind forecast anticipates that power producers in the Northeast, Northwest, and much of the U.S. wind belt will see below average wind speeds in Q4 2015. While the El Niño pattern largely has a negative impact, particularly along the Rocky Mountains, it will have a positive impact in some areas with significant wind generation according to the report.
However, the analysis finds the Southwest, Southeast, Indiana, and southern Texas should see above normal wind speeds. California is an especially bright spot with a high likelihood of elevated wind speeds, which should signal a return to smooth profitability for investors following the lows of the last six months.
“For managing portfolio risk, it is imperative to have a detailed understanding of how over or underperformance at each of your project sites fits within the historical record,” said Dr. Jim McCaa, manager of advanced applications at Vaisala. “As acquisition and merger activity increases, the industry also needs to start thinking strategically about the variability of the assets they are looking to buy and how they fit within the existing portfolio.”
Vaisala has been following the evolution of North American wind anomalies in particular detail since the release of its Q1 study revealing 40-year record low wind speeds. The low wind event caused significant reductions in generation for utilities and project owners, a number of whom reported expected shortfalls in quarterly and annual wind production.
The company’s forecast is based on the wide agreement of the atmospheric research community and all the major global weather models that the current El Niño climate signal will continue through the end of the year. The forecast was created using an ensemble approach blending mesoscale model predictions with three of the leading reanalysis datasets, each representing 35 years of climate data.