Production of a Numerical Icing Atlas for Finland

Abstract

Ice on wind turbine blades reduces efficiency and causes financial loss to energy companies. Thus, it is important to know the possible risk of icing already in the planning phase of a wind park. This paper presents a new Finnish Icing Atlas and the methodology behind it and is prepared by applying the mesoscale numerical weather prediction model AROME with 2.5 km horizontal resolution and an ice growth model based on ISO 12494. The same meteorological dataset is used as was used in the Finnish Wind Atlas (published in 2009), and thus is fully compatible with and comparable with existing climatological wind resource estimations. Representation of the selected time period is evaluated from an icing point of view. Comparing reanalysed temperature and humidity datasets for both the past 20 years and the wind atlas period, we conclude that the used time period represents large-scale atmospheric conditions favourable for icing. We perform a series of sensitivity tests to evaluate how sensitive this ice model is to input from the weather model. The new atlas presents climatological distributions of active and passive icing periods and wind power production loss in map form for three different heights (50, 100 and 200 m) over all of Finland. The results show that the risk for active icing is much greater in coastal areas, while the risk of passive icing is larger inland.

Heavy snow loads in Finnish forests respond regionally asymmetrically to projected climate change

“…While the resolution of our wind speed data was coarser compared to other variables, these deficiencies overruled each other in this study and possibly led to more a realistic simulation of rime loads in northern Finland. We further note that the heaviest rime loads were modelled over approximately the same areas which were recognised to be most susceptible for losses in wind energy production in Finland due to icing (Hämäläinen and Niemelä, 2016).…”

Evaluating atmospheric icing forecasts with ground‐based ceilometer profiles

“…Originally this model was designed for high‐voltage power lines, hence the choice of diameter, and the results can be used directly for electricity cables. Our previous studies on wind turbine icing (Turkia et al ., 2013; Hämäläinen and Niemelä, 2017) also show that icing intensities > 10 g·hr −1 begin to affect wind turbine blade aerodynamics and cause power loss.…”

“…Furthermore, the icing model includes important internal parameters related to the assumed droplet size distribution. The cloud droplet particle concentration (Nd) was set to 100 (cm −3 ) (Hämäläinen and Niemelä, 2017) and the droplet median volume diameter (MVD) is defined in terms of a Gaussian distribution of the LWC as a function of the Nd.…”

“…The sensitivity tests showed that the choice of icing intensity threshold was the dominant factor in defining icing events from the model output. Previous studies (Hämäläinen and Niemelä, 2017) have shown that if the icing intensity is > 10 g·hr −1 , it impacts wind power production and aviation safety (RAYTHEON, 1999). Since the ceilometer is very sensitive to the presence of any liquid water in the atmosphere (Vaisala, 2020) and detects clouds with a wide range of liquid water content (e.g.…”

“…When forecasting for aviation or wind energy production purposes, on–off or instantaneous icing intensity information are typically sufficient. However, in estimating products such as wind energy potential, more detailed information on ice accumulation over a longer period of time is needed (Hämäläinen and Niemelä, 2017).…”