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Probabilistic forecasting of wind power production losses in cold climates: a case study

The problem of icing on wind turbines in cold climates is addressed using probabilistic forecasting to improve next-day forecasts of icing and related production losses. A case study of probabilistic forecasts was generated for a 2-week period. Uncertainties in initial and boundary conditions are re...

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Published in:Wind Energy Science 2018, Vol.3 (2), p.667-680
Main Authors: Molinder, Jennie, Körnich, Heiner, Olsson, Esbjörn, Bergström, Hans, Sjöblom, Anna
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container_title Wind Energy Science
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creator Molinder, Jennie
Körnich, Heiner
Olsson, Esbjörn
Bergström, Hans
Sjöblom, Anna
description The problem of icing on wind turbines in cold climates is addressed using probabilistic forecasting to improve next-day forecasts of icing and related production losses. A case study of probabilistic forecasts was generated for a 2-week period. Uncertainties in initial and boundary conditions are represented with an ensemble forecasting system, while uncertainties in the spatial representation are included with a neighbourhood method. Using probabilistic forecasting instead of one single forecast was shown to improve the forecast skill of the ice-related production loss forecasts and hence the icing forecasts. The spread of the multiple forecasts can be used as an estimate of the forecast uncertainty and of the likelihood for icing and severe production losses. Best results, both in terms of forecast skill and forecasted uncertainty, were achieved using both the ensemble forecast and the neighbourhood method combined. This demonstrates that the application of probabilistic forecasting for wind power in cold climates can be valuable when planning next-day energy production, in the usage of de-icing systems and for site safety.
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subjects Boundary conditions
Case studies
Climate
ensemble prediction
Forecasting
Maintenance management
Meteorologi
Meteorology
precipitation
Renewable energy
strategy
Turbines
wet snow
Wind power
title Probabilistic forecasting of wind power production losses in cold climates: a case study
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