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Estimation of Uncertainty of Wind Energy Predictions

With Application to Weather Routing and Wind Power Generation


David Zastrau

Currently, a new generation of fuel-efficient ships, which use wind force in addition to conventional propulsion technology, is being developed. This study describes a mathematical method for a probabilistic estimate of the wind propulsion force on a ship route. The method is based on quantile regression, which makes it suitable for various ship routes with variable weather conditions. Furthermore, the author takes different macro weather situations into account for the calculation of the statistical distributions. He validates the results for a multi-purpose carrier, a ship route in the North Atlantic Ocean and archived weather forecasts. It showed that the wind force can be estimated more accurately if the macro weather situation is taken into account properly.

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7. Evaluation and Results


Abstract: This chapter describes the prediction intervals calculated with quantile regression for the ship propulsion energy and the travel time on the route in fig. 6.2. The prediction intervals are evaluated with respect to sharpness, reliability and the skill score. The key aspects of the evaluation are the accurateness of uncertainty estimates with the new regressors (LEDM), the impact of a WPS on prediction uncertainty and the integration of uncertainty estimates into an existing weather routing software. It is demonstrated that the prediction accuracy and the average ship propulsion energy significantly improve if the uncertainty of predictions is taken into account in the weather routing strategy.


7.1. Evaluation of prediction intervals

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