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Estimation of Uncertainty of Wind Energy Predictions

With Application to Weather Routing and Wind Power Generation

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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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6. Implementation

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Abstract: Chapter 5 introduced quantile regression and new regressors for a linear quantile regression model to estimate the uncertainty of weather-dependent energy predictions with prediction intervals. This chapter describes the implementation of the quantile model in GNU R and the Java implementation of a A* weather routing application. The integration of the prediction intervals into the weather routing application is also described.

Contents

6.1. Database with historical weather predictions

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