Estimation of Uncertainty of Wind Energy Predictions: With Application to Weather Routing and Wind Power Generation by David ZastrauEstimation of Uncertainty of Wind Energy Predictions: With Application to Weather Routing and Wind Power Generation by David Zastrau

Estimation of Uncertainty of Wind Energy Predictions: With Application to Weather Routing and Wind…

byDavid Zastrau

Hardcover | March 7, 2017

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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.

David Zastrau studied Computer Science at the University of Bremen where he received his PhD. He researches artificial intelligence, maritime logistics, as well as weather and wave forecast accuracy.
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Title:Estimation of Uncertainty of Wind Energy Predictions: With Application to Weather Routing and Wind…Format:HardcoverDimensions:8.5 × 6 × 0.3 inPublished:March 7, 2017Publisher:Peter Lang GmbH, Internationaler Verlag der WissenschaftenLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:3631718853

ISBN - 13:9783631718858

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Table of Contents

Uncertainty in Wind Power Generation and Weather Routing – Offshore Wind Power Logistics – Weather Routing – Ship Propulsion Energy – Wind Propulsion Systems – Statistical Pattern matching – Uncertainty in Weather Predictions – Estimation of Prediction Uncertainty – Prediction Intervals – Ensemble Prediction Systems – Quantile Regression – Local Energy Distribution Moments