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Sustainable Energy: What, Why, and How? Read chapter Read first chapter

2019 | OriginalPaper | Chapter

Advances in Wind Power Forecasting

Authors : Madison E. Dittner, Ahmad Vasel

Published in: Advances in Sustainable Energy

Publisher: Springer International Publishing

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Abstract

Wind is a force of nature and naturally changes speed and direction with time, so the amount of wind power generation from wind farms also varies. Rapid growth in wind power production has led to the integration of wind power into the power grid. Wind power forecasting enables wind farms to address the intermittency and predictability issues to a satisfactory extent and to participate in the electricity market in the same way as any other power supplier. This chapter provides an overview of existing wind power forecasting methods, their time scales (short term, medium term, and long term), and most popular statistical analyses used to assess their performance. Models reviewed in this chapter include persistence method, physical models, statistical methods, machine learning methods, and hybrid methods.

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previous chapter A Review of Wind Energy Resource Assessment in the Urban Environment
next chapter Lean Energy Buildings: Applications of Machine Learning, Optimal Central Chilled-Water Systems, and Hybrid Solar-Ground Source Heat Pump Systems
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Metadata
Title
Advances in Wind Power Forecasting
Authors
Madison E. Dittner
Ahmad Vasel
Copyright Year
2019
Book
Advances in Sustainable Energy

Print ISBN: 978-3-030-05635-3

Electronic ISBN: 978-3-030-05636-0

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-05636-0_3