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2018 | OriginalPaper | Chapter

11. Wind Power and Ramp Forecasting for Grid Integration

Authors : Cong Feng, Jie Zhang

Published in: Advanced Wind Turbine Technology

Publisher: Springer International Publishing

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Abstract

The uncertain and variable nature of the wind presents challenges to integrate wind power into the power grid, especially under extreme weather conditions. Accurate forecasts of wind power generation and extreme ramp events at different look-ahead timescales would help power systems better integrate wind power. Different models for short-term wind forecasting and ramp forecasting are reviewed and discussed in this chapter, including both individual and ensemble machine learning models and a recently developed optimized swinging door algorithm. The 1-h-ahead wind power forecasts at over 126,000 wind sites in the United States are generated using a gradient boosting machine model.

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Title: Wind Power and Ramp Forecasting for Grid Integration
Authors: Cong Feng
Jie Zhang
Publisher: Springer International Publishing
Book: Advanced Wind Turbine Technology
Print ISBN: 978-3-319-78165-5

Electronic ISBN: 978-3-319-78166-2

Copyright Year: 2018
DOI: https://doi.org/10.1007/978-3-319-78166-2_11