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Published in:
Research on Wind Speed Vertical Extrapolation Based on Extreme Learning Machine Read chapter Read first chapter

2017 | OriginalPaper | Chapter

Optimal Scheduling of Wind Turbine Generator Units Based on the Amount of Damage of Impeller

Authors : Kai Lin, Guochu Chen

Published in: Advanced Computational Methods in Energy, Power, Electric Vehicles, and Their Integration

Publisher: Springer Singapore

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Abstract

Impeller (blade and wheel) is one of the key components of wind turbine. According to different degrees of leaf and root damage and hub damage amount, a multi-objective scheduling model of wind farm with wind turbine impeller damage, wind turbine startup rate, and the uncertainty of the output of generator is established to improve the model output allocation strategy. Then optimize the model with the adaptive discrete particle swarm (ADPSO) and artificial bee colony algorithm (ABC), then obtaining the target power value and start-stop group. In combination with the practical example, the simulation results show that the proposed method optimizes the start-up and shut-down times of the wind turbines and improves the operating life of the wind turbines.

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previous chapter Research on Wind Speed Vertical Extrapolation Based on Extreme Learning Machine
next chapter A Short Term Wind Speed Forecasting Method Using Signal Decomposition and Extreme Learning Machine
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Metadata
Title
Optimal Scheduling of Wind Turbine Generator Units Based on the Amount of Damage of Impeller
Authors
Kai Lin
Guochu Chen
Copyright Year
2017
Publisher
Springer Singapore
Book
Advanced Computational Methods in Energy, Power, Electric Vehicles, and Their Integration

Print ISBN: 978-981-10-6363-3

Electronic ISBN: 978-981-10-6364-0

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-981-10-6364-0_2

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