Stochastic model-based assessment of power systems subject to extreme wind power fluctuation

被引：0

作者：

Ito K. ^{[1
]}

Kashima K. ^{[1
]}

Kato M. ^{[2
]}

Ohta Y. ^{[1
]}

机构：

[1] Graduate School of Informatics, Kyoto University, Kyoto

[2] Graduate School of Engineering, Tokyo Denki University, Tokyo

来源：

SICE Journal of Control, Measurement, and System Integration | 2021年 / 14卷 / 01期

关键词：

Extreme events; linearization; renewable energy; stable distribution; stochastic systems;

D O I：

10.1080/18824889.2021.1906017

中图分类号：

学科分类号：

摘要：

Extreme outliers of wind power fluctuation are a source of severe damage to power systems. In our previous work, we proposed a modelling framework, verified its usefulness via real data, and developed a model-based evaluation method of the impact of such extreme outliers. However, it has been a drawback that the obtained estimates of frequency fluctuation of power systems are sometimes excessively conservative for their practical use. To overcome this weakness, theory and methods for tightening the fluctuation estimates are investigated in this paper. This is done by applying a robust performance analysis method of a Lur'e system to the error analysis of stochastic linearization. The usefulness of our proposed method is shown through a load frequency control model. © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

引用

页码：67 / 77

页数：10

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