Stochastic model-based assessment of power systems subject to extreme wind power fluctuation
| Autor: | Kenji Kashima, Kaito Ito, Masakazu Kato, Yoshito Ohta |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
0209 industrial biotechnology
Work (thermodynamics) Wind power business.industry Stochastic modelling Computer science 020208 electrical & electronic engineering stochastic systems linearization 02 engineering and technology Extreme events renewable energy Stable distribution Renewable energy Electric power system 020901 industrial engineering & automation stable distribution Linearization Control theory Outlier 0202 electrical engineering electronic engineering information engineering business |
| Zdroj: | SICE Journal of Control, Measurement, and System Integration. 14(1):67-77 |
| ISSN: | 1882-4889 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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