Decomposition of Fluctuating Photovoltaic Generation Power in Frequency Bands and Analysis of Chaotic Properties

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Abstract

This paper discusses chaotic properties of fluctuating photovoltaic generation (PV) power and reveals that PV power can be decomposed into a chaotic component having shorter periods and a long-term fluctuation component. The first step is to decompose the PV power into three components containing a long-term fluctuation component, a load frequency control (LFC) component, and an irregular fluctuation component from normalized PV power data by using periodic regression analysis. The second step is to analyze the long-term fluctuation component and the LFC component using autocorrelation function. The third step is to clarify the chaotic properties of the LFC component using Lyapunov spectrum analysis. Finally, the simulation of predicting the LFC component and the normalized PV power data is carried out. This simulation clarifies that the LFC component has chaotic properties.

Original languageEnglish
Pages (from-to)26-33
Number of pages8
JournalElectrical Engineering in Japan (English translation of Denki Gakkai Ronbunshi)
Volume201
Issue number4
DOIs
Publication statusPublished - Dec 1 2017

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Frequency bands
Power generation
Decomposition
Autocorrelation
Regression analysis
Spectrum analysis

Keywords

  • chaos
  • decomposition
  • nonlinear prediction
  • photovoltaic generation
  • regression analysis

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

Cite this

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title = "Decomposition of Fluctuating Photovoltaic Generation Power in Frequency Bands and Analysis of Chaotic Properties",
abstract = "This paper discusses chaotic properties of fluctuating photovoltaic generation (PV) power and reveals that PV power can be decomposed into a chaotic component having shorter periods and a long-term fluctuation component. The first step is to decompose the PV power into three components containing a long-term fluctuation component, a load frequency control (LFC) component, and an irregular fluctuation component from normalized PV power data by using periodic regression analysis. The second step is to analyze the long-term fluctuation component and the LFC component using autocorrelation function. The third step is to clarify the chaotic properties of the LFC component using Lyapunov spectrum analysis. Finally, the simulation of predicting the LFC component and the normalized PV power data is carried out. This simulation clarifies that the LFC component has chaotic properties.",
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N2 - This paper discusses chaotic properties of fluctuating photovoltaic generation (PV) power and reveals that PV power can be decomposed into a chaotic component having shorter periods and a long-term fluctuation component. The first step is to decompose the PV power into three components containing a long-term fluctuation component, a load frequency control (LFC) component, and an irregular fluctuation component from normalized PV power data by using periodic regression analysis. The second step is to analyze the long-term fluctuation component and the LFC component using autocorrelation function. The third step is to clarify the chaotic properties of the LFC component using Lyapunov spectrum analysis. Finally, the simulation of predicting the LFC component and the normalized PV power data is carried out. This simulation clarifies that the LFC component has chaotic properties.

AB - This paper discusses chaotic properties of fluctuating photovoltaic generation (PV) power and reveals that PV power can be decomposed into a chaotic component having shorter periods and a long-term fluctuation component. The first step is to decompose the PV power into three components containing a long-term fluctuation component, a load frequency control (LFC) component, and an irregular fluctuation component from normalized PV power data by using periodic regression analysis. The second step is to analyze the long-term fluctuation component and the LFC component using autocorrelation function. The third step is to clarify the chaotic properties of the LFC component using Lyapunov spectrum analysis. Finally, the simulation of predicting the LFC component and the normalized PV power data is carried out. This simulation clarifies that the LFC component has chaotic properties.

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