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Multifractal detrended fluctuation analysis for clustering structures of electricity price periods

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  • Wang, Fang
  • Liao, Gui-ping
  • Li, Jian-hui
  • Li, Xiao-chun
  • Zhou, Tie-jun

Abstract

A new model is proposed to investigate the structure of electricity price in different time periods. A popular method — the multifractal detrended fluctuation analysis (MF-DFA) method is employed to analyze the features achieved from three types of electricity price data after filtering some trends by Fourier detrended fluctuation function. Twelve multifractal parameters are calculated and selected as the characteristic indicators for comparison. Moreover, the minimum number of indicators is determined so that the discriminant accuracy reaches maximum based on Fisher’s linear discriminant algorithm (Fisher’s LDA) for each time period. These indicators form a multi-dimensional space, in which each point represents a price time series. This allows us to cluster the three price time periods, namely, the low price time periods, the average price time periods and the peak price time periods. Fisher’s LDA is employed to evaluate the discriminant accuracy on these three kinds of time periods. Our analysis is then applied to the data in California1999–2000 and PJM2001–2002 electricity markets to demonstrate the applicability of our methods.

Suggested Citation

  • Wang, Fang & Liao, Gui-ping & Li, Jian-hui & Li, Xiao-chun & Zhou, Tie-jun, 2013. "Multifractal detrended fluctuation analysis for clustering structures of electricity price periods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(22), pages 5723-5734.
    • Handle: RePEc:eee:phsmap:v:392:y:2013:i:22:p:5723-5734
    DOI: 10.1016/j.physa.2013.07.039
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    11. Olga Y. Uritskaya & Vadim M. Uritsky, 2015. "Predictability of price movements in deregulated electricity markets," Papers 1505.08117, arXiv.org.
    12. Fan, Qingju, 2016. "Asymmetric multiscale detrended fluctuation analysis of California electricity spot price," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 252-260.
    13. Uritskaya, Olga Y. & Uritsky, Vadim M., 2015. "Predictability of price movements in deregulated electricity markets," Energy Economics, Elsevier, vol. 49(C), pages 72-81.
    14. He, Xiaoli & Wang, Hongwu & Du, Ziping, 2014. "The complexity and fractal structures of CSI300 before and after the introduction of CSI300IF," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 76-85.
    15. Lahmiri, Salim & Bekiros, Stelios, 2018. "Chaos, randomness and multi-fractality in Bitcoin market," Chaos, Solitons & Fractals, Elsevier, vol. 106(C), pages 28-34.
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    17. Sierra-Porta, D. & Domínguez-Monterroza, Andy-Rafael, 2022. "Linking cosmic ray intensities to cutoff rigidity through multifractal detrented fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).

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