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Big Data Analysis of Power Market Energy Economics

In: Big Data in Energy Economics

Author

Listed:
  • Hui Liu

    (Central South University)

  • Nikolaos Nikitas

    (University of Leeds)

  • Yanfei Li

    (Hunan Agricultural University)

  • Rui Yang

    (Central South University)

Abstract

The correlation between energy consumption and national economic growth is analyzed in this chapter. At the same time, in view of the existing problems in the city electricity price, the city electricity price metering charge adjustment scheme is put forward. Finally, the feasibility of the method is verified by experiments, and the experimental results are summarized. Compared with empirical mode decomposition and wavelet packet decomposition, the Empirical Wavelet Transform (EWT) decomposition algorithm can better identify and extract the features of complex electricity price data. The Long Short-Term Memory (LSTM) network is outstanding in the application of electricity price prediction, and its performance is better than that of deep belief network and extreme learning machine. The combined model of EWT and LSTM has high prediction accuracy and good robustness. Grey correlation analysis is used to analyze the relationship between energy consumption and national economy. Through the establishment of grey correlation model, the experiment shows that, different industries and different energy types have different correlations with China's economic growth. In terms of metering and charging of urban electricity prices, cluster analysis based on K-means algorithm is carried out to divide different electricity consumption groups and optimize the residential ladder electricity price.

Suggested Citation

  • Hui Liu & Nikolaos Nikitas & Yanfei Li & Rui Yang, 2022. "Big Data Analysis of Power Market Energy Economics," Management for Professionals, in: Big Data in Energy Economics, chapter 0, pages 137-168, Springer.
    • Handle: RePEc:spr:mgmchp:978-981-16-8965-9_6
    DOI: 10.1007/978-981-16-8965-9_6
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    Cited by:

    1. Bożena Gajdzik & Magdalena Jaciow & Radosław Wolniak & Robert Wolny & Wieslaw Wes Grebski, 2024. "Diagnosis of the Development of Energy Cooperatives in Poland—A Case Study of a Renewable Energy Cooperative in the Upper Silesian Region," Energies, MDPI, vol. 17(3), pages 1-27, January.

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