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Correlations and clustering in wholesale electricity markets

Author

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  • Cui, Tianyu
  • Caravelli, Francesco
  • Ududec, Cozmin

Abstract

We study the structure of locational marginal prices in day-ahead and real-time wholesale electricity markets. In particular, we consider the case of two North American markets and show that the price correlations contain information on the locational structure of the grid. We study various clustering methods and introduce a type of correlation function based on event synchronization for spiky time series, and another based on string correlations of location names provided by the markets. This allows us to reconstruct aspects of the locational structure of the grid.

Suggested Citation

  • Cui, Tianyu & Caravelli, Francesco & Ududec, Cozmin, 2018. "Correlations and clustering in wholesale electricity markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 1507-1522.
    • Handle: RePEc:eee:phsmap:v:492:y:2018:i:c:p:1507-1522
    DOI: 10.1016/j.physa.2017.11.077
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    Citations

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    Cited by:

    1. Michel Noussan & Roberta Roberto & Benedetto Nastasi, 2018. "Performance Indicators of Electricity Generation at Country Level—The Case of Italy," Energies, MDPI, vol. 11(3), pages 1-14, March.
    2. Arcos-Vargas, A. & Nuñez, F. & Román-Collado, R., 2020. "Short-term effects of PV integration on global welfare and CO2 emissions. An application to the Iberian electricity market," Energy, Elsevier, vol. 200(C).
    3. Peter Sinka & Peter J. Zeitsch, 2022. "Hedge Effectiveness of the Credit Default Swap Indices: a Spectral Decomposition and Network Topology Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 60(4), pages 1375-1412, December.
    4. Nie, Chun-Xiao, 2019. "Applying correlation dimension to the analysis of the evolution of network structure," Chaos, Solitons & Fractals, Elsevier, vol. 123(C), pages 294-303.

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