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Green Power Grids: How Energy from Renewable Sources Affects Networks and Markets

Author

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  • Mario Mureddu
  • Guido Caldarelli
  • Alessandro Chessa
  • Antonio Scala
  • Alfonso Damiano

Abstract

The increasing attention to environmental issues is forcing the implementation of novel energy models based on renewable sources. This is fundamentally changing the configuration of energy management and is introducing new problems that are only partly understood. In particular, renewable energies introduce fluctuations which cause an increased request for conventional energy sources to balance energy requests at short notice. In order to develop an effective usage of low-carbon sources, such fluctuations must be understood and tamed. In this paper we present a microscopic model for the description and for the forecast of short time fluctuations related to renewable sources in order to estimate their effects on the electricity market. To account for the inter-dependencies in the energy market and the physical power dispatch network, we use a statistical mechanics approach to sample stochastic perturbations in the power system and an agent based approach for the prediction of the market players’ behavior. Our model is data-driven; it builds on one-day-ahead real market transactions in order to train agents’ behaviour and allows us to deduce the market share of different energy sources. We benchmarked our approach on the Italian market, finding a good accordance with real data.

Suggested Citation

  • Mario Mureddu & Guido Caldarelli & Alessandro Chessa & Antonio Scala & Alfonso Damiano, 2015. "Green Power Grids: How Energy from Renewable Sources Affects Networks and Markets," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-15, September.
    • Handle: RePEc:plo:pone00:0135312
    DOI: 10.1371/journal.pone.0135312
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    References listed on IDEAS

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    1. James Nicolaisen & Valentin Petrov & Leigh Tesfatsion, 2000. "Market Power and Efficiency in a Computational Electricity Market with Discriminatory Double-Auction Pricing," Computational Economics 0004005, University Library of Munich, Germany.
    2. Derek W. Bunn and Fernando Oliveira, 2001. "An Application of Agent-based Simulation to the New Electricity Trading Arrangements of England and Wales," Computing in Economics and Finance 2001 93, Society for Computational Economics.
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    Citations

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    Cited by:

    1. Balint, T. & Lamperti, F. & Mandel, A. & Napoletano, M. & Roventini, A. & Sapio, A., 2017. "Complexity and the Economics of Climate Change: A Survey and a Look Forward," Ecological Economics, Elsevier, vol. 138(C), pages 252-265.
    2. Mureddu, Mario & Meyer-Ortmanns, Hildegard, 2018. "Extreme prices in electricity balancing markets from an approach of statistical physics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1324-1334.
    3. Florian Kuhnlenz & Pedro H. J. Nardelli, 2016. "Agent-based Model for Spot and Balancing Electricity Markets," Papers 1612.04512, arXiv.org.
    4. repec:hal:spmain:info:hdl:2441/1nlv566svi86iqtetenms15tc4 is not listed on IDEAS
    5. repec:spo:wpmain:info:hdl:2441/5qr7f0k4sk8rbq4do5u6v70rm0 is not listed on IDEAS
    6. Barbour, Edward & González, Marta C., 2018. "Projecting battery adoption in the prosumer era," Applied Energy, Elsevier, vol. 215(C), pages 356-370.
    7. repec:hal:spmain:info:hdl:2441/5qr7f0k4sk8rbq4do5u6v70rm0 is not listed on IDEAS
    8. Guanyi Yu & Weidong Chen & Junnan Wang & Yumeng Hu, 2022. "Research on Decision-Making for a Photovoltaic Power Generation Business Model under Integrated Energy Services," Energies, MDPI, vol. 15(15), pages 1-12, August.
    9. Scala, Antonio & Facchini, Angelo & Perna, Umberto & Basosi, Riccardo, 2019. "Portfolio analysis and geographical allocation of renewable sources: A stochastic approach," Energy Policy, Elsevier, vol. 125(C), pages 154-159.
    10. Mario Mureddu & Hildegard Meyer-Ortmanns, 2016. "Extreme prices in electricity balancing markets from an approach of statistical physics," Papers 1612.05525, arXiv.org.
    11. Hermesmann, M. & Grübel, K. & Scherotzki, L. & Müller, T.E., 2021. "Promising pathways: The geographic and energetic potential of power-to-x technologies based on regeneratively obtained hydrogen," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    12. Mahmoud M. Hussein & Mohamed Nasr Abdel Hamid & Tarek Hassan Mohamed & Ibrahim M. Al-Helal & Abdullah Alsadon & Ammar M. Hassan, 2024. "Advanced Frequency Control Technique Using GTO with Balloon Effect for Microgrids with Photovoltaic Source to Lower Harmful Emissions and Protect Environment," Sustainability, MDPI, vol. 16(2), pages 1-20, January.
    13. repec:spo:wpmain:info:hdl:2441/1nlv566svi86iqtetenms15tc4 is not listed on IDEAS

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