IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0135312.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0135312
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0135312&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0135312?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. repec:hal:spmain:info:hdl:2441/1nlv566svi86iqtetenms15tc4 is not listed on IDEAS
    3. Barbour, Edward & González, Marta C., 2018. "Projecting battery adoption in the prosumer era," Applied Energy, Elsevier, vol. 215(C), pages 356-370.
    4. repec:hal:spmain:info:hdl:2441/5qr7f0k4sk8rbq4do5u6v70rm0 is not listed on IDEAS
    5. 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.
    6. 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.
    7. repec:spo:wpmain:info:hdl:2441/1nlv566svi86iqtetenms15tc4 is not listed on IDEAS
    8. 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.
    9. Florian Kuhnlenz & Pedro H. J. Nardelli, 2016. "Agent-based Model for Spot and Balancing Electricity Markets," Papers 1612.04512, arXiv.org.
    10. repec:spo:wpmain:info:hdl:2441/5qr7f0k4sk8rbq4do5u6v70rm0 is not listed on IDEAS
    11. 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.
    12. Mario Mureddu & Hildegard Meyer-Ortmanns, 2016. "Extreme prices in electricity balancing markets from an approach of statistical physics," Papers 1612.05525, arXiv.org.
    13. 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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sensfuß, Frank & Ragwitz, Mario & Genoese, Massimo & Möst, Dominik, 2007. "Agent-based simulation of electricity markets: a literature review," Working Papers "Sustainability and Innovation" S5/2007, Fraunhofer Institute for Systems and Innovation Research (ISI).
    2. Esmaeili Aliabadi, Danial & Kaya, Murat & Sahin, Guvenc, 2017. "Competition, risk and learning in electricity markets: An agent-based simulation study," Applied Energy, Elsevier, vol. 195(C), pages 1000-1011.
    3. Ning Wang & Weisheng Xu & Weihui Shao & Zhiyu Xu, 2019. "A Q-Cube Framework of Reinforcement Learning Algorithm for Continuous Double Auction among Microgrids," Energies, MDPI, vol. 12(15), pages 1-26, July.
    4. Gaivoronskaia, E. & Tsyplakov, A., 2018. "Using a Modified Erev-Roth Algorithm in an Agent-Based Electricity Market Model," Journal of the New Economic Association, New Economic Association, vol. 39(3), pages 55-83.
    5. Rahimiyan, Morteza & Rajabi Mashhadi, Habib, 2010. "Evaluating the efficiency of divestiture policy in promoting competitiveness using an analytical method and agent-based computational economics," Energy Policy, Elsevier, vol. 38(3), pages 1588-1595, March.
    6. Dawid Herbert & Gemkow Simon & Harting Philipp & Kabus Kordian & Neugart Michael & Wersching Klaus, 2008. "Skills, Innovation, and Growth: An Agent-Based Policy Analysis," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 228(2-3), pages 251-275, April.
    7. Hailu, Atakelty & Schilizzi, Steven & Thoyer, Sophie, 2005. "Assessing the performance of auctions for the allocation of conservation contracts: Theoretical and computational approaches," 2005 Annual meeting, July 24-27, Providence, RI 19478, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    8. Guerci, E. & Ivaldi, S. & Pastore, S. & Cincotti, S., 2005. "Modeling and implementation of an artificial electricity market using agent-based technology," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(1), pages 69-76.
    9. Leigh Tesfatsion, 2002. "Agent-Based Computational Economics," Computational Economics 0203001, University Library of Munich, Germany, revised 15 Aug 2002.
    10. Albert Banal-Estañol & Augusto Rupérez-Micola, 2010. "Are agent-based simulations robust? The wholesale electricity trading case," Economics Working Papers 1214, Department of Economics and Business, Universitat Pompeu Fabra.
    11. Atakelty Hailu & Sophie Thoyer, 2007. "Designing Multi‐unit Multiple Bid Auctions: An Agent‐based Computational Model of Uniform, Discriminatory and Generalised Vickrey Auctions," The Economic Record, The Economic Society of Australia, vol. 83(s1), pages 57-72, September.
    12. Eric Guerci & Stefano Ivaldi & Silvano Cincotti, 2008. "Learning Agents in an Artificial Power Exchange: Tacit Collusion, Market Power and Efficiency of Two Double-auction Mechanisms," Computational Economics, Springer;Society for Computational Economics, vol. 32(1), pages 73-98, September.
    13. Alexandre Truc & Muriel Dal Pont Legrand, 2024. "Agent-Based Models: Impact and Interdisciplinary Influences in Economics," GREDEG Working Papers 2024-19, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
    14. Manuel L. Costa & Fernando S. Oliveira, 2005. "An Evolutionary Analysis of Investment in Electricity Markets," Computing in Economics and Finance 2005 430, Society for Computational Economics.
    15. Atakelty Hailu & Sophie Thoyer, 2005. "Multi-Unit Auctions to Allocate Water Scarcity Simulating Bidding Behaviour with Agent Based Models," Others 0512012, University Library of Munich, Germany.
    16. Atakelty Hailu & Sophie Thoyer, 2010. "What Format for Multi-Unit Multiple-Bid Auctions?," Computational Economics, Springer;Society for Computational Economics, vol. 35(3), pages 189-209, March.
    17. Banal-Estañol, Albert & Rupérez Micola, Augusto, 2011. "Behavioural simulations in spot electricity markets," European Journal of Operational Research, Elsevier, vol. 214(1), pages 147-159, October.
    18. Sarıca, Kemal & Kumbaroğlu, Gürkan & Or, Ilhan, 2012. "Modeling and analysis of a decentralized electricity market: An integrated simulation/optimization approach," Energy, Elsevier, vol. 44(1), pages 830-852.
    19. Weidlich, Anke & Veit, Daniel, 2008. "A critical survey of agent-based wholesale electricity market models," Energy Economics, Elsevier, vol. 30(4), pages 1728-1759, July.
    20. Hailu, Atakelty & Schilizzi, Steven, 2003. "Investigating the performance of market-based instruments for resource conservation: the contribution of agent-based modelling," 2003 Conference (47th), February 12-14, 2003, Fremantle, Australia 57883, Australian Agricultural and Resource Economics Society.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0135312. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.