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High wind penetration in an agent-based model of the electricity market

Author

Listed:
  • Eric Guerci
  • Alessandro Sapio

    (DISAE - PARTHENOPE - Università degli Studi di Napoli “Parthenope” = University of Naples)

Abstract

In this paper, we build a realistic large-scale agent-based model of the Italian electricity market and run simulations to investigate how a significant increase in wind capacity can affect electricity prices at the national level when the wind resource is geographically concentrated, as in the case of Italy. The simulator implements both cost-based and oligopoly models in which electricity companies learn to bid strategically. We compare a scenario based on the 2010 wind supply and a scenario based on the maximum potential wind capacity as estimated in technical reports. Results confirm the beneficial effect of low-cost renewable energy in reducing average market prices, but simulated power flows in the grid suggest that congestion in the electricity network induced by high wind penetration creates market power opportunities that can offset the price reduction effects.

Suggested Citation

  • Eric Guerci & Alessandro Sapio, 2012. "High wind penetration in an agent-based model of the electricity market," Post-Print halshs-00871036, HAL.
    • Handle: RePEc:hal:journl:halshs-00871036
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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. Jean-Luc Gaffard & Mauro Napoletano, 2012. "Improving the toolbox. New advances in Agent-based and Computational Models," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(5), pages 7-13.
    3. repec:hal:spmain:info:hdl:2441/5qr7f0k4sk8rbq4do5u6v70rm0 is not listed on IDEAS
    4. Sapio, Alessandro & Spagnolo, Nicola, 2020. "The effect of a new power cable on energy prices volatility spillovers," Energy Policy, Elsevier, vol. 144(C).
    5. Sapio, Alessandro, 2019. "Greener, more integrated, and less volatile? A quantile regression analysis of Italian wholesale electricity prices," Energy Policy, Elsevier, vol. 126(C), pages 452-469.
    6. Jean-Luc Gaffard & Mauro Napoletano, 2012. "Introduction - Improving the Toolbox: New Advances in Agent-Based and Computational Models," Post-Print hal-01053562, HAL.
    7. repec:hal:spmain:info:hdl:2441/1nlv566svi86iqtetenms15tc4 is not listed on IDEAS
    8. Sirin, Selahattin Murat & Yilmaz, Berna N., 2020. "Variable renewable energy technologies in the Turkish electricity market: Quantile regression analysis of the merit-order effect," Energy Policy, Elsevier, vol. 144(C).
    9. De Siano, Rita & Sapio, Alessandro, 2022. "Spatial merit order effects of renewables in the Italian power exchange," Energy Economics, Elsevier, vol. 108(C).
    10. James Wesley Burnett & Xueting Zhao, 2017. "Spatially Explicit Prediction of Wholesale Electricity Prices," International Regional Science Review, , vol. 40(2), pages 99-140, March.
    11. Sapio, Alessandro, 2015. "The effects of renewables in space and time: A regime switching model of the Italian power price," Energy Policy, Elsevier, vol. 85(C), pages 487-499.
    12. repec:hal:spmain:info:hdl:2441/53r60a8s3kup1vc9l564k4686 is not listed on IDEAS
    13. Browne, Oliver & Poletti, Stephen & Young, David, 2015. "How does market power affect the impact of large scale wind investment in 'energy only' wholesale electricity markets?," Energy Policy, Elsevier, vol. 87(C), pages 17-27.
    14. Sapio, Alessandro & Spagnolo, Nicola, 2016. "Price regimes in an energy island: Tacit collusion vs. cost and network explanations," Energy Economics, Elsevier, vol. 55(C), pages 157-172.

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