IDEAS home Printed from https://ideas.repec.org/a/spr/decfin/v44y2021i2d10.1007_s10203-021-00365-4.html
   My bibliography  Save this article

Optimal installation of renewable electricity sources: the case of Italy

Author

Listed:
  • Almendra Awerkin

    (University of Padua)

  • Tiziano Vargiolu

    (University of Padua)

Abstract

Starting from the model in Koch and Vargiolu (SIAM J Control Optim 59(4): 3068–3095, 2021), we test the real impact of current renewable installed power in the electricity price in Italy, and assess how much the renewable installation strategy which was put in place in Italy deviated from the optimal one obtained from the model in the period 2012–2018. To do so, we consider the Ornstein–Uhlenbeck (O–U) process, including an exogenous increasing process influencing the mean-reverting term, which is interpreted as the current renewable installed power. We estimate the parameters of this model by using real data of electricity prices and energy production from photovoltaic and wind power plants from the six main Italian price zones. We obtain that the model fits well the North, Central North and Sardinia zones: among these zones, the North is impacted by photovoltaic production, Sardinia by wind and the Central North does not present significant price impact. Then, we implement the solution of the singular optimal control problem of installing renewable power plants, in order to maximize the profit of selling the produced energy in the market net of installation costs. We extend the results of Koch and Vargiolu (SIAM J Control Optim 59(4): 3068–3095, 2021) to the case when no impact on power price is presented and to the case when N players can produce electricity by installing renewable power plants. To this extent, we analyze both the concepts of Pareto optima and of Nash equilibria. For this latter, we present a verification theorem in the 2-player case and an explicit characterization of a Nash equilibrium in the no-impact case. We are thus able to describe the optimal strategy and compare it with the real installation strategy that was put in place in Italy.

Suggested Citation

  • Almendra Awerkin & Tiziano Vargiolu, 2021. "Optimal installation of renewable electricity sources: the case of Italy," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 1179-1209, December.
  • Handle: RePEc:spr:decfin:v:44:y:2021:i:2:d:10.1007_s10203-021-00365-4
    DOI: 10.1007/s10203-021-00365-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10203-021-00365-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10203-021-00365-4?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Rama Cont & Xin Guo & Renyuan Xu, 2020. "Pareto Optima for a Class of Singular Control Games," Working Papers hal-03049246, HAL.
    2. Damiano Brigo & Antonio Dalessandro & Matthias Neugebauer & Fares Triki, 2008. "A Stochastic Processes Toolkit for Risk Management," Papers 0812.4210, arXiv.org.
    3. Weron, R & Bierbrauer, M & Trück, S, 2004. "Modeling electricity prices: jump diffusion and regime switching," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 336(1), pages 39-48.
    4. Dias, Luís & Gouveia, João Pedro & Lourenço, Paulo & Seixas, Júlia, 2019. "Interplay between the potential of photovoltaic systems and agricultural land use," Land Use Policy, Elsevier, vol. 81(C), pages 725-735.
    5. Helyette Geman & A. Roncoroni, 2006. "Understanding the Fine Structure of Electricity Prices," Post-Print halshs-00144198, HAL.
    6. Fred Espen Benth & Jūratė Šaltytė Benth & Steen Koekebakker, 2008. "Stochastic Modeling of Electricity and Related Markets," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 6811, January.
    7. Alvaro Cartea & Marcelo Figueroa, 2005. "Pricing in Electricity Markets: A Mean Reverting Jump Diffusion Model with Seasonality," Applied Mathematical Finance, Taylor & Francis Journals, vol. 12(4), pages 313-335.
    8. Maria B. Chiarolla & Giorgio Ferrari & Frank Riedel, 2012. "Generalized Kuhn-Tucker Conditions for N-Firm Stochastic Irreversible Investment under Limited Resources," Papers 1203.3757, arXiv.org, revised Aug 2013.
    9. Dirk Becherer & Todor Bilarev & Peter Frentrup, 2015. "Optimal Asset Liquidation with Multiplicative Transient Price Impact," Papers 1501.01892, arXiv.org, revised Apr 2017.
    10. Cartea, Álvaro & Jaimungal, Sebastian & Qin, Zhen, 2019. "Speculative trading of electricity contracts in interconnected locations," Energy Economics, Elsevier, vol. 79(C), pages 3-20.
    11. Dirk Becherer & Todor Bilarev & Peter Frentrup, 2018. "Optimal liquidation under stochastic liquidity," Finance and Stochastics, Springer, vol. 22(1), pages 39-68, January.
    12. Bruno Bosco & Lucia Parisio & Matteo Pelagatti & Fabio Baldi, 2010. "Long-run relations in european electricity prices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(5), pages 805-832.
    13. Gianfreda, Angelica & Parisio, Lucia & Pelagatti, Matteo, 2016. "Revisiting long-run relations in power markets with high RES penetration," Energy Policy, Elsevier, vol. 94(C), pages 432-445.
    14. Borovkova, Svetlana & Schmeck, Maren Diane, 2017. "Electricity price modeling with stochastic time change," Energy Economics, Elsevier, vol. 63(C), pages 51-65.
    15. repec:dau:papers:123456789/1433 is not listed on IDEAS
    16. Hélyette Geman & Andrea Roncoroni, 2006. "Understanding the Fine Structure of Electricity Prices," The Journal of Business, University of Chicago Press, vol. 79(3), pages 1225-1262, May.
    Full references (including those not matched with items on IDEAS)

    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. Koch, Torben & Vargiolu, Tiziano, 2019. "Optimal Installation of Solar Panels with Price Impact: a Solvable Singular Stochastic Control Problem," Center for Mathematical Economics Working Papers 627, Center for Mathematical Economics, Bielefeld University.
    2. Deschatre, Thomas & Féron, Olivier & Gruet, Pierre, 2021. "A survey of electricity spot and futures price models for risk management applications," Energy Economics, Elsevier, vol. 102(C).
    3. Carlo Mari & Emiliano Mari, 2021. "Gaussian clustering and jump-diffusion models of electricity prices: a deep learning analysis," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 1039-1062, December.
    4. Gianfreda, Angelica & Maranzano, Paolo & Parisio, Lucia & Pelagatti, Matteo, 2023. "Testing for integration and cointegration when time series are observed with noise," Economic Modelling, Elsevier, vol. 125(C).
    5. Mayer, Klaus & Trück, Stefan, 2018. "Electricity markets around the world," Journal of Commodity Markets, Elsevier, vol. 9(C), pages 77-100.
    6. Nowotarski, Jakub & Tomczyk, Jakub & Weron, Rafał, 2013. "Robust estimation and forecasting of the long-term seasonal component of electricity spot prices," Energy Economics, Elsevier, vol. 39(C), pages 13-27.
    7. Michel Culot & Valérie Goffin & Steve Lawford & Sébastien de Meten & Yves Smeers, 2013. "Practical stochastic modelling of electricity prices," Post-Print hal-01021603, HAL.
    8. Themistoclis Pantos & Stathis Polyzos & Aggelos Armenatzoglou & Ilias Kampouris, 2019. "Volatility Spillovers in Electricity Markets: Evidence from the United States," International Journal of Energy Economics and Policy, Econjournals, vol. 9(4), pages 131-143.
    9. Iván Blanco, Juan Ignacio Peña, and Rosa Rodriguez, 2018. "Modelling Electricity Swaps with Stochastic Forward Premium Models," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    10. Rafal Weron & Florian Ziel, 2018. "Electricity price forecasting," HSC Research Reports HSC/18/08, Hugo Steinhaus Center, Wroclaw University of Technology.
    11. Weron, Rafał, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
    12. Jakub Nowotarski & Jakub Tomczyk & Rafal Weron, 2013. "Modeling and forecasting of the long-term seasonal component of the EEX and Nord Pool spot prices," HSC Research Reports HSC/13/02, Hugo Steinhaus Center, Wroclaw University of Technology.
    13. Latini, Luca & Piccirilli, Marco & Vargiolu, Tiziano, 2019. "Mean-reverting no-arbitrage additive models for forward curves in energy markets," Energy Economics, Elsevier, vol. 79(C), pages 157-170.
    14. Coulon, Michael & Powell, Warren B. & Sircar, Ronnie, 2013. "A model for hedging load and price risk in the Texas electricity market," Energy Economics, Elsevier, vol. 40(C), pages 976-988.
    15. Chan, Kam Fong & Gray, Philip & van Campen, Bart, 2008. "A new approach to characterizing and forecasting electricity price volatility," International Journal of Forecasting, Elsevier, vol. 24(4), pages 728-743.
    16. Janczura, Joanna & Trück, Stefan & Weron, Rafał & Wolff, Rodney C., 2013. "Identifying spikes and seasonal components in electricity spot price data: A guide to robust modeling," Energy Economics, Elsevier, vol. 38(C), pages 96-110.
    17. Carlo Lucheroni, 2012. "A hybrid SETARX model for spikes in tight electricity markets," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 22(1), pages 13-49.
    18. Mari, Carlo & Cananà, Lucianna, 2012. "Markov switching of the electricity supply curve and power prices dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1481-1488.
    19. Gudkov, Nikolay & Ignatieva, Katja, 2021. "Electricity price modelling with stochastic volatility and jumps: An empirical investigation," Energy Economics, Elsevier, vol. 98(C).
    20. Rafal Weron, 2006. "Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach," HSC Books, Hugo Steinhaus Center, Wroclaw University of Technology, number hsbook0601.

    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:spr:decfin:v:44:y:2021:i:2:d:10.1007_s10203-021-00365-4. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.