IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i18p10098-d632068.html
   My bibliography  Save this article

Methodology and Application of Statistical Techniques to Evaluate the Reliability of Electrical Systems Based on the Use of High Variability Generation Sources

Author

Listed:
  • César Berna-Escriche

    (Instituto Universitario de Investigación en Ingeniería Energética of the Universitat Politècnica de València (UPV), Camino de Vera s/n, 46022 Valencia, Spain)

  • Ángel Pérez-Navarro

    (Instituto Universitario de Investigación en Ingeniería Energética of the Universitat Politècnica de València (UPV), Camino de Vera s/n, 46022 Valencia, Spain)

  • Alberto Escrivá

    (Instituto Universitario de Investigación en Ingeniería Energética of the Universitat Politècnica de València (UPV), Camino de Vera s/n, 46022 Valencia, Spain)

  • Elías Hurtado

    (Instituto Universitario de Investigación en Ingeniería Energética of the Universitat Politècnica de València (UPV), Camino de Vera s/n, 46022 Valencia, Spain)

  • José Luis Muñoz-Cobo

    (Instituto Universitario de Investigación en Ingeniería Energética of the Universitat Politècnica de València (UPV), Camino de Vera s/n, 46022 Valencia, Spain)

  • María Cristina Moros

    (Instituto Universitario de Investigación en Ingeniería Energética of the Universitat Politècnica de València (UPV), Camino de Vera s/n, 46022 Valencia, Spain)

Abstract

This study presents a new methodology, based on Monte-Carlo techniques to evaluate the reliability of a carbon-free electricity generation system based on renewable sources; it uses as inputs the variation of the electricity demand and the fluctuations in the renewable supply and provides the renewable system to be installed to guarantee a specific supply reliability level. Additionally, looking for a reduction of this renewable system, the methodology determines the improvements by the incorporation of nuclear power and electricity storage. The methodology is of general application, its implementation being possible under different contexts, such as different time horizons and different future energy scenarios, both for developing, emerging, and developed countries. The only requirement is to have a sufficient database from which to make predictions for future scenarios of electrical generation–demand balances. As an example of practical implementation, the electrical system reliability for the particular case of Spain in 2040 has been forecasted. When considering the fluctuations in solar and wind power contributions, very high values of the installed power from these renewable sources are needed to reach a high reliability of the system. These values decrease substantially if contributions from nuclear and storage technologies are included.

Suggested Citation

  • César Berna-Escriche & Ángel Pérez-Navarro & Alberto Escrivá & Elías Hurtado & José Luis Muñoz-Cobo & María Cristina Moros, 2021. "Methodology and Application of Statistical Techniques to Evaluate the Reliability of Electrical Systems Based on the Use of High Variability Generation Sources," Sustainability, MDPI, vol. 13(18), pages 1-27, September.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:18:p:10098-:d:632068
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/18/10098/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/18/10098/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ingeborg Graabak & Magnus Korpås, 2016. "Variability Characteristics of European Wind and Solar Power Resources—A Review," Energies, MDPI, vol. 9(6), pages 1-31, June.
    2. Nathalie Spittler & Ganna Gladkykh & Arnaud Diemer & Brynhildur Davidsdottir, 2019. "Understanding the Current Energy Paradigm and Energy System Models for More Sustainable Energy System Development," Post-Print hal-02127724, HAL.
    3. Lazkano, Itziar & Nøstbakken, Linda & Pelli, Martino, 2017. "From fossil fuels to renewables: The role of electricity storage," European Economic Review, Elsevier, vol. 99(C), pages 113-129.
    4. Mirjat, Nayyar Hussain & Uqaili, Muhammad Aslam & Harijan, Khanji & Walasai, Gordhan Das & Mondal, Md Alam Hossain & Sahin, Hasret, 2018. "Long-term electricity demand forecast and supply side scenarios for Pakistan (2015–2050): A LEAP model application for policy analysis," Energy, Elsevier, vol. 165(PB), pages 512-526.
    5. McPherson, Madeleine & Johnson, Nils & Strubegger, Manfred, 2018. "The role of electricity storage and hydrogen technologies in enabling global low-carbon energy transitions," Applied Energy, Elsevier, vol. 216(C), pages 649-661.
    6. Huber, Matthias & Dimkova, Desislava & Hamacher, Thomas, 2014. "Integration of wind and solar power in Europe: Assessment of flexibility requirements," Energy, Elsevier, vol. 69(C), pages 236-246.
    7. Henriques, Sofia Teives & Borowiecki, Karol J., 2017. "The drivers of long-run CO2 emissions in Europe, North America and Japan since 1800," Energy Policy, Elsevier, vol. 101(C), pages 537-549.
    8. Hunter, Kevin & Sreepathi, Sarat & DeCarolis, Joseph F., 2013. "Modeling for insight using Tools for Energy Model Optimization and Analysis (Temoa)," Energy Economics, Elsevier, vol. 40(C), pages 339-349.
    9. Hong, Sanghyun & Bradshaw, Corey J.A. & Brook, Barry W., 2015. "Global zero-carbon energy pathways using viable mixes of nuclear and renewables," Applied Energy, Elsevier, vol. 143(C), pages 451-459.
    10. Hall, Lisa M.H. & Buckley, Alastair R., 2016. "A review of energy systems models in the UK: Prevalent usage and categorisation," Applied Energy, Elsevier, vol. 169(C), pages 607-628.
    11. Mike Brian Ndawula & Sasa Z. Djokic & Ignacio Hernando-Gil, 2019. "Reliability Enhancement in Power Networks under Uncertainty from Distributed Energy Resources," Energies, MDPI, vol. 12(3), pages 1-24, February.
    12. Collins, Seán & Deane, John Paul & Poncelet, Kris & Panos, Evangelos & Pietzcker, Robert C. & Delarue, Erik & Ó Gallachóir, Brian Pádraig, 2017. "Integrating short term variations of the power system into integrated energy system models: A methodological review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 839-856.
    13. Zhao, Weigang & Cao, Yunfei & Miao, Bo & Wang, Ke & Wei, Yi-Ming, 2018. "Impacts of shifting China's final energy consumption to electricity on CO2 emission reduction," Energy Economics, Elsevier, vol. 71(C), pages 359-369.
    14. Nathalie Spittler & Ganna Gladkykh & Arnaud Diemer & Brynhildur Davidsdottir, 2019. "Understanding the Current Energy Paradigm and Energy System Models for More Sustainable Energy System Development," Energies, MDPI, vol. 12(8), pages 1-22, April.
    15. Jiang, Xuemei & Guan, Dabo, 2016. "Determinants of global CO2 emissions growth," Applied Energy, Elsevier, vol. 184(C), pages 1132-1141.
    16. Xiaoyang Sun & Baosheng Zhang & Xu Tang & Benjamin C. McLellan & Mikael Höök, 2016. "Sustainable Energy Transitions in China: Renewable Options and Impacts on the Electricity System," Energies, MDPI, vol. 9(12), pages 1-20, November.
    17. Das, Anjana & Halder, Arideep & Mazumder, Rahul & Saini, Vinay Kumar & Parikh, Jyoti & Parikh, Kirit S., 2018. "Bangladesh power supply scenarios on renewables and electricity import," Energy, Elsevier, vol. 155(C), pages 651-667.
    18. Zaman, Khalid & Moemen, Mitwali Abd-el., 2017. "Energy consumption, carbon dioxide emissions and economic development: Evaluating alternative and plausible environmental hypothesis for sustainable growth," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 1119-1130.
    19. Strachan, Neil & Kannan, Ramachandran, 2008. "Hybrid modelling of long-term carbon reduction scenarios for the UK," Energy Economics, Elsevier, vol. 30(6), pages 2947-2963, November.
    20. Valentina Bosetti & Emanuele Massetti & Massimo Tavoni, 2007. "The WITCH Model. Structure, Baseline, Solutions," Working Papers 2007.10, Fondazione Eni Enrico Mattei.
    21. deLlano-Paz, Fernando & Calvo-Silvosa, Anxo & Iglesias Antelo, Susana & Soares, Isabel, 2015. "The European low-carbon mix for 2030: The role of renewable energy sources in an environmentally and socially efficient approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 49-61.
    22. Ştefan Dragoş Cîrstea & Claudia Steluţa Martiş & Andreea Cîrstea & Anca Constantinescu-Dobra & Melinda Timea Fülöp, 2018. "Current Situation and Future Perspectives of the Romanian Renewable Energy," Energies, MDPI, vol. 11(12), pages 1-22, November.
    23. Farihan Mohamad & Jiashen Teh & Ching-Ming Lai & Liang-Rui Chen, 2018. "Development of Energy Storage Systems for Power Network Reliability: A Review," Energies, MDPI, vol. 11(9), pages 1-19, August.
    24. Lund, Henrik & Østergaard, Poul Alberg & Connolly, David & Mathiesen, Brian Vad, 2017. "Smart energy and smart energy systems," Energy, Elsevier, vol. 137(C), pages 556-565.
    25. P. Capros & Denise Van Regemorter & Leonidas Paroussos & P. Karkatsoulis & C. Fragkiadakis & S. Tsani & I. Charalampidis & Tamas Revesz, 2013. "GEM-E3 Model Documentation," JRC Research Reports JRC83177, Joint Research Centre.
    26. Cany, C. & Mansilla, C. & Mathonnière, G. & da Costa, P., 2018. "Nuclear contribution to the penetration of variable renewable energy sources in a French decarbonised power mix," Energy, Elsevier, vol. 150(C), pages 544-555.
    27. Whiting, Kai & Carmona, Luis Gabriel & Sousa, Tânia, 2017. "A review of the use of exergy to evaluate the sustainability of fossil fuels and non-fuel mineral depletion," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 202-211.
    28. Weigang Zhao & Yunfei Cao & Bo Miao & Ke Wang & Yi-Ming Wei, 2018. "Impacts of shifting China¡¯s final energy consumption to electricity on CO2 emission reduction," CEEP-BIT Working Papers 115, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    29. Messner, Sabine & Schrattenholzer, Leo, 2000. "MESSAGE–MACRO: linking an energy supply model with a macroeconomic module and solving it iteratively," Energy, Elsevier, vol. 25(3), pages 267-282.
    30. Subodh Kharel & Bahman Shabani, 2018. "Hydrogen as a Long-Term Large-Scale Energy Storage Solution to Support Renewables," Energies, MDPI, vol. 11(10), pages 1-17, October.
    31. Amorim, Filipa & Pina, André & Gerbelová, Hana & Pereira da Silva, Patrícia & Vasconcelos, Jorge & Martins, Victor, 2014. "Electricity decarbonisation pathways for 2050 in Portugal: A TIMES (The Integrated MARKAL-EFOM System) based approach in closed versus open systems modelling," Energy, Elsevier, vol. 69(C), pages 104-112.
    32. Ringkjøb, Hans-Kristian & Haugan, Peter M. & Solbrekke, Ida Marie, 2018. "A review of modelling tools for energy and electricity systems with large shares of variable renewables," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 440-459.
    33. Lopion, Peter & Markewitz, Peter & Robinius, Martin & Stolten, Detlef, 2018. "A review of current challenges and trends in energy systems modeling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 156-166.
    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. Diankai Wang & Inna Gryshova & Anush Balian & Mykola Kyzym & Tetiana Salashenko & Viktoriia Khaustova & Olexandr Davidyuk, 2022. "Assessment of Power System Sustainability and Compromises between the Development Goals," Sustainability, MDPI, vol. 14(4), pages 1-23, February.
    2. César Berna-Escriche & Carlos Vargas-Salgado & David Alfonso-Solar & Alberto Escrivá-Castells, 2022. "Hydrogen Production from Surplus Electricity Generated by an Autonomous Renewable System: Scenario 2040 on Grand Canary Island, Spain," Sustainability, MDPI, vol. 14(19), pages 1-29, September.
    3. Berna-Escriche, César & Rivera, Yago & Alvarez-Piñeiro, Lucas & Muñoz-Cobo, José Luis, 2024. "Best estimate plus uncertainty methodology for forecasting electrical balances in isolated grids: The decarbonized Canary Islands by 2040," Energy, Elsevier, vol. 294(C).
    4. Carlos Vargas-Salgado & César Berna-Escriche & Alberto Escrivá-Castells & Dácil Díaz-Bello, 2022. "Optimization of All-Renewable Generation Mix According to Different Demand Response Scenarios to Cover All the Electricity Demand Forecast by 2040: The Case of the Grand Canary Island," Sustainability, MDPI, vol. 14(3), pages 1-29, February.

    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. Berna-Escriche, César & Rivera, Yago & Alvarez-Piñeiro, Lucas & Muñoz-Cobo, José Luis, 2024. "Best estimate plus uncertainty methodology for forecasting electrical balances in isolated grids: The decarbonized Canary Islands by 2040," Energy, Elsevier, vol. 294(C).
    2. Østergaard, P.A. & Lund, H. & Thellufsen, J.Z. & Sorknæs, P. & Mathiesen, B.V., 2022. "Review and validation of EnergyPLAN," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    3. Yoro, Kelvin O. & Daramola, Michael O. & Sekoai, Patrick T. & Wilson, Uwemedimo N. & Eterigho-Ikelegbe, Orevaoghene, 2021. "Update on current approaches, challenges, and prospects of modeling and simulation in renewable and sustainable energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    4. Plazas-Niño, F.A. & Ortiz-Pimiento, N.R. & Montes-Páez, E.G., 2022. "National energy system optimization modelling for decarbonization pathways analysis: A systematic literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    5. Charlotte Senkpiel & Audrey Dobbins & Christina Kockel & Jan Steinbach & Ulrich Fahl & Farina Wille & Joachim Globisch & Sandra Wassermann & Bert Droste-Franke & Wolfgang Hauser & Claudia Hofer & Lars, 2020. "Integrating Methods and Empirical Findings from Social and Behavioural Sciences into Energy System Models—Motivation and Possible Approaches," Energies, MDPI, vol. 13(18), pages 1-30, September.
    6. Martínez-Gordón, R. & Morales-España, G. & Sijm, J. & Faaij, A.P.C., 2021. "A review of the role of spatial resolution in energy systems modelling: Lessons learned and applicability to the North Sea region," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    7. Felder, F.A. & Kumar, P., 2021. "A review of existing deep decarbonization models and their potential in policymaking," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    8. Sacha Hodencq & Mathieu Brugeron & Jaume Fitó & Lou Morriet & Benoit Delinchant & Frédéric Wurtz, 2021. "OMEGAlpes, an Open-Source Optimisation Model Generation Tool to Support Energy Stakeholders at District Scale," Energies, MDPI, vol. 14(18), pages 1-30, September.
    9. Yazdanie, M. & Orehounig, K., 2021. "Advancing urban energy system planning and modeling approaches: Gaps and solutions in perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    10. Nathalie Spittler & Ganna Gladkykh & Arnaud Diemer & Brynhildur Davidsdottir, 2019. "Understanding the Current Energy Paradigm and Energy System Models for More Sustainable Energy System Development," Energies, MDPI, vol. 12(8), pages 1-22, April.
    11. Klemm, Christian & Vennemann, Peter, 2021. "Modeling and optimization of multi-energy systems in mixed-use districts: A review of existing methods and approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    12. Fattahi, A. & Sijm, J. & Faaij, A., 2020. "A systemic approach to analyze integrated energy system modeling tools: A review of national models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    13. Md. Nasimul Islam Maruf, 2019. "Sector Coupling in the North Sea Region—A Review on the Energy System Modelling Perspective," Energies, MDPI, vol. 12(22), pages 1-35, November.
    14. David Huckebrink & Valentin Bertsch, 2021. "Integrating Behavioural Aspects in Energy System Modelling—A Review," Energies, MDPI, vol. 14(15), pages 1-26, July.
    15. Gils, Hans Christian & Gardian, Hedda & Kittel, Martin & Schill, Wolf-Peter & Zerrahn, Alexander & Murmann, Alexander & Launer, Jann & Fehler, Alexander & Gaumnitz, Felix & van Ouwerkerk, Jonas & Bußa, 2022. "Modeling flexibility in energy systems — comparison of power sector models based on simplified test cases," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    16. Chen, Huayi & Ma, Tieju, 2021. "Technology adoption and carbon emissions with dynamic trading among heterogeneous agents," Energy Economics, Elsevier, vol. 99(C).
    17. Chang, Miguel & Lund, Henrik & Thellufsen, Jakob Zinck & Østergaard, Poul Alberg, 2023. "Perspectives on purpose-driven coupling of energy system models," Energy, Elsevier, vol. 265(C).
    18. Dagoumas, Athanasios S. & Koltsaklis, Nikolaos E., 2019. "Review of models for integrating renewable energy in the generation expansion planning," Applied Energy, Elsevier, vol. 242(C), pages 1573-1587.
    19. Gyanwali, Khem & Komiyama, Ryoichi & Fujii, Yasumasa, 2020. "Representing hydropower in the dynamic power sector model and assessing clean energy deployment in the power generation mix of Nepal," Energy, Elsevier, vol. 202(C).
    20. Maximilian Hoffmann & Leander Kotzur & Detlef Stolten & Martin Robinius, 2020. "A Review on Time Series Aggregation Methods for Energy System Models," Energies, MDPI, vol. 13(3), pages 1-61, February.

    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:gam:jsusta:v:13:y:2021:i:18:p:10098-:d:632068. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.