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Balancing Power in Sweden Using Different Renewable Resources, Varying Prices, and Storages Like Batteries in a Resilient Energy System

Author

Listed:
  • Erik Dahlquist

    (School of Business, Society and Engineering, Malardalen University, 722 20 Västerås, Sweden)

  • Fredrik Wallin

    (School of Business, Society and Engineering, Malardalen University, 722 20 Västerås, Sweden)

  • Koteshwar Chirumalla

    (School of Business, Society and Engineering, Malardalen University, 722 20 Västerås, Sweden)

  • Reza Toorajipour

    (School of Business, Society and Engineering, Malardalen University, 722 20 Västerås, Sweden)

  • Glenn Johansson

    (School of Business, Society and Engineering, Malardalen University, 722 20 Västerås, Sweden
    Department of Design Sciences, Lund University, 221 00 Lund, Sweden)

Abstract

In this paper, balancing electricity production using renewable energy such as wind power, PV cells, hydropower, and CHP (combined heat and power) with biomass is carried out in relation to electricity consumption in primarily one major region in Sweden, SE-3, which contains 75% of the country’s population. The time perspective is hours and days. Statistics with respect to power production and consumption are analyzed and used as input for power-balance calculations. How long periods are with low or high production, as well as the energy for charge and discharge that is needed to maintain a generally constant power production, is analyzed. One conclusion is that if the difference in production were to be completely covered with battery capacity it would be expensive, but if a large part of the difference were met by a shifting load it would be possible to cover the rest with battery storage in an economical way. To enhance the economy with battery storage, second-life batteries are proposed to reduce the capital cost in particular. Batteries are compared to hydrogen as an energy carrier. The efficiency of a battery system is higher than that of hydrogen plus fuel cells, but in general much fewer precious materials are needed with an H 2 /fuel-cell system than with batteries. The paper discusses how to make the energy system more robust and resilient.

Suggested Citation

  • Erik Dahlquist & Fredrik Wallin & Koteshwar Chirumalla & Reza Toorajipour & Glenn Johansson, 2023. "Balancing Power in Sweden Using Different Renewable Resources, Varying Prices, and Storages Like Batteries in a Resilient Energy System," Energies, MDPI, vol. 16(12), pages 1-28, June.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:12:p:4734-:d:1172048
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    References listed on IDEAS

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    1. Zhang, Xingxing & Lovati, Marco & Vigna, Ilaria & Widén, Joakim & Han, Mengjie & Gal, Csilla & Feng, Tao, 2018. "A review of urban energy systems at building cluster level incorporating renewable-energy-source (RES) envelope solutions," Applied Energy, Elsevier, vol. 230(C), pages 1034-1056.
    2. Elkadeem, M.R. & Younes, Ali & Sharshir, Swellam W. & Campana, Pietro Elia & Wang, Shaorong, 2021. "Sustainable siting and design optimization of hybrid renewable energy system: A geospatial multi-criteria analysis," Applied Energy, Elsevier, vol. 295(C).
    3. Monika Topel & Josefine Grundius, 2020. "Load Management Strategies to Increase Electric Vehicle Penetration—Case Study on a Local Distribution Network in Stockholm," Energies, MDPI, vol. 13(18), pages 1-16, September.
    4. Jelica, D. & Taljegard, M. & Thorson, L. & Johnsson, F., 2018. "Hourly electricity demand from an electric road system – A Swedish case study," Applied Energy, Elsevier, vol. 228(C), pages 141-148.
    5. Nycander, Elis & Söder, Lennart & Olauson, Jon & Eriksson, Robert, 2020. "Curtailment analysis for the Nordic power system considering transmission capacity, inertia limits and generation flexibility," Renewable Energy, Elsevier, vol. 152(C), pages 942-960.
    6. Räsänen, Teemu & Voukantsis, Dimitrios & Niska, Harri & Karatzas, Kostas & Kolehmainen, Mikko, 2010. "Data-based method for creating electricity use load profiles using large amount of customer-specific hourly measured electricity use data," Applied Energy, Elsevier, vol. 87(11), pages 3538-3545, November.
    7. Henning, Dag & Trygg, Louise, 2008. "Reduction of electricity use in Swedish industry and its impact on national power supply and European CO2 emissions," Energy Policy, Elsevier, vol. 36(7), pages 2330-2350, July.
    8. Andersen, F.M. & Larsen, H.V. & Gaardestrup, R.B., 2013. "Long term forecasting of hourly electricity consumption in local areas in Denmark," Applied Energy, Elsevier, vol. 110(C), pages 147-162.
    9. Kipping, A. & Trømborg, E., 2015. "Hourly electricity consumption in Norwegian households – Assessing the impacts of different heating systems," Energy, Elsevier, vol. 93(P1), pages 655-671.
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