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Evaluating rotational inertia as a component of grid reliability with high penetrations of variable renewable energy

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  • Johnson, Samuel C.
  • Papageorgiou, Dimitri J.
  • Mallapragada, Dharik S.
  • Deetjen, Thomas A.
  • Rhodes, Joshua D.
  • Webber, Michael E.

Abstract

Growth of electricity generation from variable renewable resources like wind and solar has raised questions about future grid stability. This paper used several renewable energy penetration scenarios to determine when an electric grid might be more vulnerable to frequency contingencies, such as a generator outage. Unit commitment and dispatch modeling was used to quantify system inertia, an established proxy for grid stability. A case study of the Electric Reliability Council of Texas grid was used to illustrate the method. Results from the modeled scenarios showed that the Texas grid is resilient to major grid changes, even with relatively high penetrations (∼30% of annual energy generation compared to 18% in 2017) of renewable energy. However, retiring nuclear power plants and private-use networks in the model led to unstable inertia levels in our results. When the system inertia was constrained to meet a minimum threshold in our model, multiple coal and natural gas combined-cycle plants were dispatched at part-load or at their minimum operating level to maintain stable system inertia levels. This behavior is expected to expand with higher renewable energy penetrations and could occur on other electric grids that are reliant on synchronous generators for inertia support.

Suggested Citation

  • Johnson, Samuel C. & Papageorgiou, Dimitri J. & Mallapragada, Dharik S. & Deetjen, Thomas A. & Rhodes, Joshua D. & Webber, Michael E., 2019. "Evaluating rotational inertia as a component of grid reliability with high penetrations of variable renewable energy," Energy, Elsevier, vol. 180(C), pages 258-271.
    • Handle: RePEc:eee:energy:v:180:y:2019:i:c:p:258-271
    DOI: 10.1016/j.energy.2019.04.216
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    References listed on IDEAS

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    1. Anthony Papavasiliou & Shmuel S. Oren, 2013. "Multiarea Stochastic Unit Commitment for High Wind Penetration in a Transmission Constrained Network," Operations Research, INFORMS, vol. 61(3), pages 578-592, June.
    2. Lund, Henrik & Andersen, Anders N. & Østergaard, Poul Alberg & Mathiesen, Brian Vad & Connolly, David, 2012. "From electricity smart grids to smart energy systems – A market operation based approach and understanding," Energy, Elsevier, vol. 42(1), pages 96-102.
    3. Tuohy, Aidan & Meibom, Peter & Denny, Eleanor & O'Malley, Mark, 2009. "Unit commitment for systems with significant wind penetration," MPRA Paper 34849, University Library of Munich, Germany.
    4. Deetjen, Thomas A. & Martin, Henry & Rhodes, Joshua D. & Webber, Michael E., 2018. "Modeling the optimal mix and location of wind and solar with transmission and carbon pricing considerations," Renewable Energy, Elsevier, vol. 120(C), pages 35-50.
    5. PAPAVASILIOU, Anthony & OREN, Schmuel S., 2013. "Multiarea stochastic unit commitment for high wind penetration in a transmission constrained network," LIDAM Reprints CORE 2500, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Kavvadias, K.C., 2016. "Energy price spread as a driving force for combined generation investments: A view on Europe," Energy, Elsevier, vol. 115(P3), pages 1632-1639.
    7. Denholm, Paul & Hand, Maureen, 2011. "Grid flexibility and storage required to achieve very high penetration of variable renewable electricity," Energy Policy, Elsevier, vol. 39(3), pages 1817-1830, March.
    8. Deetjen, Thomas A. & Rhodes, Joshua D. & Webber, Michael E., 2017. "The impacts of wind and solar on grid flexibility requirements in the Electric Reliability Council of Texas," Energy, Elsevier, vol. 123(C), pages 637-654.
    9. Bilgili, Mehmet & Ozbek, Arif & Sahin, Besir & Kahraman, Ali, 2015. "An overview of renewable electric power capacity and progress in new technologies in the world," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 323-334.
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