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Assessing the impact of inertia and reactive power constraints in generation expansion planning

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  • Wogrin, S.
  • Tejada-Arango, D.
  • Delikaraoglou, S.
  • Botterud, A.

Abstract

On the path towards power systems with high renewable penetrations and ultimately carbon-neutral, more and more synchronous generation is being displaced by variable renewable generation that does not currently provide system inertia nor reactive power support. This could create serious issues of power system stability in the near future, and countries with high renewable penetrations such as Ireland are already facing these challenges. Therefore, this paper aims at answering the questions of whether and how explicitly including inertia and reactive power constraints in generation expansion planning would affect the optimal capacity mix of the power system of the future. Towards this end, we propose the novel Low-carbon Expansion Generation Optimization model, which explicitly accounts for: unit commitment constraints, Rate of Change of Frequency inertia requirements and virtual inertia provision, and, a second-order cone programming approximation of the AC power flow, accounting for reactive power constraints. An illustrative case study underlines that disregarding inertia and reactive power constraints in generation expansion planning can result in additional system cost, system infeasibilities, a distortion of optimal resource allocation and inability to reach established policy goals.

Suggested Citation

  • Wogrin, S. & Tejada-Arango, D. & Delikaraoglou, S. & Botterud, A., 2020. "Assessing the impact of inertia and reactive power constraints in generation expansion planning," Applied Energy, Elsevier, vol. 280(C).
    • Handle: RePEc:eee:appene:v:280:y:2020:i:c:s0306261920313842
    DOI: 10.1016/j.apenergy.2020.115925
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    Cited by:

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    2. Helistö, Niina & Kiviluoma, Juha & Morales-España, Germán & O’Dwyer, Ciara, 2021. "Impact of operational details and temporal representations on investment planning in energy systems dominated by wind and solar," Applied Energy, Elsevier, vol. 290(C).
    3. Klatzer, T. & Bachhiesl, U. & Wogrin, S. & Tomasgard, A., 2024. "Ramping up the hydrogen sector: An energy system modeling framework," Applied Energy, Elsevier, vol. 355(C).
    4. Nycander, Elis & Morales-España, Germán & Söder, Lennart, 2022. "Power-based modelling of renewable variability in dispatch models with clustered time periods," Renewable Energy, Elsevier, vol. 186(C), pages 944-956.
    5. Mao, Jiachen & Jafari, Mehdi & Botterud, Audun, 2022. "Planning low-carbon distributed power systems: Evaluating the role of energy storage," Energy, Elsevier, vol. 238(PA).
    6. Md Asaduzzaman Shobug & Nafis Ahmed Chowdhury & Md Alamgir Hossain & Mohammad J. Sanjari & Junwei Lu & Fuwen Yang, 2024. "Virtual Inertia Control for Power Electronics-Integrated Power Systems: Challenges and Prospects," Energies, MDPI, vol. 17(11), pages 1-33, June.
    7. Mejia-Ruiz, Gabriel E. & Paternina, Mario R. Arrieta & Segundo Sevilla, Felix Rafael & Korba, Petr, 2022. "Fast hierarchical coordinated controller for distributed battery energy storage systems to mitigate voltage and frequency deviations," Applied Energy, Elsevier, vol. 323(C).

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