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Towards a Net Zero-Emission Electricity Generation System by Optimizing Renewable Energy Sources and Nuclear Power Plant

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  • Mujammil Asdhiyoga Rahmanta

    (PT. PLN (Persero) Puslitbang Ketenagalistrikan (Research Institute), Jl. PLN Duren Tiga No. 102, Pancoran, Jakarta 12760, Indonesia)

  • Rahmat Adiprasetya Al Hasibi

    (Department of Electrical Engineering, Universitas Muhammadiyah Yogyakarta, Jl. Brawijaya, Kasihan, Bantul, Yogyakarta 55183, Indonesia)

  • Handrea Bernando Tambunan

    (PT. PLN (Persero) Puslitbang Ketenagalistrikan (Research Institute), Jl. PLN Duren Tiga No. 102, Pancoran, Jakarta 12760, Indonesia)

  • Ruly

    (PT. PLN (Persero) Puslitbang Ketenagalistrikan (Research Institute), Jl. PLN Duren Tiga No. 102, Pancoran, Jakarta 12760, Indonesia)

  • Agussalim Syamsuddin

    (PT. PLN (Persero) Puslitbang Ketenagalistrikan (Research Institute), Jl. PLN Duren Tiga No. 102, Pancoran, Jakarta 12760, Indonesia)

  • Indra Ardhanayudha Aditya

    (PT. PLN (Persero) Puslitbang Ketenagalistrikan (Research Institute), Jl. PLN Duren Tiga No. 102, Pancoran, Jakarta 12760, Indonesia)

  • Benny Susanto

    (PT. PLN (Persero) Puslitbang Ketenagalistrikan (Research Institute), Jl. PLN Duren Tiga No. 102, Pancoran, Jakarta 12760, Indonesia
    Department of Mechanical Engineering, University of Indonesia, Kampus UI, Depok 16424, Indonesia)

Abstract

Greenhouse gas emissions, including CO 2 emissions, are an issue in the energy sector that must be addressed urgently. The energy sector, including electricity, has been given a global aim of net zero emissions (NZE). This article examines three scenarios for reaching net-zero emissions in power supply. These scenarios are baseline, NZE1, and NZE2. The baseline scenario represents power plant capacity planning based on existing regulations in the base year. The net zero emissions consisting of the NZE1 and NZE2 scenarios aim to achieve net zero emissions by 2060. The NZE1 and NZE2 scenarios differ in the usage of nuclear power plant technology. The NZE1 scenario employs advanced costs for small modular reactors and large reactors technology, whilst the NZE2 scenario employs the low cost of small modular reactors and large reactors. The three scenarios were implemented and examined using the low emissions analysis platform software. The analytical results demonstrate that the NZE1 and NZE2 scenarios can meet the net zero emission objective by 2058. The baseline scenario results in power plant capacity planning with an average annual CO 2 emission growth rate of 3.58%. On the other hand, the baseline scenario has the lowest investment expenses, at only 44 billion USD.

Suggested Citation

  • Mujammil Asdhiyoga Rahmanta & Rahmat Adiprasetya Al Hasibi & Handrea Bernando Tambunan & Ruly & Agussalim Syamsuddin & Indra Ardhanayudha Aditya & Benny Susanto, 2024. "Towards a Net Zero-Emission Electricity Generation System by Optimizing Renewable Energy Sources and Nuclear Power Plant," Energies, MDPI, vol. 17(8), pages 1-22, April.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:8:p:1958-:d:1379186
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    References listed on IDEAS

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    1. Malka, Lorenc & Bidaj, Flamur & Kuriqi, Alban & Jaku, Aldona & Roçi, Rexhina & Gebremedhin, Alemayehu, 2023. "Energy system analysis with a focus on future energy demand projections: The case of Norway," Energy, Elsevier, vol. 272(C).
    2. Peng, Qiao & Liu, Weilong & Zhang, Yong & Zeng, Shihong & Graham, Byron, 2023. "Generation planning for power companies with hybrid production technologies under multiple renewable energy policies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 176(C).
    3. Yu, Yanghao & Du, Ershun & Chen, Zhichao & Su, Yibo & Zhang, Xianfeng & Yang, Hongbin & Wang, Peng & Zhang, Ning, 2022. "Optimal portfolio of a 100% renewable energy generation base supported by concentrating solar power," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
    4. Nian, Victor & Mignacca, Benito & Locatelli, Giorgio, 2022. "Policies toward net-zero: Benchmarking the economic competitiveness of nuclear against wind and solar energy," Applied Energy, Elsevier, vol. 320(C).
    5. Wambui, Valentine & Njoka, Francis & Muguthu, Joseph & Ndwali, Patrick, 2022. "Scenario analysis of electricity pathways in Kenya using Low Emissions Analysis Platform and the Next Energy Modeling system for optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    6. Calikoglu, Umit & Aydinalp Koksal, Merih, 2023. "A pathway to achieve the net zero emissions target for the public electricity and heat production sector: A case study for Türkiye," Energy Policy, Elsevier, vol. 179(C).
    7. Liu, Jia & Zhou, Yuekuan & Yang, Hongxing & Wu, Huijun, 2022. "Net-zero energy management and optimization of commercial building sectors with hybrid renewable energy systems integrated with energy storage of pumped hydro and hydrogen taxis," Applied Energy, Elsevier, vol. 321(C).
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