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Optimization of the possible pathways for gradual energy system decarbonization

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  • Herc, Luka
  • Pfeifer, Antun
  • Duić, Neven

Abstract

The European Union and other signatories to the Paris Climate Accord have agreed to limit global warming to 2° Celsius above pre-industrial levels. Previously published studies have examined the optimal energy system structure required to satisfy carbon neutrality end goals. This research focuses on addressing the intermediate steps towards decarbonization. The steps are quantified as the percentage share of renewable energy sources. The objective of the optimization is to reach a predetermined level of renewable energy and emissions, minimize curtailment of renewable energy sources, minimize system cost, and limit the use of natural resources such as biomass in the energy sector. Considered technologies in the optimization process are energy-generating capacities, demand response technologies, and energy storage. The results of such a method reflect the use of considered technologies and are displayed as a function of renewable energy share and carbon dioxide emissions level, which also represent the decarbonization timeline from 2020 to 2050. The method is carried out with the use of energy planning software EnergyPLAN and highly modified Python-based optimization software EPLANopt. The results presented in the research display the necessity for continuous implementation of variable generating capacities as well as demand response technologies, mainly vehicle to grid.

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  • Herc, Luka & Pfeifer, Antun & Duić, Neven, 2022. "Optimization of the possible pathways for gradual energy system decarbonization," Renewable Energy, Elsevier, vol. 193(C), pages 617-633.
  • Handle: RePEc:eee:renene:v:193:y:2022:i:c:p:617-633
    DOI: 10.1016/j.renene.2022.05.005
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    2. Jing Fan & Yanbo Yang & Tiancai Ma & Dong Zhu & Xinru Xu, 2023. "Investigation on a Shutdown Control Strategy with Residual Oxygen Rapid Elimination for Proton Exchange Membrane Fuel Cell System," Energies, MDPI, vol. 16(3), pages 1-13, January.
    3. 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).
    4. Diego Viesi & Gregorio Borelli & Silvia Ricciuti & Giovanni Pernigotto & Md Shahriar Mahbub, 2024. "Modeling the Optimal Transition of an Urban Neighborhood towards an Energy Community and a Positive Energy District," Energies, MDPI, vol. 17(16), pages 1-30, August.
    5. Zuo, Yinhui & Sun, Yigao & Zhang, Luquan & Zhang, Chao & Wang, Yingchun & Jiang, Guangzheng & Wang, Xiaoguang & Zhang, Tao & Cui, Longqing, 2024. "Geothermal resource evaluation in the Sichuan Basin and suggestions for the development and utilization of abandoned oil and gas wells," Renewable Energy, Elsevier, vol. 225(C).
    6. Kılkış, Şiir, 2023. "Integrated urban scenarios of emissions, land use efficiency and benchmarking for climate neutrality and sustainability," Energy, Elsevier, vol. 285(C).
    7. Petrucci, Andrea & Ayevide, Follivi Kloutse & Buonomano, Annamaria & Athienitis, Andreas, 2023. "Development of energy aggregators for virtual communities: The energy efficiency-flexibility nexus for demand response," Renewable Energy, Elsevier, vol. 215(C).

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