Local energy system design support using a renewable energy mix multi-objective optimization model and a co-creative optimization process
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DOI: 10.1016/j.renene.2019.11.089
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- Gul, Eid & Baldinelli, Giorgio & Bartocci, Pietro & Shamim, Tariq & Domenighini, Piergiovanni & Cotana, Franco & Wang, Jinwen & Fantozzi, Francesco & Bianchi, Francesco, 2023. "Transition toward net zero emissions - Integration and optimization of renewable energy sources: Solar, hydro, and biomass with the local grid station in central Italy," Renewable Energy, Elsevier, vol. 207(C), pages 672-686.
- Mayer, Martin János & Biró, Bence & Szücs, Botond & Aszódi, Attila, 2023. "Probabilistic modeling of future electricity systems with high renewable energy penetration using machine learning," Applied Energy, Elsevier, vol. 336(C).
- Amita Singh & Jannicke Baalsrud Hauge & Magnus Wiktorsson, 2021. "Simulation-Based Participatory Modelling in Urban and Production Logistics: A Review on Advances and Trends," Sustainability, MDPI, vol. 14(1), pages 1-21, December.
- Horasan, Muhammed Bilal & Kilic, Huseyin Selcuk, 2022. "A multi-objective decision-making model for renewable energy planning: The case of Turkey," Renewable Energy, Elsevier, vol. 193(C), pages 484-504.
- Khrisydel Rhea M. Supapo & Lorafe Lozano & Ian Dominic F. Tabañag & Edward M. Querikiol, 2022. "A Backcasting Analysis toward a 100% Renewable Energy Transition by 2040 for Off-Grid Islands," Energies, MDPI, vol. 15(13), pages 1-19, June.
- Karaaslan, Abdulkerim & Gezen, Mesliha, 2022. "The evaluation of renewable energy resources in Turkey by integer multi-objective selection problem with interval coefficient," Renewable Energy, Elsevier, vol. 182(C), pages 842-854.
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Keywords
Local energy system; Co-creative design; Renewable energy mix; Multi-objective optimization; Participatory; Backcasting;All these keywords.
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