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Optimization of annual energy demand in office buildings under the influence of climate change in Chile

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  • Rubio-Bellido, Carlos
  • Pérez-Fargallo, Alexis
  • Pulido-Arcas, Jesús A.

Abstract

Numerous studies about climate change have emerged in recent years because of their potential impact on many activities of human life, amongst which, the building sector is no exception. Changes in climate conditions have a direct influence on the external conditions for buildings and, thus, on their energy demand. In this context, computer aided simulation provides handy tools that help in assessing this impact. This paper investigates climate data for future scenarios and the effect on energy demand in office buildings in Chile. This data has been generated in the 9 climatic zones that are representative of the main inhabited areas, for the years 2020, 2050 and 2080. Predictions have been produced for the acknowledged A2 ‘medium-high’ Greenhouse Gases emissions GHG scenario, pursuant the Intergovernmental Panel on Climate Change (IPCC). The effect of climate change on the energy demand for office buildings is optimized by implementing the calculation procedure of ISO-13790:2008, based on iterations of its envelope and form. As a result, this research clarifies how future climate scenarios will affect the energy demand for different types of office buildings in Chile, and how their shape and enclosure can be optimized.

Suggested Citation

  • Rubio-Bellido, Carlos & Pérez-Fargallo, Alexis & Pulido-Arcas, Jesús A., 2016. "Optimization of annual energy demand in office buildings under the influence of climate change in Chile," Energy, Elsevier, vol. 114(C), pages 569-585.
    • Handle: RePEc:eee:energy:v:114:y:2016:i:c:p:569-585
    DOI: 10.1016/j.energy.2016.08.021
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    References listed on IDEAS

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    Cited by:

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    5. Marta Videras Rodríguez & Antonio Sánchez Cordero & Sergio Gómez Melgar & José Manuel Andújar Márquez, 2020. "Impact of Global Warming in Subtropical Climate Buildings: Future Trends and Mitigation Strategies," Energies, MDPI, vol. 13(23), pages 1-22, November.
    6. Pérez-Andreu, Víctor & Aparicio-Fernández, Carolina & Martínez-Ibernón, Ana & Vivancos, José-Luis, 2018. "Impact of climate change on heating and cooling energy demand in a residential building in a Mediterranean climate," Energy, Elsevier, vol. 165(PA), pages 63-74.
    7. Li, Xiaoma & Zhou, Yuyu & Yu, Sha & Jia, Gensuo & Li, Huidong & Li, Wenliang, 2019. "Urban heat island impacts on building energy consumption: A review of approaches and findings," Energy, Elsevier, vol. 174(C), pages 407-419.
    8. Naga Venkata Sai Kumar Manapragada & Anoop Kumar Shukla & Gloria Pignatta & Komali Yenneti & Deepika Shetty & Bibhu Kalyan Nayak & Venkataramana Boorla, 2022. "Development of the Indian Future Weather File Generator Based on Representative Concentration Pathways," Sustainability, MDPI, vol. 14(22), pages 1-17, November.
    9. Zheng, Yuanfan & Weng, Qihao, 2019. "Modeling the effect of climate change on building energy demand in Los Angeles county by using a GIS-based high spatial- and temporal-resolution approach," Energy, Elsevier, vol. 176(C), pages 641-655.
    10. Pérez-Fargallo, Alexis & Rubio-Bellido, Carlos & Pulido-Arcas, Jesús A. & Javier Guevara-García, Fco., 2018. "Fuel Poverty Potential Risk Index in the context of climate change in Chile," Energy Policy, Elsevier, vol. 113(C), pages 157-170.
    11. Lucía Pereira-Ruchansky & Alexis Pérez-Fargallo, 2020. "Integrated Analysis of Energy Saving and Thermal Comfort of Retrofits in Social Housing under Climate Change Influence in Uruguay," Sustainability, MDPI, vol. 12(11), pages 1-22, June.
    12. David Bienvenido-Huertas & Juan Antonio Fernández Quiñones & Juan Moyano & Carlos E. Rodríguez-Jiménez, 2018. "Patents Analysis of Thermal Bridges in Slab Fronts and Their Effect on Energy Demand," Energies, MDPI, vol. 11(9), pages 1-18, August.
    13. Larrea-Sáez, Lorena & Muñoz, Enrique & Cuevas, Cristian & Casas-Ledón, Yannay, 2024. "Optimizing insulation and heating systems for social housing in Chile: Insights for sustainable energy policies," Energy, Elsevier, vol. 290(C).
    14. Tettey, Uniben Yao Ayikoe & Dodoo, Ambrose & Gustavsson, Leif, 2017. "Energy use implications of different design strategies for multi-storey residential buildings under future climates," Energy, Elsevier, vol. 138(C), pages 846-860.
    15. David Bienvenido-Huertas, 2020. "Assessing the Environmental Impact of Thermal Transmittance Tests Performed in Façades of Existing Buildings: The Case of Spain," Sustainability, MDPI, vol. 12(15), pages 1-18, August.
    16. Pino-Mejías, Rafael & Pérez-Fargallo, Alexis & Rubio-Bellido, Carlos & Pulido-Arcas, Jesús A., 2017. "Comparison of linear regression and artificial neural networks models to predict heating and cooling energy demand, energy consumption and CO2 emissions," Energy, Elsevier, vol. 118(C), pages 24-36.
    17. Daniel Sánchez-García & David Bienvenido-Huertas & Mónica Tristancho-Carvajal & Carlos Rubio-Bellido, 2019. "Adaptive Comfort Control Implemented Model (ACCIM) for Energy Consumption Predictions in Dwellings under Current and Future Climate Conditions: A Case Study Located in Spain," Energies, MDPI, vol. 12(8), pages 1-22, April.
    18. Krstić-Furundžić, Aleksandra & Vujošević, Milica & Petrovski, Aleksandar, 2019. "Energy and environmental performance of the office building facade scenarios," Energy, Elsevier, vol. 183(C), pages 437-447.
    19. Pino-Mejías, Rafael & Pérez-Fargallo, Alexis & Rubio-Bellido, Carlos & Pulido-Arcas, Jesús A., 2018. "Artificial neural networks and linear regression prediction models for social housing allocation: Fuel Poverty Potential Risk Index," Energy, Elsevier, vol. 164(C), pages 627-641.

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