An ontology-driven method for urban building energy modeling DOI
Rui Ma, Qi Li, Botao Zhang

et al.

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 106, P. 105394 - 105394

Published: March 29, 2024

Language: Английский

Simulation-based evaluation of occupancy on energy consumption of multi-scale residential building archetypes DOI Creative Commons
Divyanshu Sood, Ibrahim Alhindawi, Usman Ali

et al.

Journal of Building Engineering, Journal Year: 2023, Volume and Issue: 75, P. 106872 - 106872

Published: May 23, 2023

Building archetypes are commonly used to identify areas with energy-inefficient buildings and estimate energy demand at different spatial scales. However, these often rely on conventional occupancy schedules, which fixed uniform throughout the year. This study proposes a new methodology that uses data from Time Use Survey (TUS) extract realistic profiles. The profiles model heat gains due along their interaction lighting heating systems. developed schedules take into account factors such as number of occupants, dwelling types, month year, day Energy simulations were conducted evaluate impact multi-scale residential building scales (postcode, county, national). results showed significantly resulting in approximately 8%–10% variations annual various compared base case. Monthly electricity consumption also 25% 32%, respectively, With more granularity, daily reported 50% 12%, case standard schedules. These highlight importance incorporating for reliable predictions temporal Occupancy-integrated can help policymakers, local authorities, urban planners make informed decisions based actual develop effective recommendations direct retrofit investment policies.

Language: Английский

Citations

23

From building energy modeling to urban building energy modeling: A review of recent research trend and simulation tools DOI
Graziano Salvalai, Yunxi Zhu, Marta Maria Sesana

et al.

Energy and Buildings, Journal Year: 2024, Volume and Issue: 319, P. 114500 - 114500

Published: July 3, 2024

Language: Английский

Citations

15

Integrated energy demand-supply modeling for low-carbon neighborhood planning DOI
Morteza Vahid‐Ghavidel, Mehdi Jafari, Samuel Letellier-Duchesne

et al.

Applied Energy, Journal Year: 2024, Volume and Issue: 358, P. 122560 - 122560

Published: Jan. 14, 2024

Language: Английский

Citations

11

Balancing construction and operational carbon emissions: Evaluating neighbourhood renovation strategies DOI Creative Commons
Javier García-López, Miguel Hernández-Valencia, Jorge Roa-Fernández

et al.

Journal of Building Engineering, Journal Year: 2024, Volume and Issue: 94, P. 109993 - 109993

Published: June 28, 2024

Compliance with the global decarbonisation commitments set out in Horizon 2050 undoubtedly involves optimising conditions of housing stock. In this respect, massive energy renovation obsolete blocks southern EU countries holds key for achievement such compliance. This research strives to demonstrate suitability intervention strategies at district scale. For purpose, an innovative methodology that combines open data, Geographic Information Systems (GIS), Urban Energy Modelling (UBEM), and Life Cycle Assessment (LCA) is proposed tested a case study, whilst considering several new-building hypotheses. As approach, study concurrently analyses greenhouse gas emissions arising from both use-related consumption (operational carbon footprint) construction process (embodied footprint). dual perspective provides added value results obtained, since it offers more comprehensive representation reality. Based on LCA UBEM models, unveils entire impact residential use combined either footprint or new buildings. The analysis reveals total emissions, encompassing embodied operational aspects, are lower retrofitting existing buildings when compared construction, up 2050. Remarkably, preference persists even as far 2100. underscores critical importance upgrading stock order achieve ambitious goal net-zero by

Language: Английский

Citations

11

An ontology-driven method for urban building energy modeling DOI
Rui Ma, Qi Li, Botao Zhang

et al.

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 106, P. 105394 - 105394

Published: March 29, 2024

Language: Английский

Citations

8