Integrated Energy and Environmental Modeling to Design Cost-Effective Building Solutions at a Regional Level
This study introduces a computationally efficient urban building energy model (UBEM) to assess decarbonization strategies for the residential sector at the regional level. The model considers a range of inputs, including building characteristics, climate data, technology penetration, and occupant be...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-11-01
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| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/17/22/5730 |
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| Summary: | This study introduces a computationally efficient urban building energy model (UBEM) to assess decarbonization strategies for the residential sector at the regional level. The model considers a range of inputs, including building characteristics, climate data, technology penetration, and occupant behavior. The model provides an economic analysis associating emission reduction potential with economic returns through an abatement cost curve, which is critical to designing cost-effective solutions. The model was validated at its full scale in Portugal, using actual consumption data from all municipalities. Key findings showed that lighting upgrades (100% LEDs) are the most cost-effective measure, offering the lowest abatement cost (−521 EUR/tonCO<sub>2</sub>eq) and a low discounted payback period of 2 years, while heat pumps for water heating provide the highest emission reduction potential, with an annual reduction of 863 tonnes of CO<sub>2</sub>eq annually, equivalent to a 20% reduction in national emissions. Additionally, behavioral measures achieved an annual reduction of 147 tonnes of CO<sub>2</sub>eq. The analysis further reveals that, while some measures might have a negative abatement cost at the national level, their economic viability varies locally, with certain municipalities incurring positive abatement costs, highlighting how local context affects the economic viability of decarbonization strategies. |
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| ISSN: | 1996-1073 |