An agile heating and cooling energy demand model for residential buildings. Case study in a mediterranean city residential sector
[EN] Climate Change will affect people¿s health, especially in cities. Hence, Energy Planning will play a key role in the development of sustainable and resilient cities. Urban Building Energy Models facilitate energy planning as heating and cooling demand becomes known, and the consequences of diff...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2023 |
| País: | España |
| Institución: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglés |
| OAI Identifier: | oai:riunet.upv.es:10251/204234 |
| Acceso en línea: | https://riunet.upv.es/handle/10251/204234 |
| Access Level: | acceso abierto |
| Palabra clave: | Buildings thermal demand 3D GIS Urban energy planning Heating and Cooling Retrofitting Climate change impact MAQUINAS Y MOTORES TERMICOS PROYECTOS DE INGENIERIA 07.- Asegurar el acceso a energías asequibles, fiables, sostenibles y modernas para todos 11.- Conseguir que las ciudades y los asentamientos humanos sean inclusivos, seguros, resilientes y sostenibles 13.- Tomar medidas urgentes para combatir el cambio climático y sus efectos |
| Sumario: | [EN] Climate Change will affect people¿s health, especially in cities. Hence, Energy Planning will play a key role in the development of sustainable and resilient cities. Urban Building Energy Models facilitate energy planning as heating and cooling demand becomes known, and the consequences of different planning actions can be modelled. This research presents an agile heating and cooling demand model. It combines an European standard¿s methodology, geometric information of buildings collected from cadastral and altimetric datasets using GIS-based technologies, solar irradiation analysis and the degree-days method. The model is validated with various case studies and then applied to several buildings in different environments. The models show the strong influence of the building¿s age (design and materials) and the building surface-to-volume ratio on the energy demand, and the importance of the solar irradiation analysis. Furthermore, the model allows us to predict the effects of the temperature rise on energy demand; or to prioritize the buildings to be retrofitted. Indeed, the model achieves the goal that advanced retrofitting of 17% of the most energy demanding buildings would obtain a 50% decrease in thermal demand; if the percentage was 50%, an 85% reduction could be reached. In conclusion, the energy planning tool hereby presented enables us to viably foresee the energy demand of residential buildings and districts and the effects of climate change on their energy demand, as well as the consequences of countermeasures like retrofitting. |
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