Energy Benchmarking Models for Hotel Buildings: A Case Study in Londrina, Paraná, Brazil
Room occupancy is an important variable influencing electrical energy consumption in hotel buildings. Given the randomness of this variable, energy demands fluctuate, making it challenging to develop accurate models for describing energy use patterns. This research aimed to develop energy benchmarki...
| Autores: | , , |
|---|---|
| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2024 |
| País: | Brasil |
| Institución: | Universidade Estadual de Londrina (UEL) |
| Repositorio: | Revista Semina: Ciências Exatas e Tecnológicas (Online) |
| Idioma: | inglés |
| OAI Identifier: | oai:ojs2.ojs.uel.br:article/50380 |
| Acceso en línea: | https://ojs.uel.br/revistas/uel/index.php/semexatas/article/view/50380 |
| Access Level: | acceso abierto |
| Palabra clave: | energy benchmarks energy efficiency energy indicators hotels benchmark energético eficiência energética indicadores energéticos hotéis |
| Sumario: | Room occupancy is an important variable influencing electrical energy consumption in hotel buildings. Given the randomness of this variable, energy demands fluctuate, making it challenging to develop accurate models for describing energy use patterns. This research aimed to develop energy benchmarking models for hotels. For this, five hotel buildings in Londrina, Paraná, Brazil, were used as a reference. Data were collected through questionnaires, interviews with hotel managers, site visits, and analysis of project plans. The analyzed indicators included energy use intensity per built-up area (EUI), room night (EUIRN), average room area (EUIRA), and number of rooms (EUIR). Benchmark equations were obtained by multiple linear regression. The response variables were annual energy use, EUI, EUIRA, and EUIR. Benchmarks were classified on a scale from A to E according to operational energy performance, with A being the most efficient and E the least efficient. Of the five buildings, three were categorized into the same class by the three studied models. The classes of the other two buildings varied according to the model, demonstrating the importance of choosing adequate energy performance indicators for each analysis. |
|---|