Multivariate statistical modelling and monitoring of smart buildings

• Autores: Llorenç Burgas Nadal
• Directores de la Tesis: Joan Colomer Llinás (dir. tes.), Joaquim Meléndez Frigola (codir. tes.)
• Lectura: En la Universitat de Girona ( España ) en 2019
• Idioma: español
• Tribunal Calificador de la Tesis: Richard Chbeir (presid.), Magda Ruiz Ordóñez (secret.), Mohammad Ali Fotouhi Ghazvin (voc.)
• Programa de doctorado: Programa de Doctorado en Tecnología por la Universidad de Girona
• Materias:
  • Ciencias tecnológicas
    • Tecnología e ingeniería mecánicas
• Enlaces
  • Tesis en acceso abierto en: TDX
• Resumen

  • In order to reduce mismatches between real and expected consumption, this thesis explores the use of PCA (Principal Component Analysis) as a modelling tool for buildings. PCA is a statistical technique that allows complex systems to be modelled, and, subsequently, to monitor them to detect abnormal behaviours with respect to the conditions initially modelled. The work in this thesis includes adapting PCA to take full advantage of its potential in buildings. Such adaption is also verified by applying it to various use cases.