The rise in global concerns over the continuous increase of greenhouse gas emissions and the increasing demand for energy, has led to an increase in the uptake of sustainable building technology products and photovoltaic (PV) systems technology. However, despite the wide adoption of PV globally as a substitute to the grid, it faces information-related challenges that hinder its adoption. The enormous volumes of information available on these technology products overwhelm intended users when acquiring valuable knowledge to make informed decisions. Similarly, information on PV is represented on the web using non-machine-processable languages that focus on describing the pattern of data rather than execution models. The semantic web and its associated technologies have become state-of-the-art solutions to such knowledge modelling, representation, and reasoning challenges. This research aims to exploit the extent to which semantic web technologies can be used for knowledge modelling in the domain of sustainable building technology products with emphasis on photovoltaic systems. This research develops a unique methodological framework to develop rich and comprehensive theoretical and conceptual knowledge models of the domain. As part of operationalizing the methodology, the research investigates the integration of semantic web with the standardised information foundation classes (IFC) for efficient knowledge discovery. This led to the development of a rich and modular ontology for the PV domain called the IfcOWL_pvOntology that extends the standard IfcOWL ontology to represent knowledge on photovoltaic systems. Consequently, this research further investigates and proposes a selection model with an algorithmic approach for sizing and selection of photovoltaic technology components involving multicriterial design parameters. Backed by mathematical computations, this process model is used alongside the IfcOWL_pvOntology to develop a successfully evaluated semantic web-based navigable prototype system that provides recommendations on choices of PV technology products to intended users. The prototype system is developed to serve as a proof-by-demonstration and a proof of the concepts established in investigating the extent to which semantic web technologies can be exploited to provide decision support in sizing and selection of PV systems to intended users. The decision to extend IFC is paramount because only continuous use can make standards advance. The proposed ontology could be adopted and approved by the buildingSMART working group in the world wide web consortium (W3C) as an official extension of IFC ontology for the photovoltaic technology domain. This prototype will be treated as part of a future large expert system where the knowledge and inference models will be used in practice in the industry to provide decision support for not only photovoltaic systems but other sustainable building technology products at large.
Permanent link to this resource: https://doi.org/10.24384/svj5-gq65
Usman, Zainab Shamsiya
Supervisors: Tah, Joseph ; Abanda, Henry ; Nche, Charles
Faculty of Technology, Design and Environment
Year: 2023
© Usman, Zainab Shamsiya Published by Oxford Brookes UniversityAll rights reserved. Copyright © and Moral Rights for this thesis are retained by the author and/or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This thesis cannot be reproduced or quoted extensively from without first obtaining permission in writing from the copyright holder(s). The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the copyright holders.