Ontology based decision support in urban energy planning / eingereicht von Najd Ouhajjou, MSc
VerfasserOuhajjou, Najd
Begutachter / BegutachterinTjoa, A Min
ErschienenWien 21. Dezember 2016
Umfangxix, 191 Seiten : Illustrationen, Diagramme, Karten
HochschulschriftTechnische Universität Wien, Univ., Dissertation, 2016
Zusammenfassung in deutscher Sprache
Bibl. ReferenzOeBB
Schlagwörter (EN)urban energy planning / planning support / decision support / energy systems modeling / ontologies
URNurn:nbn:at:at-ubtuw:1-1935 Persistent Identifier (URN)
 Das Werk ist frei verfügbar
Ontology based decision support in urban energy planning [24.48 mb]
Zusammenfassung (Englisch)

Cities are emitting worldwide around 70% of all greenhouse gas emissions. To reduce this large share, cities aim to develop energy strategies, implemented as a set of measures to mitigate energy demand and ensure a sustainable energy supply for the built environment. Thus, adequate IT tools are required to support the urban energy planning processes. However, developers of such tools i.e. modellers of complex urban energy system face four main challenges: (i) Supporting the perspectives of different involved stakeholders (i.e. targeted information supply). (ii) Quantifying the impact of developed strategies and simplifying the presentation of their impact (so that it is understood by all the stakeholders). (iii) Integrating of the measures that compose the strategy, also in terms of stakeholders-implication. (iv) Ensuring the replicability of the system in different cities that have different data availabilities or stakeholders. This dissertation addresses the problem in an incremental approach, where an ontology is progressively developed. Measures to be implemented are defined. Stakeholders that each measure involves are identified, and questions they raise for their decision making are listed, as competency questions of the ontology. Computation models to answer these questions are identified (to be potentially reused) or developed, taking into consideration the data availability in the city. The semantics used in these models are then captured and classified within the ontology. Then, the decision-making-knowledge of the stakeholders is integrated within the ontology. Finally, the ontology is used through a web-map-based interface. The proposed solution anticipates the potential decisions of the different stakeholders, easing the progress of the energy planning process, typically happening in workshops or forums in collaboration with different stakeholders. The approach has been applied to develop a planning support system that supports two measures: solar photovoltaics planning and building refurbishment planning. The system has been applied and tested in a district (4th District) in the city of Vienna.