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When studying for a doctoral degree (PhD), candidates submit a thesis that provides a critical review of the current state of knowledge of the thesis subject as well as the student’s own contributions to the subject. The distinguishing criterion of doctoral graduate research is a significant and original contribution to knowledge.
Once accepted, the candidate presents the thesis orally. This oral exam is open to the public.
A significant share of the total primary energy belongs to buildings. In many buildings, improving energy performance of buildings is of particular importance in new construction and existing buildings. Building refurbishment is considered a practical pathway towards energy efficiency as the replacement of older buildings is at a slow pace. There are various ways of incorporating energy conservation measures in buildings through refurbishment projects. In doing so, we have to choose among various passive or active measures. The energy usage can be significantly reduced by adopting passive strategies. These methods might not need additional capital investment. An integrated building renovation approach, in which passive methods are implemented, can reduce the energy consumption of building, compensating the additional cost of new technologies. This thesis aims at developing an integrated assessment-optimization framework to provide a decision support for prioritization and selection of building refurbishment measures with energy conservation potentials by considering the cost uncertainty.
Firstly, a literature review is carried out to ascertain the state of the art in the retrofit decisions in buildings at the presence of several decision criteria. possible and available passive measures are investigated and identified based on four energy control principles. Secondly, the analytic network process (ANP) is reviewed as a multiple criteria decision-making method capable of incorporating the interdependencies among decision criteria to arrive at an overall assessment (relative scores) for alternative retrofit measures. Simultaneously, fuzzy theory is explored to incorporate uncertainty of the initial cost of materials by using three methods including graded mean integration, aggregate approach and interval approach. Then, the scores resulted from the assessment phase and the result derived from the fuzzy step, will be fed into a multi-objective optimization model. Former results are formulated a utility objective function to be maximized alongside the latter results which are formed cost objective functions that are minimized. There are three, well-known developed methods to optimize multi-objective models with conflicting objectives comprising distance to ideal, compromise programming and goal programming. These methods are used to solve optimization problem by considering linear and integer programming. The applicability of the proposed three-stage assessment-optimization approach under uncertainty is then illustrated through the case study of a typical building in order to verify its applicability and usefulness and the solution scenarios are explored and compared The proposed framework can assist decision makers in choosing the best passive measures in the planning phase of the building refurbishment addressing the complexities arising from multiplicity of feasible measures and their varied characteristics.Finally, in terms of the impact of the above research, it worth mentioning that 40% of final energy is used in buildings and the use of passive measures as a means of refurbishment for building stocks could create significant energy efficiency gains.