Abstract

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 measures. 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. To incorporate uncertainties in formulating the initial cost of materials, a fuzzy set approach is adopted. Then, the scores resulted from the assessment phase are formulated a utility objective function to be maximized alongside the cost objective function(s) that are minimized. The fuzzy numbers representing the cost uncertainties are incorporated into the cost objective function using alternative methods of graded mean integration, aggregate approach and interval approach. Various Solution approaches are then utilized for the multi-objective models to deal with the conflicting objectives including distance to ideal, compromise programming and goal programming. The cases of linear and integer assumptions about decision variables are investigated. 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.