Deep-retrofit decision-making support for achieving nearly zero-energy buildings with enhanced comfort
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The emerging trends for deep-retrofit of existing buildings in Europe require formulation of strategies for nearly zero-energy buildings (nZEBs) and achieving benchmarks as outlined in the Energy Performance of Buildings Directive (EPBD) recast. The fundamental process of retrofitting to an explicit high performance (both energy and comfort) necessitates the development of robust and diverse methodologies to be used during the early-stages of planning in retrofit projects. The construction sector lacks the extensive use of such methods for early decision-making that are essential to accelerate building renovation in Europe. Therefore, considering the need to upgrade existing buildings to nZEB, the thesis aims at developing decision-making support for deep-retrofits. This research presents the application of combined (i) research techniques, (ii) audit and assessment methods, (iii) building simulation, and (iv) optimisation strategies investigated on an existing building field-study that shall support the decision-making in retrofitting existing buildings to low-energy and comfortable buildings. The overall research methodology incorporated a preliminary scoping study, including literature review and stakeholder analysis, followed by a detailed field-study, building simulation and optimisation for deep-retrofit analysis and solutions. The scoping study was designed to assess the gaps in theory through literature review and practice using surveys, a workshop and focused interviews investigating experience, knowledge, expectation, and needs of retrofit industry stakeholders in Ireland. The results of this scoping study informed the overall methodology for research in this thesis. A systematic field-study was conducted on a partially-retrofitted university building (built during 1970s) in Ireland. The different building performance metrics for energy and comfort were examined for the existing building and their optimisation opportunities were identified. Furthermore, an indoor environmental quality (IEQ) assessment was carried out using standards-based procedures and practices along with detailed energy audits and occupant surveys. The metrics of thermal, visual and acoustic comfort, together with indoor air quality (IAQ), were analysed for occupant satisfaction. This formed the basis for further investigation focusing on achieving nearly zero-energy performance with improved IEQ and led to the identification of proposed retrofit measures. The further investigation involved the development of a whole-building energy simulation models using the field-study data. A novel multi-stage automated-calibration methodology was developed to calibrate the simulation model using genetic algorithm (GA). The methodology combined a rigorous uncertainty analysis of simulation input parameters using the Morris method. The model was calibrated and validated with the energy and environmental reference datasets from the field-study meeting the acceptance criteria outlined in the standards. Furthermore, the impact of several proposed retrofit measures on energy, comfort, and cost were evaluated using the calibrated model, through multi-objective optimisation (MOO) (Pareto fronts), to explore deep-retrofit solution packages. The main objectives of the MOO were primary energy consumption (PEC), discomfort hours (DH) and net present value (NPV) of life cycle-costs (LCC). An additional analysis of IAQ was also conducted, which provided added benefits that were also taken into consideration in the proposed deep-retrofit solution packages. To validate the effectiveness of these solutions, single-step and staged-retrofit approaches were examined for their feasibility in achieving cost-optimal nZEB performance. The overall work concludes with different retrofit approaches for critical assessment tied to the main research methodology that supports the decision-making for non-domestic retrofits from the energy, cost and IEQ perspective. Multi-objective optimisation ensured robust model calibration and analysis of most optimal solutions for the decision making of deep-retrofit packages based on selected objectives. Findings of this research may (i) benefit the non-domestic deep-retrofit projects (and their stakeholders) to develop a systematic approach and processes to achieve nZEBs, (ii) provide evidence that deep-retrofit of non-domestic buildings can significantly reduce their energy consumption, (iii) strengthen and align the focus of retrofit industry on improving IEQ together with energy efficiency, (iii) inform the local legislation into setting up the nZEB benchmarks for existing buildings performance and, (iv) add to the primary case study database on non-domestic buildings outlining the deep-retrofit impact.
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