The role of the energy performance modelling with a view to low energy buildings

Climate change requires courageous choices, the European Union has accepted this challenge. One of the 2050 European low-carbon targets is energy savings in the building sector which is responsible for around 40% of energy consumption and 36% of CO2 emissions in the EU. The role of Building Performance Simulation (BPS) is central in that it allows to improve the design, optimization, construction, operation and maintenance of new and existing buildings. In order to achieve the correct estimate of energy consumption of buildings, different models have been developed in the last decades. They can be grouped into three categories: black box models, gray box models and white box models. They are differentiated by the degree of detail with which they describe the physical phenomena that govern the calculation of energy performance instead of using statistical algorithms for the estimation of the same or some characteristics of the building. However, the most detailed models are still only a representation of reality and therefore with margins of error due to assumptions and approximations of calculation. These aspects could be critical in the estimation of energy performance of nearly Zero Energy Buildings (nZEBs) where low performance values could become comparable with errors in estimating energy performances themselves. nZEBs are currently not diffuse in the EU building stock, however are those on which Europe is pointing as a key to building renewal. This thesis aims to investigate the role of energy performance modelling of buildings with low energy consumption. For this reason, research fields of BPS are identified in which the energy performance modelling has been used. They are: climatic data versus energy performance, energy performance rating and ranking of buildings, definition of minimum building requirements and exploring of technologies and valuation methods of energy efficiency measures. For having a wider vision on which model can be used, with what simplifications and what expectations, a research was carried out for each application field. Numerical models are applied both to single buildings and to building stocks, but first ones are the main focus of the investigation. Concerning the first application field, in order to estimate the energy performance (EP) of buildings which have a very low amount of energy covered to a very significant extent by energy from renewable sources accurate and reliable climatic data are necessary. The analysis of EP estimated with different calculation methods shows that the sources of climate data currently available lead to results which can be very different from each other. An improved Typical Meteorological Year construction procedure is proposed to higher the reliability and representativeness of climatic data. Two data mining methods for selecting energy efficiency measures on an urban scale are tested and validated by saved energy of dynamic models. With reference to application field of definition of minimum building requirements the thesis analyses the process to define them. Moreover, it studies how the energy performance modelling influence the definition of minimum building requirements (about the fabric or the HVAC system) and as a fixed requirement could have an imbalance effect between different services. An improved procedure is shown to define the notional reference building and an analysis is led on a heating generator to show how the modelling of technology can affect minimum requirements. Finally concerning EP in valuation methods, case studies with Cost-Optimal Analysis (COA) and Multi-Criteria Analysis (MCA) are performed. The first one gives the possibility to compare results obtained with two calculation methods, the second one permits to investigate the role of energy performance in MCA.