CALIBRATION AND VALIDATION OF RESIDENTIAL BUILDINGS: 8 CASE STUDIES OF DETACHED HOUSES Georgios Georgiou, Mahroo Eftekhari, Phil Eames Loughborough University, Loughborough, United Kingdom ABSTRACT Reducing our dependence on fossil fuels for energy and thereby, mitigating the impacts of climate change is one of the key challenges of the 21 st century. Buildings are responsible for nearly 40% of energy consumption (and 36% of GHG emissions) in the EU. The Europe-wide initiatives on transforming the energy system for a decarbonized future recognize the importance of buildings and the refurbishment of the existing housing inventory, for energy conservation and associated CO2 emissions. Building simulation is well accepted as a best practise to investigate the application of ECM in the building sector. In order to enhance the integrity of the outcome, the building models must be validated. Thereby, this study seeks to present the application of the mid-season calibration, using 8 actual dwellings as case studies. These houses are evaluated by statistical metrics, demonstrating the effective application of mid-season calibration, using the indoor temperature and monthly energy consumption. INTRODUCTION Building simulation is routinely applied as a tool for energy and environmental performance assessments of buildings. The building physics can be investigated, statically or dynamically, providing a suitable tool to study thermal comfort, predict energy performance and/or sizing the HVAC systems in the building environment. In essence, the simulation is repeatable; allowing the analyst (designer/engineer) to replicate numerous experiments, on the contrary with the real world where due to its “nature” is merely difficult to allow precise experimentation. It is then evident that a growing acceptance defines building simulation as a best practice to imitate the real life scenarios. However, real life and buildings are governed by complex dynamic-principles, which require realistic simulations, rather than simple imitation (Clarke, 2001). The importance of a reliable outcome is critically presented during the adoption of ECMs. Fault decisions, due to the inability to represent the abstraction of reality, may lead to inconvenience and expenses which are coherent with the insufficient actions and measures during the design stage. Particularly, during the synthesis of a simulation model, several parameters of the building are assigned as “inputs” (i.e. material properties, infiltration rate, orientation, ground reflectance, weather profile and etc.), which are associated with uncertainties. Thus, in order to foster the accuracy and the reliability of the “output”, the calibration and validation of the model is considered as an essential stage in the context of energy saving measures and building simulation (Reddy et al., 1994). In an extensive literature review on calibrating a model, Reddy 2005, presented the essential steps of calibration procedure, as follows: (1) data collection, (2) importing data into the model, (3) comparison of predicted and actual performance and (4) finally, the evaluation whether the desired accuracy has been achieved (Reddy, 2005). Reddy 2005 also, categorized the calibration procedures into: (a) manual, iterative and pragmatic intervention (Filippin et al., 2008; Pedrini et al., 2002; Reddy et al., 1994; Yoon et al., 2003), (b) suite of informative graphical comparative displays (Bou- Saada and Haberl, 1995; Haberl et al., 1996; McCray et al., 1995), (c) special tests and analytical procedures (Haves et al., 2001; Reddy et al., 1999; Soebarto, 1997; Subbarao, 1998; Wei et al., 1998) and (d) analytical/mathematical models (Caroll and Hitchcock, 1993; Heo et al., 2012; Tahmasebi and Mahdavi, 2012; Tahmasebi et al., 2012). The adoption of a particular approach is primarily founded on the experience and skills of the analyst, the type of the building, the availability and interval of input data and the time availability, and as a result, a heuristic tuning of the model. The scene is deteriorated in residential sector, due to the privacy characterizing domestic buildings, their operation and the limited literature with regards on the calibration of dwellings. Through this paper, a step-by-step calibration procedure will be presented for actual dwellings. It will be based on a backward stepwise approach founded on the key concept of mid-season calibration, due to the absence of hourly energy data (Lyberg, 1987; Yoon et al., 2003).Additionally, in order to enhance the accuracy of the model, hourly indoor temperature will be employed to match the actual and