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Building Performance Simulation (BPS) has the potential to provide relevant design information by indicating directions for design solutions or uncertainty and sensitivity analysis. A major challenge in simulation tools is how to deal with difficulties through large variety of parameters and complexity of factors such as non-linearity, discreteness, and uncertainty. It is hypothesized that conducting an uncertainty and sensitivity analysis throughout key stages of the design process would be of great importance. The purpose of uncertainty and sensitivity analysis can be described as identifying uncertainties in input and output of a system or simulation tool [Lomas, 1992; Fuerbringer, 1994;MacDonald, 2002]. In practice uncertainty and sensitivity analysis have many additional benefits including:(1) With the help of parameter screening it enables the simplification of a model [de Wit, 1997].(2) It allows the analysis of the robustness of a model [Litko, 2005]. (3) It makes aware of unexpected sensitivities that may lead to errors and/ or wrong specifications (quality assurance) [Lewandowska et al., 2004; Hopfe et al., 2006;Hopfe et al., 2007] (4) By changing the input of the parameters and showing the effect on the outcome of a model, it provides a "what-if analysis". It is for instance used in multiple decision support tools [Gokhale, 2009].In this paper a case study is performed based on an office building with respect to various building performance parameters. Uncertainty analysis (UA) is carried out and implications for the results considering energy consumption (annual heating and cooling) and thermal comfort (weighted over-and underheating hours) are demonstrated and elaborated. The added value and usefulness of the integration of UA in BPS is shown.

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There is a need for decision support tools that integrate energy simulation into early design of zero energy buildings in the architectural practice. Despite the proliferation of simulation programs in the last decade, there are no ready-to-use applications that cater specifically for the hot climates and their comfort conditions. Furthermore, the majority of existing tools focus on evaluating the design alternatives after the decision making, and largely overlook the issue of informing the design before the decision making. This paper presents energy-oriented software tool that both accommodates the Egyptian context and provides informative support that aims to facilitate decision making of zero energy buildings. A residential benchmark was established coupling sensitivity analysis modelling and energy simulation software (EnergyPlus) as a means of developing a decision support tool to allow designers to rapidly and flexibly assess the thermal comfort and energy performance of early design alternatives. Validation of the results generated by the tool and ability to support the decision making are presented in the context of a case study and usability testing.

More than 30% of the total primary energy in the world is consumed in buildings. It is crucial to reduce building energy consumption in order to preserve energy resources and mitigate global climate change. Building performance simulations have been widely used for the estimation and optimization of building performance, providing reference values for the assessment of building energy consumption and the effects of energy-saving technologies. Among the various factors influencing building energy consumption, occupant behavior has drawn increasing attention. Occupant behavior includes occupant presence, movement, and interaction with building energy devices and systems. However, there are gaps in occupant behavior modeling as different energy modelers have employed varied data and tools to simulate occupant behavior, therefore producing different and incomparable results. Aiming to address these gaps, the International Energy Agency (IEA) Energy in Buildings and Community (EBC) Programme Annex 66 has established a scientific methodological framework for occupant behavior research, including data collection, behavior model representation, modeling and evaluation approaches, and the integration of behavior modeling tools with building performance simulation programs. Annex 66 also includes case studies and application guidelines to assist in building design, operation, and policymaking, using interdisciplinary approaches to reduce energy use in buildings and improve occupant comfort and productivity. This paper highlights the key research issues, methods, and outcomes pertaining to Annex 66, and offers perspectives on future research needs to integrate occupant behavior with the building life cycle.