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There is a growing use of metamodels to evaluate building energy performance. However, current metamodeling approaches lack a common foundation. The aim of this work was to develop a general metamodel for building energy performance. Based on the premise that each building element can have an impact on energy performance, our general metamodel assumes that the overall impact is a polynomial function of the individual impacts. The model includes time-dependent parameters such as the solar heat gain coefficient and energy system efficiency. A model derived from the general model was tested on an office located in Paris. Energy needs and consumption, the cost of energy consumption and the CO 2 emissions for heating and cooling were analyzed. The study highlighted the significant impact of the choice of the performance criteria in evaluating the efficiency of building design solutions. The metamodel represents a fast way to perform calculations with an accuracy close to that of dynamic simulations. It can be used as a basis to perform parametric studies and for future building energy regulations. [ABSTRACT FROM AUTHOR]

Abstract: A rational choice of solutions for low energy building requires a performance evaluation for a large number of parameter combinations. Currently, building thermal dynamic simulation is used to check design solutions but it gives little information on what and how much may be improved. Iterative parameter optimization is a solution but the methods used may stick in local minima and do not allow the designer to evaluate different solutions. An alternative evaluation method is to obtain simple polynomial functions which estimate the annual energy demand as a function of building envelope parameters. The coefficients of these functions may be obtained by regression from dynamic simulation results. The number of dynamic simulations needed is reduced if the numerical simulations are optimally designed. The polynomial functions may be used to predict alternative performances from which the solution may be chosen. The designer is guided in his choice by the coefficients of the polynomial function which give the effect of each parameter on energy demand. [Copyright &y& Elsevier]

Abstract: The Kyoto protocol binded the developed countries to reduce the greenhouse gas emissions at least by 5% by 2008–2012 in order to tackle global warming and climate change. Some of the measures of the governments to achieve this goal are to promote new buildings construction and to retrofit existing buildings while satisfying low energy criteria. This means improving energy efficiency of buildings and energy systems, developing sustainable building concepts and promoting renewable energy sources. The design of a low energy building requires parametric studies via simulation tools in order to optimize the design of the building envelope and HVAC systems. These studies are often complex and time consuming due to a large number of parameters to consider. Hence, this paper aims to set up a methodology that simplifies parametrical studies during the design process of a low energy building. The methodology is based on the Design of Experiments (DOE) method which is a statistical method widely used in industry to perform parametric studies that reduces the required number of experiments. [Copyright &y& Elsevier]