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Building heating demand evaluation with a simple polynomial function
Abstract
The choice of the design solutions for low energy buildings requires the performance evaluation of the alternatives. In the present study, simple polynomial function is used to estimate the annual energy demand as a function of building envelope physical and geometric parameters. The coefficients of this function are obtained by regression from dynamic simulation results. The number of dynamic simulations needed is reduced by using the design of experiments method. The model shows a good agreement with the dynamic simulation results.
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The methods used to assess the energy performance of buildings are static or dynamic. A paradigm shift is to estimate the energy consumption by using a probabilistic approach and a single concept for the whole range of operation of the building (heating, ventilation and cooling) and to decouple the thermal behavior of the building, the thermal comfort range and the climate data. These requirements can be achieved by using the free-running temperature to characterize the building behavior and the frequency distribution of the outdoor temperature to describe the climate. This paper demonstrates that the dynamic values can be used to estimate the energy load curve, that this curve may be applied to calculate the energy consumption and that the free-running temperature is an equivalent form of the heating/cooling curve. The main advantages of using the concept of free-running temperature are that: (1) the dynamic behavior may be described by steady-state concepts, (2) the whole range of building operation (heating, ventilation and cooling) is described by a single concept and (3) the thermal behavior of the building, the comfort and the climate are decoupled. The mathematical formalism uses matrix notation.
The objective of the OPTI program (the office building module) is to help architects, engineers and design departments to take into account the impact of design choices on energy consumption designing a project.In order to do so, the program must:•be highly user-friendly (language based on drawings);•need a minimum of data;•be very fast.The computation of energy needs and overheating estimation require dynamic thermal programs. These are often slow and need a large amount of data.The use of many parametric studies realized with a dynamic thermal program along with the application of a method used in experimental research (method of experimental design) allowed us to create software providing the user instantaneously with results from a dynamic thermal program without subjecting architects to the disadvantages of this type of program. Indeed, the program provides annual thermal needs and thermal comfort (winter and summer) in relation with orientation, building footprint, window area and type, internal gains, presence of external or internal shading devices, ventilation strategy applied and thermal mass. This design tool is based on Belgian climatic weather data but the same step could be transposed to other climatic data.