In this context, the developed tool combines a dynamic energy simulation module based on the heat balance method and a Life Cycle Cost (LCC) module with an optimization toolbox (Matlab - OptimTool).
The aim of this study is to provide a tool to aid designers in satisfying the requirements of government regulations and green building certification programs while optimizing the costs and maintaining thermal comfort. An extensive range of design possibilities is identified which achieve low-energy status by greatly different means with some concentrating on reducing losses and others on maximising their use of causal gains, including solar gains.īuildings have a remarkable impact on the environment, therefore finding efficient design configurations satisfying conflicting criteria such as the economic and environmental performance has become an important task. These designs are then presented to the user in the form of a visual summary for judgement as to potential use.In order that sufficiently different designs are evolved, and the thermal model can be run over a complete year on an hourly grid, several adaptations to the genetic algorithm have had to be made.The approach is illustrated by the design of a community hall. This paper couples a population-based optimisation algorithm (a genetic algorithm) to a dynamic thermal model with the idea of identifying large numbers of distinctly different low-energy designs. Simply minimising the heat loss from a building will not necessarily lead to an exemplary low-energy design: overheating may occur, leading to a large amount of cooling energy being used, and the shape and form of the design may not fit with other sensitivities and elements of the design brief.
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