Low-energy design: combining computer-based optimisation and human judgement

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 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. 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. 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. (C) 2002 Elsevier Science Ltd. All rights reserved.