Residential building design optimisation using sensitivity analysis and genetic algorithm

Abstract The objective of this paper is to combine sensitivity analysis and simulation-based optimisation in order to optimise the thermal and energy performance of residential buildings in the Argentine Littoral region. An actual house was selected as case study. This is a typical, local, single-family house having some rooms conditioned only by natural ventilation, and other rooms with natural ventilation supplemented by mechanical air-conditioning (hybrid ventilation). Hence, the total degree-hours at the naturally ventilated living room and the total energy consumption by air-conditioning at the bedrooms were chosen as objective functions to be minimised. The global objective function characterising the thermal and energy performance of the house was defined as the weighted sum of these objective functions. This objective function was computed using the EnergyPlus building performance simulation programme. Then, we performed a sensitivity analysis using the Morris screening method to rank the influence of the design variables on the objective function. This showed that the type of external walls, the windows infiltration rate and the solar azimuth were the most influential design variables on the given objective function for the considered house, and also that the azimuth either had a highly nonlinear effect on the objective function or was highly correlated to the others variables, deserving in any case a finer discretisation. Finally, we solved an optimisation problem using genetic algorithms in order to find the optimal set of design variables for the considered house. The results highlighted the efficiency and the effectiveness of the proposed methodology to redesign a typical house in the Argentine Littoral region, improving hugely its thermal and energy performance.

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