A step towards the optimization of the indoor luminous environment by genetic algorithms

Abstract

Buildings are heavily responsible for energy consumption and CO2 emissions. Increasing their energy efficiency is in the direction of the EU strategies; and this is consistent with EU Energy Performance of Buildings Directive (EPBD 2010/31/EU), 2010. In this view the design and management of daylight and artificial light can play a fundamental role. In this paper, a method to optimize indoor lighting design from energy efficiency, economic and environmental viewpoints is presented. The optimization was developed through the Genetic Algorithms technique and the optimal layout in terms of number, location and mounting heights of luminaires in a generic office room was evaluated. Solutions with different types of light sources, nominal luminous flux and photometric distribution curves were compared and the cost effectiveness of these alternatives was also considered. The systems resulting from the optimization show increased uniformity of illuminance, a reduction of the number of luminaires and a decrease of the maximum UGR values, proving the effectiveness of the technique in the lighting design field. Results show that current methods for lighting design can still be improved to achieve optimal configurations in terms of energy efficiency and cost effectiveness.