The sources of energy are limited but the need is growing and electricity is one of the highest operational costs of a building. The high cost is mainly contributed by the electrical energy consumption of the air-conditioning and lighting systems. Optimizing the power consumption of a building without sacrificing the occupants’ comfort is extremely important as this will reduce electricity bills while maintaining the productivity level of the building’s occupants. This work adopts the use of Genetic Algorithm (GA), for solving the multi-objective optimization problem of the power consumption and comfort in a building, focusing on the room temperature and illumination. The case study involves the use of one air conditioning unit and 12 units of 36-watt fluorescent lamps in a 5-m2 room with the objective of minimizing the power consumption and maximizing comfort. With the application of the GA, the demand requirements have been satisfied. Comparisons between the use of the optimization technique and without the optimization technique have been carried out, both in simulation and real-time experiments. The results show that the GA optimization produces a 23.85% reduction in terms of current (amp), 24.68% reduction in terms of power (w), 23.09% reduction kWh, and 22.81 % reduction in terms of the electric billing cost.
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