Intelligent Power Control and User Comfort Management in Buildings Using Bacterial Foraging Algorithm

One of the major challenges in smart buildings is the task of minimizing the power consumption and simultaneously maximizing the occupants' comfort. Multiagent control system with intelligent optimization that optimize heating, ventilation and air-conditioning (HVAC) environmental parameters based on Bacterial Foraging Algorithm (BFA) and Genetic Algorithm (GA) is presented in this paper. Fuzzy logic controllers were used to compute the required power consumption by each of the three local controllers regulating temperature, illumination and relative humidity to meet the building occupants' comfort requirement. The considered parameters were optimized using BFA and GA and optimal set points as preferred by end user were obtained with the corresponding power and comfort values. This consequently minimizes the total required power with respect to the comfort index. The optimized comfort and power values obtained using BFA and GA has average values of 0.9722, 0.9747 and 69.82kW, 99.29kW respectively which shows a percentage increase of 21.86 % in comfort using BFA and 22.17 % using GA and 80.33 % decrease in power consumption for BFA and 72.02% for GA when compared with an un-optimized scenario depicting the effectiveness of the intelligent optimizers.