Fuzzy Logic Control based Optimization Algorithms for Heating Ventilation and Air Condition System Performance Evaluation

Abstract

There has been a rising concern in decreasing the power consumption in residential house. The heating ventilation and air condition (HVAC) system is the greatest consumer of power in a domestic house. In numerous countries, limited energy from suppliers and the enhancement in power demands leads to a new chance in utilization of home energy management system (HEMS) for an accurate energy utilization. In this study, the particle backtracking search algorithm (BSA) is utilized for HVAC system to decrease annual power consumption, reduce electricity cost and maximize thermal comfort. The developed models analyzed the (HVAC heating and cooling system) energy consumption and cost sceneries during peak, off-peak and both peak and off-peak hours. Fuzzy logic controller (FLC) was developed for the HEMS to perform energy utilization estimation and cost analysis during these periods taking the Malaysian tariff for domestic use into consideration. To improve the FLC outcomes and solve the membership function constraint of FLC, BSA is developed to ensure an optimal reduction of cost and power consumption. To validate the BSA results, particle swarm optimization (PSO) is also used in this study. The results showed BSA enhances the power saving for the HVAC (cooling system) 36.17% and for the HVAC (heating system) 32.57%. The results indicate the BSA shows good performance than PSO schedule controller to reduce the cost and power consumption toward efficient HEMS