Application of Taguchi method in optimising thermal comfort and cognitive performance during direct load control events

Abstract

Direct load control (DLC) is a demand response strategy that allows a utility or an aggregator to cycle specific appliances of their customers on and off or implement thermostat setback during peak demand periods. In the present research, a methodology is proposed to optimise DLC air-conditioning algorithms in order to achieve optimum and robust thermal comfort and cognitive performance outcome for commercial building occupants using Taguchi method. Human subject experiments were carried out simulating DLC events with four control factors in a university lecture theatre. Results reveal that off cycle fraction and adapting temperature are the two most important control factors that affect both the variability and mean response of building occupants' thermal sensation; off cycle fraction is the only significant control factor that affects the robustness of occupants' cognitive performance while none of the four control factors has any significant impact on the mean performance scores. DLC algorithms with off cycle fraction not higher than 50% and adapting temperature lower than occupants' neutral temperature are recommended to achieve optimum and robust thermal comfort and cognitive performance outcome. Cycling period and building envelope thermal performance do not have any significant impact. DLC air-conditioning strategies can be widely implemented in commercial buildings with various thermal performance conditions as long as the off cycle fraction and adapting temperature are optimised.