Robust control and optimisation of energy consumption in daylight—artificial light integrated schemes

Abstract

Energy efficiency strategies based on daylight—artificial light integrated schemes have proved to be efficient by many researchers worldwide. But much larger energy savings with the benefit of visual and thermal comfort can be achieved when systems integration strategies are competently designed. They require a high level of expertise and familiarity with new design techniques. This study describes the results of three computational models suitable for the optimum integration of visual comfort, thermal comfort, and energy consumption in schemes where daylight and artificial light are integrated. This mainly involves: (i) a system identification approach in lighting control strategy, (ii) a fuzzy logic based controller to reduce glare, increase uniformity and thermal comfort, and (iii) an adaptive predictive control scheme for the dimming of artificial light. In addition to the above models the scheme must take account of occupancy and user wishes. The anticipated synergetic effects of the computational models have been validated using climate data. A SIMULINK environment is established for the real time control and analysis of daylight—artificial light integrated schemes. Overall, the schemes maximise energy cost saving while optimizing the performance and the quality of the visual environment.