Balancing the Performance-Efficiency Trade-off in Lighting Control Systems through Meta-Optimisation

Occupancy-based lighting control systems provide dimming solutions according to the positions of occupants. Computational optimisation assists these systems in identifying dimming strategies that enhance energy efficiency. However, the parameters used in the optimisation process influence both the system’s processing time and the level of energy reduction achieved. This study used a meta-optimisation method to determine these parameters, balancing processing time and energy consumption. In a simulated realistic open-plan office environment, the Non-Dominated Sorting Genetic Algorithm II was used to evaluate a range of dimming optimisation parameters that varied in processing time and energy efficiency. The resulting optimal parameters allowed the lighting control system to effectively provide dimming solutions for dynamic occupancy scenarios, leading to improved energy savings.