Control Strategy of Central Air Conditioning using RF-NSGA-II

Optimizing the control strategy of the central air conditioning system is crucial for conserving energy in buildings and facilitating the attainment of the dual carbon goal. To address the complex issue of equipment modeling in the system, the RF model is used to accurately depict the nonlinear relationship between system parameters and prediction objectives, which simplifies the modeling process. Then we establishes a dual objective optimization problem, aiming to minimize total power consumption while minimizing system efficiency. The NSGA-II algorithm is utilized to obtain a set of pareto optimal solutions, and then ASF is employed to identify the unique optimal solution. By implementing the derived control strategies, which involve adjusting the fan speed and equipment states, the central air conditioning system achieves reduction in power consumption by 14.5% and system efficiency by 56.31%. This validates the effectiveness of the proposed RF-NSGA-II model.