Optimization of Air Conditioning Energy Consumption Based on Indoor Comfort Degree

With the aggravation of energy shortage and environmental degradation, energy saving and emission reduction are imperative. Among them, the energy consumption of air conditioners accounts for a large proportion, and there is a great potential to enhance the energy consumption system of air conditioners to improve the situation. Therefore, reducing the energy consumption of air conditioners has become a hot topic of concern. However, traditional methods often ignore the requirements of indoor personnel for comfort and do not meet the actual needs. To address this problem, this paper proposes to combine thermal comfort (PMV) and air quality (IAQ) as an integrated indoor comfort level, and the genetic algorithm optimized BP neural network (GA-BP) algorithm is used to model the comfort-energy consumption, which is verified by simulation, and the results prove that the model has small error and is feasible. Based on this, the energy consumption optimization strategy is proposed to achieve the relative optimal relationship between human comfort and energy saving.