A novel HVAC fuzzy controller based on improved snake optimizer algorithm

Abstract

Heating, ventilation, and air conditioning (HVAC) systems are characterized by time-varying, nonlinear, and parametric coupling, making it challenging to design their controllers. As a major source of energy consumption in buildings, the control schemes for HVAC systems need to be optimized to improve energy efficiency. To address the above issues, a fuzzy controller was designed to regulate the HVAC system, and an improved snake optimizer (ISO) was proposed to optimize the membership function of the fuzzy controller in this study. In the ISO algorithm, the parameter Threshold of the snake optimizer (SO) was dynamically adjusted, and the snake egg-hatching formula was improved. Benchmark function tests show that the convergence speed and optimization accuracy of ISO are superior to those of the established comparison algorithms. Furthermore, simulation experiments indicate that the ISO-optimized HVAC system has a temperature error of 0 and a humidity ratio error of less than 1.5% compared to competing methods. In addition, the ISO-optimized HVAC system achieves a 40.8% reduction in annual energy consumption.