Modeling and optimization of a passive building HVAC system based on improved PSO and H-J Algorithm

Abstract

Passive buildings employ the principles of active optimization and passive priority to demonstrate their energy-saving, comfortable, and cost-effective qualities, thereby addressing energy consumption in an efficient manner. However, it cannot be ignored that the Heating Ventilation Air Conditioning (HVAC) system is still the largest energy consumer, especially when it is necessary to maintain the comfort of the indoor environment. Consequently, the control and optimization of the HVAC system is a research hotspot and a challenge in the field of building energy conservation, as it is the key to achieving ultra-low energy consumption operation in passive buildings while ensuring the thermal comfort of the indoor environment. This paper presents a comprehensive modeling, control, and optimization framework for the efficient operation of HVAC systems in a passive building located in Jinan, China. Firstly, the HVAC system is modeled using the transient system simulation tool (TRNSYS), GenOpt, Java, and other software. Secondly, the HVAC system’s year-round operation is simulated using specific configurations. In order to enhance the energy-saving effect, a strategy of increasing heat storage and return air ducts was proposed, and a significant energy-saving effect (approximately 17.31%) was realized. Lastly, the data communication interface with GenOpt is established utilizing the TRNOPT module, a method for actively optimizing the refrigerant temperature is proposed, and recalculation and optimization are carried out utilizing the swarm intelligence algorithm and the pattern search algorithm (Hooker-Jeeves algorithm, H-J algorithm). The final optimization results demonstrate a 19% reduction in energy consumption relative to the baseline heat recovery model, validating the applicability of the optimization method under this strategy. The control and optimization method of the HVAC system proposed in this paper can further exploit the energy-saving potential of the passive building HVAC system and will contribute to the advancement of building energy conservation.