Development of an optimal mechanical ventilation system control strategy based on weather forecasting data for outdoor air cooling in livestock housing. (1st April 2023)

• Record Type: Journal Article
• Authors: Shin, Hakjong; Kwak, Younghoon; Jo, Seng-Kyoun; Kim, Se-Han; Huh, Jung-Ho
• Is Part Of: Energy. Volume 268(2023)
• Publication Date: 2023-04-01
• Subjects: Livestock -- Mechanical ventilation -- Optimal energy control -- Outdoor air cooling -- Weather forecasting data; HVAC heating, ventilation, and air conditioning -- IEQ indoor environment quality -- VFD variable frequency drive -- CFD computational fluid dynamics -- BES building energy simulation -- PLR part-load ratio -- EPW EnergyPlus weather file -- CVRMSE coefficient of variance of the root mean square error -- ASHRAE American Society of Heating, Refrigerating and Air-Conditioning Engineers -- CTF conduction transfer function -- PLF part-load factor -- ESP energy-saving performance -- ESPA energy-saving performance achievement -- MAE mean absolute error -- MBE mean bias error; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2023.126649
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract : Mechanical ventilation systems are commonly utilized in livestock housing to counter indoor pollution and control the indoor thermal environment. During their operation, the systems must be appropriately controlled according to the changes in the indoor/outdoor thermal environments (conventionally handled by the facility manager based on their experience). In this study, a 24 h optimal ventilation system control strategy was developed using weather forecasting data to control the temperature in livestock housing. A building energy system model for livestock housing was developed based on measurement data. The optimal control strategy was derived by conducting simulation analysis using the model and optimizing four control variables of the ventilation system. The developed optimal ventilation system control strategy showed better indoor air temperature maintenance performance (energy-saving performance (ESP) of 20.50%) compared to the conventional control method. Furthermore, the ESP achievement increased as the prediction performance of the weather forecasting data increased. The optimal ventilation fan control strategy developed in this study, an intelligent control method based on an energy model and weather forecasting data, is expected to be introduced as an advanced technology to the field of livestock housing wherein research on the development of such strategies in the operation stage is still insufficient. Highlights: Optimal control of livestock mechanical ventilation systems via weather forecasting. Proposed strategy demonstrates sufficient indoor temperature maintenance performance. Proposed strategy exhibited high energy efficiency compared to conventional method. Enhanced energy savings through accurate weather forecasts.