Real-Time Implementation of Model Predictive Control for Cooling System of a Factory Building

• Published in: ASHRAE transactions Vol. 128; no. 2; pp. 175 - 182
• Main Authors: Ra, Seon-Jung, Kim, Jin-Hong, Jo, Hyeong-Gon, Kim, Young-Sub, Park, Cheol-Soo
• Format: Journal Article
• Language: English
• Published: Atlanta American Society of Heating, Refrigerating, and Air-Conditioning Engineers, Inc. (ASHRAE) 01.01.2022; American Society of Heating, Refrigeration and Air Conditioning Engineers, Inc
• Subjects: Accuracy; Air conditioning; Air temperature; Analysis; Artificial neural networks; Control systems; Cooling; Cooling systems; Diffusers; Energy conservation; Energy consumption; Energy management systems; Environmental control; Green buildings; Humidity; HVAC; Indoor environments; Machine learning; Neural networks; Predictive control; Real time; Relative humidity; Simulation; Simulation models; South Korea; Temperature; Variables; Weather forecasting; South Korea

This paper presents a real-time application of model predictive control (MPC) for a cooling system of a target building using machine learning models. The building is a heavy-machinery assembly building consisting of many large indoor spaces. The size of a thermal zone of our interest is 80 m*60m *9...