Modeling and Controlling of Temperature and Humidity in Building Heating, Ventilating, and Air Conditioning System Using Model Predictive Control

Pouria Bahramnia, Seyyed Mohammad Hosseini Rostami, Jin Wang and Gwang-jun Kim
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Pouria Bahramnia: Electrical Engineering Department, Science and Research Branch, Islamic Azad University, Tehran 1477893855, Iran
Seyyed Mohammad Hosseini Rostami: Electrical Engineering Department, Shiraz University of Technology, Shiraz, Fars 7155713876, Iran
Jin Wang: Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation, School of Computer & Communication Engineering, Changsha University of Science & Technology, Changsha 410004, China
Gwang-jun Kim: Computer Engineering Department, Chonnam National University, Gwangju 61186, Korea

Energies, 2019, vol. 12, issue 24, 1-24

Abstract: Nowadays, by huge improvements in industrial control and the necessity of efficient energy consumption for buildings, unified managing systems are established to monitor and control mechanical equipment and energy usage. One of the main portions of the building management system (BMS) is the cooling and heating equipment called heating and ventilation and air-conditioning (HVAC). Based on temperature slow dynamic and presented uncertainty in modeling, a model predictive control (MPC) strategy to track both temperature and humidity is proposed in this study. The main goal of this study is to provide a framework to describe temperature and humidity elements required for dynamic modeling. Following that, by utilizing a predictive approach, a control strategy is obtained, which optimizes the tracking error of two interactional channel and performs the effort control by minimizing the optimization index. Other articles have mostly only had control over the temperature variable, but in our article, we tried to study the equations of temperature and humidity as well as their interference and according to the ASHRAE standard, both temperature and humidity controls must be accurate. The humidity was the novelty in our article. Simulation results proved the effectiveness of the proposed approach compared to the conventional proportional-integral controller. Evidently, the key idea behind the control objective is providing the comfort condition while consuming the least possible energy.

Keywords: MPC; HVAC; BMS; energy saving; simultaneously control of temperature and humidity; constrained quadratic optimal control; multi-objective optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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