scholarly journals Economic Multiple Model Predictive Control for HVAC Systems - A Case Study for a Food Manufacturer in Germany

2018 ◽  
Author(s):  
Tobias Heidrich ◽  
Jonathan Grobe ◽  
Henning Meschede ◽  
Jens Hesselbach
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Air Conditioning ◽  
Variable Temperature ◽  
Conveyor Belt ◽  
Electricity Price ◽  
Multiple Model ◽  
Air Conditioning System ◽  
Discrete State ◽  
Temperature And Humidity

The following paper describes an economical, multiple model predictive control (EMMPC) for an air conditioning system of a confectionery manufacturer in Germany. The application consists of a packaging hall for chocolate bars, in which a new local conveyor belt air conditioning system is used and thus the temperature and humidity limits in the hall can be significantly extended. The EMMPC calculates the optimum energy or cost humidity and temperature set points in the hall. For this purpose, time-discrete state space models and an economic objective function with which it is possible to react to flexible electricity prices in a cost-optimised manner are created. A possible future electricity price model for Germany with a flexible EEG levy was used as a flexible electricity price. The flexibility potential is determined by variable temperature and humidity limits in the hall, which are oriented towards the comfort field for easily working persons, and the building mass. The building mass of the created room model is used as a thermal energy store. Considering electricity price and weather forecasts as well as internal, production plan-dependent load forecasts, the model predictive controller directly controls the heating and cooling register and the humidifier of the air conditioning system.

scholarly journals Economic Multiple Model Predictive Control for HVAC Systems—A Case Study for a Food Manufacturer in Germany

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3461 ◽  
Author(s):  
Tobias Heidrich ◽  
Jonathan Grobe ◽  
Henning Meschede ◽  
Jens Hesselbach
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Air Conditioning ◽  
Variable Temperature ◽  
Conveyor Belt ◽  
Electricity Price ◽  
Multiple Model ◽  
Air Conditioning System ◽  
Discrete State ◽  
Temperature And Humidity

The following paper describes an economical, multiple model predictive control (EMMPC) for an air conditioning system of a confectionery manufacturer in Germany. The application consists of a packaging hall for chocolate bars, in which a new local conveyor belt air conditioning system is used and thus the temperature and humidity limits in the hall can be significantly extended. The EMMPC calculates the optimum energy or cost humidity and temperature set points in the hall. For this purpose, time-discrete state space models and an economic objective function with which it is possible to react to flexible electricity prices in a cost-optimised manner are created. A possible future electricity price model for Germany with a flexible Renewable Energies levy (EEG levy) was used as a flexible electricity price. The flexibility potential is determined by variable temperature and humidity limits in the hall, which are oriented towards the comfort field for easily working persons, and the building mass. The building mass of the created room model is used as a thermal energy store. Considering the electricity price and weather forecasts as well as an internal, production plan-dependent load forecasts, the model predictive controller directly controls the heating and cooling register and the humidifier of the air conditioning system.

scholarly journals Model Predictive Control with Adaptive Building Model for Heating Using the Hybrid Air-Conditioning System in a Railway Station

Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1996
Author(s):  
Ruixin Lv ◽  
Zhongyuan Yuan ◽  
Bo Lei ◽  
Jiacheng Zheng ◽  
Xiujing Luo
Keyword(s):  
Energy Consumption ◽  
Model Predictive Control ◽  
Thermal Comfort ◽  
Predictive Control ◽  
Pid Control ◽  
Air Conditioning ◽  
Adaptive Model ◽  
Air Conditioning System ◽  
Building Model ◽  
Indoor Thermal Comfort

A model predictive control (MPC) system with an adaptive building model based on thermal-electrical analogy for the hybrid air conditioning system using the radiant floor and all-air system for heating is proposed in this paper to solve the heating supply control difficulties of the railway station on Tibetan Plateau. The MPC controller applies an off-line method of updating the building model to improve the accuracy of predicting indoor conditions. The control performance of the adaptive MPC is compared with the proportional-integral-derivative (PID) control, as well as an MPC without adaptive model through simulation constructed based on a TRNSYS-MATLAB co-simulation testbed. The results show that the implementation of the adaptive MPC can improve indoor thermal comfort and reduce 22.2% energy consumption compared to the PID control. Compared to the MPC without adaptive model, the adaptive MPC achieves fewer violations of constraints and reduces energy consumption by 11.5% through periodic model updating. This study focuses on the design of a control system to maintain indoor thermal comfort and improve system efficiency. The proposed method could also be applied in other public buildings.

Experimental study of a model predictive control system for active chilled beam (ACB) air-conditioning system

2019 ◽  
Vol 203 ◽  
pp. 109451 ◽  
Author(s):  
Shiyu Yang ◽  
Man Pun Wan ◽  
Bing Feng Ng ◽  
Swapnil Dubey ◽  
Gregor P. Henze ◽  
...  
Keyword(s):  
Experimental Study ◽  
Control System ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Air Conditioning ◽  
Air Conditioning System
Sign in / Sign up

Export Citation Format

Share Document