Model predictive control of VAV air supply system

Author(s):  
Fan Xiaowei ◽  
He Dasi ◽  
Qiu Guoyong
2014 ◽  
Vol 532 ◽  
pp. 50-57 ◽  
Author(s):  
Khoa Duc Nguyen ◽  
Eric Bideaux ◽  
Minh Tu Pham ◽  
Philippe le Brusq

Auxiliary electrification in Hybrid Electric Vehicle (HEV) and Plug-in Hybrid Electric Vehicle (PHEV) represents a promising solution in energy management of vehicle. The work presented in the following paper focuses on the design of a controller able to reduce the electrical energy consumption of electrified auxiliaries during a driving cycle. A Model Predictive Control (MPC) is proposed and applied to the air supply system of a PHEV. A comparison of energy consumption between this method and two others (Hysteresis Control and Dynamic Programming) is carried out in order to verify the performance of the MPC controller. Numerical simulations show that this technique allows to obtain a significant gain on energy consumption compared to a standard Hysteresis Control. Furthermore, the difference in term of energy consumption between MPC and Dynamic Programming is weak.


2004 ◽  
Vol 2004.79 (0) ◽  
pp. _6-13_-_6-14_
Author(s):  
Tomonori NISHIOKA ◽  
Ryohei YOKOYAMA ◽  
Koichi ITO ◽  
Kazuyuki KAMIMURA ◽  
Tadahiko MATSUBA

Energy ◽  
2019 ◽  
Vol 188 ◽  
pp. 116078 ◽  
Author(s):  
Duo Yang ◽  
Rui Pan ◽  
Yujie Wang ◽  
Zonghai Chen

2015 ◽  
Author(s):  
Alfredo Díaz Jácome ◽  
Marco E. Sanjuán ◽  
Victor Fontalvo Morales ◽  
Cinthia Audivet Durán

U.S. Department of Energy affirms that HVAC systems consume approximately 40% of the total energy used in commercial-building sector. These types of systems are complex because they are composed of a large number of interconnected subsystems. The analysis shown in this paper is established on a building geographically located at the Caribbean coast region of Colombia in a region with tropical savanna climate and it is exposed to constant thermal load changes associated to high wall temperatures and direct sunlight incidence. Under this perspective, an energetic analysis is performed for the HVAC in order to implement a Model Predictive Control (MPC) strategy to enhance the system efficiency under the previously mentioned external conditions. The model predictive strategy is implemented as a system supervisor in order to minimize a cost function that measures the ratio of water consumption to air temperature change in the cooling coil. The strategy manipulates the required temperature of supply water to cooling coil from the chiller, perceiving as input perturbation the outdoor temperature, the desired temperatures for the classrooms and the desired temperature of the air supply to the different zones. The comparison and selection of thermodynamical states for analysis are conducted according to the dynamic characteristics of the entire system and individual components, and the energy assessment is performed including the system transient response. The accomplishment of the supervisory control strategy has demonstrated that dynamic energetic analysis and assessment is an auxiliary tool for HVAC performance management. The analysis performed shows that the supervisory strategy can reduce properly the energy performance index as a consequence, the energy consumption of the fan has a reduction of a 0.65%, while the water required shows a reduction of 66.93%.


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