TY - JOUR
T1 - Model-based multi-objective optimal control of a VRF (variable refrigerant flow) combined system with DOAS (dedicated outdoor air system) using genetic algorithm under heating conditions
AU - Kim, Wonuk
AU - Jeon, Seung Won
AU - Kim, Yongchan
N1 - Funding Information:
This work was supported by the Human Resources Development Program (No. 20144010200770 ) and the Energy Technology Development Program (No. 20142010102660 ) with a Korea Institute of Energy Technology Evaluation and Planning (KETEP) grant funded by the Korea Government Ministry of Trade, Industry and Energy.
PY - 2016/7/15
Y1 - 2016/7/15
N2 - A VRF (variable refrigerant flow) combined system adopting a DOAS (dedicated outdoor air system) has been proposed to reduce the total energy consumption while satisfying IAQ (indoor air quality) and THC (thermal and humidity comfort) with minimum outdoor air. The objective of this study is to develop a model-based multi-objective optimal control strategy for the VRF combined system with multi-zone in order to optimize the multi-objective functions of the THC, IAQ, and total energy consumption. The performance of the VRF combined system was evaluated using the EnergyPlus model. The VRF combined system was optimized by GA (genetic algorithm) and RSM (response surface methodology) with the multi-objective functions of the THC, IAQ, and total energy consumption. The proposed multi-objective optimal control strategies (A and B) were compared with the TS (time schedule) strategy and the DCVH (demand controlled ventilation with humidifying). Optimal control strategy B reduced the total energy consumption by 20.4% and increased the ratio of the hours satisfying the extended comfort zone by 19.1% compared to the DCVH strategy.
AB - A VRF (variable refrigerant flow) combined system adopting a DOAS (dedicated outdoor air system) has been proposed to reduce the total energy consumption while satisfying IAQ (indoor air quality) and THC (thermal and humidity comfort) with minimum outdoor air. The objective of this study is to develop a model-based multi-objective optimal control strategy for the VRF combined system with multi-zone in order to optimize the multi-objective functions of the THC, IAQ, and total energy consumption. The performance of the VRF combined system was evaluated using the EnergyPlus model. The VRF combined system was optimized by GA (genetic algorithm) and RSM (response surface methodology) with the multi-objective functions of the THC, IAQ, and total energy consumption. The proposed multi-objective optimal control strategies (A and B) were compared with the TS (time schedule) strategy and the DCVH (demand controlled ventilation with humidifying). Optimal control strategy B reduced the total energy consumption by 20.4% and increased the ratio of the hours satisfying the extended comfort zone by 19.1% compared to the DCVH strategy.
KW - Dedicated outdoor air system
KW - Model-based control
KW - Multi-objective optimization
KW - Multi-zone ventilation
KW - Variable refrigerant flow
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U2 - 10.1016/j.energy.2016.03.139
DO - 10.1016/j.energy.2016.03.139
M3 - Article
AN - SCOPUS:84964459819
VL - 107
SP - 196
EP - 204
JO - Energy
JF - Energy
SN - 0360-5442
ER -