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

Wonuk Kim; Seung Won Jeon; Yongchan Kim

doi:10.1016/j.energy.2016.03.139

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

Wonuk Kim
, Seung Won Jeon
, Yongchan Kim^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

60 Citations (Scopus)

Abstract

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.

Original language	English
Pages (from-to)	196-204
Number of pages	9
Journal	Energy
Volume	107
DOIs	https://doi.org/10.1016/j.energy.2016.03.139
Publication status	Published - 2016 Jul 15

Bibliographical note

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.

Publisher Copyright:
© 2016 Elsevier Ltd.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Dedicated outdoor air system
Model-based control
Multi-objective optimization
Multi-zone ventilation
Variable refrigerant flow

ASJC Scopus subject areas

Civil and Structural Engineering
Building and Construction
Pollution
Mechanical Engineering
Industrial and Manufacturing Engineering
Electrical and Electronic Engineering

Access to Document

10.1016/j.energy.2016.03.139

Cite this

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title = "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",

abstract = "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.",

keywords = "Dedicated outdoor air system, Model-based control, Multi-objective optimization, Multi-zone ventilation, Variable refrigerant flow",

author = "Wonuk Kim and Jeon, \{Seung Won\} and Yongchan Kim",

note = "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. Publisher Copyright: {\textcopyright} 2016 Elsevier Ltd.",

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doi = "10.1016/j.energy.2016.03.139",

language = "English",

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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. Publisher Copyright: © 2016 Elsevier Ltd.

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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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DO - 10.1016/j.energy.2016.03.139

M3 - Article

AN - SCOPUS:84964459819

SN - 0360-5442

VL - 107

SP - 196

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JO - Energy

JF - Energy

ER -

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

Abstract

Bibliographical note

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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