Distributed Control of Multizone HVAC Systems Considering Indoor Air Quality

被引:28
|
作者
Yang, Yu [1 ]
Srinivasan, Seshadhri [1 ]
Hu, Guoqiang [2 ]
Spanos, Costas J. [3 ]
机构
[1] Berkeley Educ Alliance Res Singapore, SinBerBEST, Singapore 138602, Singapore
[2] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore 639798, Singapore
[3] Univ Calif Berkeley, Dept Elect Engn & Comp Sci, Berkeley, CA 94720 USA
基金
新加坡国家研究基金会;
关键词
CO2; distributed approach; indoor air quality (IAQ); multizone heating; ventilation; and air-conditioning (HVAC) system; two levels; VENTILATION CONTROL STRATEGY; ENERGY MANAGEMENT; BUILDINGS;
D O I
10.1109/TCST.2020.3047407
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This article studies a scalable control method for multizone heating, ventilation, and air-conditioning (HVAC) systems to optimize the energy cost for maintaining thermal comfort (TC) and indoor air quality (IAQ) (represented by CO2) simultaneously. This problem is computationally challenging due to the complex system dynamics, various spatial and temporal couplings, as well as multiple control variables to be coordinated. To address the challenges, we propose a two-level distributed method (TLDM) with an upper level and lower level control integrated. The upper level computes zone mass flow rates for maintaining zone TC with minimal energy cost, and then, the lower level strategically regulates zone mass flow rates and the ventilation rate to achieve IAQ while preserving the near energy-saving performance of upper level. As both the upper and the lower level computation are deployed in a distributed manner, the proposed method is scalable and computationally efficient. The near-optimal performance of the method in energy cost saving is demonstrated through comparison with the centralized method. In addition, the comparisons with the existing distributed method show that our method can provide IAQ with only little increase of energy cost, while the latter fails. Moreover, we demonstrate that our method outperforms the demand-controlled ventilation (DCVs) strategies for IAQ management with about 8%-10% energy cost reduction. Note to Practitioners: The high portion of building energy consumption has motivated the energy saving for heating, ventilation, and air-conditioning (HVAC) systems. Concurrently, the living standards for indoor environment are rising among the occupants. Nevertheless, the status quo on improving building energy efficiency has mostly focused on maintaining thermal comfort (such as temperature), and the indoor air quality (IAQ) (usually represented by CO2 level) has been seldom incorporated. In our previous work with the similar setting, we observed that the CO2 levels will surge beyond tolerance during the high occupancy periods if only thermal comfort (TC) is considered for HVAC control. This deduces the IAQ and TC should be jointly considered while pursuing the energy cost saving target and thus studied in this article. This task is computationally cumbersome due to the complex system dynamics (thermal and CO2) and tight correlations among the different control components (variable air volume and fresh air damper). To cope with these challenges, this work develops a two-level distributed computation paradigm for HVAC systems based on problem structures. Specifically, the upper level control (ULC) first calculates zone mass flow rates for maintaining comfortable zone temperature with minimal energy cost, and then, the lower level strategically regulates the computed zone mass flow rates as well as ventilation rate to satisfy IAQ while preserving the near energy-saving performance of the ULC. As both the upper and lower level calculations can be implemented in a distributed manner, the proposed method is scalable to large multizone deployment. The method's performance both in maintaining comfort (i.e., TC and IAQ) and energy cost saving is demonstrated via simulations in comparisons with the centralized method, the distributed token-based scheduling strategy, and the demand-controlled ventilation strategies.
引用
收藏
页码:2586 / 2597
页数:12
相关论文
共 50 条
  • [1] Energy Optimization of HVAC Systems in Commercial Buildings Considering Indoor Air Quality Management
    Yu, Liang
    Xie, Di
    Huang, Chongxin
    Jiang, Tao
    Zou, Yulong
    [J]. IEEE TRANSACTIONS ON SMART GRID, 2019, 10 (05) : 5103 - 5113
  • [2] Influence of indoor air quality on energy performance of HVAC systems
    Kajtar, Laszlo
    Hrustinszky, Tamas
    [J]. PROCEEDINGS OF THE 6TH IASME/WSEAS INTERNATIONAL CONFERENCE ON HEAT TRANSFER, THERMAL ENGINEERING AND ENVIRONMENT (HTE'08), PTS I AND II: NEW ASPECTS OF HEAT TRANSFER, THERMAL ENGINEERING AND ENVIRONMENT, 2008, : 360 - +
  • [3] An Adaptive Distributed Consensus Control for Air Balancing of HVAC Systems
    Liu, Zhangjie
    Zhang, Xin
    Cai, Wenjian
    Cui, Can
    [J]. IECON 2020: THE 46TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY, 2020, : 4794 - 4798
  • [4] AGGREGATION DISAGGREGATION METHOD FOR OPTIMAL-CONTROL OF MULTIZONE HVAC SYSTEMS
    RINK, RE
    LI, N
    [J]. ENERGY CONVERSION AND MANAGEMENT, 1995, 36 (02) : 79 - 86
  • [5] Indoor air quality: Clean, green HVAC machine
    Townsend, Terry
    [J]. FILTRATION + SEPARATION, 2007, 44 (01) : 24 - 26
  • [6] VENTILATION AIR CONTROL IN HVAC SYSTEMS
    NORDEEN, H
    [J]. HEATING-PIPING-AIR CONDITIONING, 1983, 55 (11): : 71 - &
  • [7] Current and recent trend of HVAC filters for Indoor Air Quality
    Choi, KJ
    [J]. INDOOR AIR 2005: PROCEEDINGS OF THE 10TH INTERNATIONAL CONFERENCE ON INDOOR AIR QUALITY AND CLIMATE, VOLS 1-5, 2005, : 1228 - 1230
  • [8] Indoor Air Quality Assessment in an Art Gallery with an HVAC System
    Cai, Wei
    Wang, Danjun
    Wen, Xiaodong
    Yu, Xubo
    [J]. 2010 4TH INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICAL ENGINEERING (ICBBE 2010), 2010,
  • [9] A multi-agent based distributed approach for optimal control of multi-zone ventilation systems considering indoor air quality and energy use
    Li, Wenzhuo
    Wang, Shengwei
    [J]. APPLIED ENERGY, 2020, 275
  • [10] Optimal price based control of HVAC systems in multizone office buildings for demand response
    Amin, U.
    Hossain, M. J.
    Fernandez, E.
    [J]. JOURNAL OF CLEANER PRODUCTION, 2020, 270