Nonintrusive Load Monitoring of Variable Speed Drive Cooling Systems

被引:5
作者
Lindahl, Peter A. [1 ]
Ali, Muhammad Tauha [2 ]
Armstrong, Peter [2 ]
Aboulian, Andre [3 ]
Donnal, John [4 ]
Norford, Les [5 ]
Leeb, Steven B. [3 ]
机构
[1] Exponent Inc, Natick, MA 01760 USA
[2] Khalifa Univ Sci & Technol, Dept Mech Engn, Abu Dhabi, U Arab Emirates
[3] MIT, Dept Elect Engn & Comp Sci, Cambridge, MA 02139 USA
[4] US Naval Acad, Weapons & Syst Engn Dept, Annapolis, MD 21402 USA
[5] MIT, Dept Architecture, 77 Massachusetts Ave, Cambridge, MA 02139 USA
关键词
Cooling; Buildings; Monitoring; Refrigerants; Harmonic analysis; Heating systems; Power system harmonics; Air conditioning; condition monitoring; cooling; HVAC; nonintrusive load monitoring; smart meters; variable speed drives; ENERGY-CONSUMPTION; DISAGGREGATION; MODEL; TEMPERATURE;
D O I
10.1109/ACCESS.2020.3039408
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
To improve the energy efficiencies of building cooling systems, manufacturers are increasingly utilizing variable speed drive (VSD) motors in system components, e.g. compressors and condensers. While these technologies can provide significant energy savings, these benefits are only realized if these components operate as intended and under proper control. Undetected faults can foil efficiency gains. As such, it's imperative to monitor cooling system performance to both identify faulty conditions and to properly inform building or multi-building models used for predictive control and energy management. This paper presents nonintrusive load monitoring (NILM) based "mapping" techniques for tracking the performance of a building's central air conditioning from smart electrical meter or energy monitor data. Using a multivariate linear model, a first mapping disaggregates the air conditioner's power draw from that of the total building by exploiting the correlations between the building's line-current harmonics and the power consumption of the air conditioner's VSD motors. A second mapping then estimates the air conditioner's heat rejection performance using as inputs the estimated power draw of the first mapping, the building's zonal temperature, and the outside environmental temperature. The usefulness of these mapping techniques are demonstrated using data collected from a research facility building on the Masdar City Campus of Khalifa University. The mapping techniques combine to provide accurate estimates of the building's air conditioning performance when operating under normal conditions. These estimates could thus be used as feedback in building energy management controllers and can provide a performance baseline for detection of air conditioner underperformance.
引用
收藏
页码:211451 / 211463
页数:13
相关论文
共 50 条
[31]   DistribuNet: A Robust Neural Framework for Mitigating Distributional Shifts in Nonintrusive Load Monitoring [J].
Xu, Yang ;
Xu, Qingshan ;
Xia, Yuanxing .
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2025, 74
[32]   MODELLING OF THE VARIABLE SPEED DRIVE WITH SPEED OBSERVER [J].
Rinkeviciene, Roma ;
Kriauciunas, Jonas .
ELECTRICAL AND CONTROL TECHNOLOGIES, 2010, :215-218
[33]   Detecting Users' Behaviors based on Nonintrusive Load Monitoring Technologies [J].
Chen, Yung-Chi ;
Chu, Chun-Mei ;
Tsao, Shiao-Li ;
Tsai, Tzung-Cheng .
2013 10TH IEEE INTERNATIONAL CONFERENCE ON NETWORKING, SENSING AND CONTROL (ICNSC), 2013, :804-809
[34]   Exploiting HMM Sparsity to Perform Online Real-Time Nonintrusive Load Monitoring [J].
Makonin, Stephen ;
Popowich, Fred ;
Bajic, Ivan V. ;
Gill, Bob ;
Bartram, Lyn .
IEEE TRANSACTIONS ON SMART GRID, 2016, 7 (06) :2575-2585
[35]   An Adaptive Two-Stage Load Event Detection Method for Nonintrusive Load Monitoring [J].
Luan, Wenpeng ;
Liu, Zishuai ;
Liu, Bo ;
Yu, Yixin ;
Hou, Yufan .
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2022, 71
[36]   Improving Nonintrusive Load Monitoring Efficiency via a Hybrid Programing Method [J].
Kong, Weicong ;
Dong, Zhao Yang ;
Hill, David J. ;
Luo, Fengji ;
Xu, Yan .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2016, 12 (06) :2148-2157
[37]   Variable Frequency Drive as a Source of Condition Monitoring Data [J].
Orkisz, M. ;
Wnek, M. ;
Kryczka, K. ;
Joerg, P. .
2008 INTERNATIONAL SYMPOSIUM ON POWER ELECTRONICS, ELECTRICAL DRIVES, AUTOMATION AND MOTION, VOLS 1-3, 2008, :179-+
[38]   Aging Condition Monitoring for Aluminum Electrolytic Capacitor in Variable Speed Drives [J].
Wang, Bo ;
Meng, Jinlei ;
Zhao, Pinzhi .
IEEE TRANSACTIONS ON POWER ELECTRONICS, 2022, 37 (04) :4564-4574
[39]   Recurrence Plots and Convolutional Neural Networks Applied to Nonintrusive Load Monitoring [J].
Cavalca, Diego L. ;
Fernandes, Ricardo A. S. .
2020 IEEE POWER & ENERGY SOCIETY GENERAL MEETING (PESGM), 2020,
[40]   Deep Transfer Learning-Based Feature Extraction: An Approach to Improve Nonintrusive Load Monitoring [J].
Cavalca, Diego L. ;
Fernandes, Ricardo A. S. .
IEEE ACCESS, 2021, 9 :139328-139335