Implementation of a robust real-time non-intrusive load monitoring solution

被引:36
作者
Welikala, Shirantha [1 ,2 ]
Thelasingha, Neelanga [1 ]
Akram, Muhammed [1 ]
Ekanayake, Parakrama B. [1 ]
Godaliyadda, Roshan I. [1 ]
Ekanayake, Janaka B. [1 ,3 ]
机构
[1] Univ Peradeniya, Dept Elect & Elect Engn, Peradeniya, Sri Lanka
[2] Boston Univ, Div Syst Engn, Boston, MA 02215 USA
[3] Cardiff Univ, Sch Engn, Cardiff, S Glam, Wales
基金
美国国家科学基金会;
关键词
Non-intrusive load monitoring; Real-time load monitoring; Subspace techniques; Smart grid; Demand side management; Supply voltage variation; ALGORITHM; POWER;
D O I
10.1016/j.apenergy.2019.01.167
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
This paper presents the formulation and practical implementation of a spectral decomposition based, Real-Time Non-Intrusive Load Monitoring (RT-NILM) solution. Many of the NILM techniques reported in the literature have been validated on environments with non-varying supply voltages, while relying on multiple measurements taken at high sampling rates. In contrast, the RT-NILM solution proposed in this paper has addressed the issue of supply voltage variability, which is a common practical problem prevalent in many developing countries and is anticipated to emerge globally with the increased penetration of renewable energy sources. Therefore, the proposed RT-NILM algorithm was implemented to maintain high accuracy levels even under severe supply voltage fluctuations. An iterative implementation of the Karhunen-Loeve expansion was introduced to improve the spectrum decomposition resolution. Further, a fast deconvolution based technique was introduced for the disaggregation of individual power levels of active appliances in an computationally efficient manner. The proposed solution has been validated on a real voltage varying environment, at a real house, in real-time, using active power and voltage measurements taken at a low sampling rate of 1 Hz.
引用
收藏
页码:1519 / 1529
页数:11
相关论文
共 50 条
  • [41] Unsupervised Adaptive Non-Intrusive Load Monitoring System
    Chou, Po-An
    Chang, Ray-I
    2013 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC 2013), 2013, : 3180 - 3185
  • [42] Overview of non-intrusive load monitoring and identification techniques
    Aladesanmi, E. J.
    Folly, K. A.
    IFAC PAPERSONLINE, 2015, 48 (30): : 415 - 420
  • [43] Elimination of Overfitting of Non-intrusive Load Monitoring Model
    Zhou, Yongjun
    Ji, Chao
    Dong, Zhihua
    Yang, Lin
    Zhang, Shu
    2021 IEEE IAS INDUSTRIAL AND COMMERCIAL POWER SYSTEM ASIA (IEEE I&CPS ASIA 2021), 2021, : 1567 - 1571
  • [44] Designing a Novel Dataset for Non-Intrusive Load Monitoring
    Renaux, Douglas P. B.
    Linhares, Robson R.
    Pottker, Fabiana
    Lazzaretti, Andre E.
    Lima, Carlos R. E.
    Coelho Neto, Adil O.
    Campaner, Mateus H.
    2018 VIII BRAZILIAN SYMPOSIUM ON COMPUTING SYSTEMS ENGINEERING (SBESC 2018), 2018, : 243 - 249
  • [45] Non-intrusive load monitoring based on harmonic characteristics
    Li, Yaqian
    Yang, Yuquan
    Sima, Kai
    Li, Boyang
    Sun, Tong
    Li, Xue
    PROCEEDINGS OF THE 10TH INTERNATIONAL CONFERENCE OF INFORMATION AND COMMUNICATION TECHNOLOGY, 2021, 183 : 776 - 782
  • [46] A Time-Frequency Approach for Event Detection in Non-Intrusive Load Monitoring
    Jin, Yuanwei
    Telebakemi, Eniye
    Berges, Mario
    Soibelman, Lucio
    SIGNAL PROCESSING, SENSOR FUSION, AND TARGET RECOGNITION XX, 2011, 8050
  • [47] INCORPORATING TIME-OF-DAY USAGE PATTERNS INTO NON-INTRUSIVE LOAD MONITORING
    Dinesh, Chinthaka
    Makonin, Stephen
    Bajic, Ivan V.
    2017 IEEE GLOBAL CONFERENCE ON SIGNAL AND INFORMATION PROCESSING (GLOBALSIP 2017), 2017, : 1110 - 1114
  • [48] ELECTRIcity: An Efficient Transformer for Non-Intrusive Load Monitoring
    Sykiotis, Stavros
    Kaselimi, Maria
    Doulamis, Anastasios
    Doulamis, Nikolaos
    SENSORS, 2022, 22 (08)
  • [49] Non-Intrusive Load Monitoring by Novel Neuro-Fuzzy Classification Considering Uncertainties
    Lin, Yu-Hsiu
    Tsai, Men-Shen
    IEEE TRANSACTIONS ON SMART GRID, 2014, 5 (05) : 2376 - 2384
  • [50] Simultaneous disaggregation of multiple appliances based on non-intrusive load monitoring
    Hua, Dong
    Huang, Fanqi
    Wang, Longjun
    Chen, Wutao
    ELECTRIC POWER SYSTEMS RESEARCH, 2021, 193