SEADS: A Modifiable Platform for Real Time Monitoring of Residential Appliance Energy Consumption

被引:0
|
作者
Adabi, Ali [1 ]
Manovi, Pavlo [1 ]
Mantey, Patrick [1 ]
机构
[1] Univ Calif Santa Cruz, J Baskin Sch Engn, Santa Cruz, CA 95064 USA
关键词
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Non-Intrusive Load Monitoring (NILM) is the identification of individual electrical loads from aggregate power measurements. Application of NILM in residential settings has been hampered by limited data availability. Utility billing smart meters provide very sparse (time) sampling of energy use, yielding data that is not adequate for quantifying fundamental harmonics of the waveform. For research in NILM, there is an obvious need for a low-cost sensor system to collect energy data with fast sampling and with significant precision. SEADS (Smart Energy Analytic Disaggregation System) provides a powerful and flexible system, supporting user configuration of sampling rates and amplitude resolution up to 65KHz and up to 24 bits respectively. The SEADS internal processor is capable of implementing NILM algorithms in real time on the sampled measurements.
引用
收藏
页数:4
相关论文
共 50 条
  • [1] REAL TIME MONITORING OF INDOOR ENVIRONMENT QUALITY AND ENERGY CONSUMPTION IN A RESIDENTIAL BUILDING
    Toderasc, Mihai
    Iordache, Vlad
    Petcu, Cristian
    Petran, Horia
    ENVIRONMENTAL ENGINEERING AND MANAGEMENT JOURNAL, 2019, 18 (07): : 1561 - 1574
  • [2] Real-time identification of residential appliance events based on power monitoring
    Yang, Zhao
    Zhu, Zhicheng
    Wei, Zhiqiang
    Yin, Bo
    Wang, Xiuwei
    2017 INTERNATIONAL SYMPOSIUM ON APPLICATION OF MATERIALS SCIENCE AND ENERGY MATERIALS (SAMSE 2017), 2018, 322
  • [3] Development of a real time energy monitoring platform
    Bayindir, Ramazan
    Irmak, Erdal
    Colak, Ilhami
    Bektas, Askin
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2011, 33 (01) : 137 - 146
  • [4] Atomic Scheduling of Appliance Energy Consumption in Residential Smart Grids
    Kim, Kyeong Soo
    Lee, Sanghyuk
    Ting, Tiew On
    Yang, Xin-She
    ENERGIES, 2019, 12 (19)
  • [5] Real-Time Recognition Non-Intrusive Electrical Appliance Monitoring Algorithm for a Residential Building Energy Management System
    Agyeman, Kofi Afrifa
    Han, Sekyung
    Han, Soohee
    ENERGIES, 2015, 8 (09): : 9029 - 9048
  • [6] Electric appliance type detection: Approach for estimating residential energy consumption
    Hamdi, Marwa
    Bouguila, Nasreddine
    Chrifi-Alaoui, Larbi
    2017 18TH INTERNATIONAL CONFERENCE ON SCIENCES AND TECHNIQUES OF AUTOMATIC CONTROL AND COMPUTER ENGINEERING (STA), 2017, : 421 - 425
  • [7] Smart IoT Device For Energy Consumption Monitoring In Real Time
    Lopez-Alfaro, Gerardo Asael
    Hernandez-Fernandez, Luis Angel
    Aguirre-Nunez, Jose Alonso
    Serrano-Rubio, Juan Pablo
    Herrera-Guzman, Rafael
    Rodriguez-Vidal, Luz Maria
    PROCEEDINGS OF THE 2021 XXIII IEEE INTERNATIONAL AUTUMN MEETING ON POWER, ELECTRONICS AND COMPUTING (ROPEC 2021), 2021,
  • [8] An educational platform for residential and industrial energy monitoring
    Carraco, Fabio
    Santos, Goncalo
    Fonseca, Inacio
    Lopes, Fernando
    2016 51ST INTERNATIONAL UNIVERSITIES POWER ENGINEERING CONFERENCE (UPEC), 2016,
  • [9] Real-time Disaggregation of Residential Energy Consumption Enhanced with User Feedback
    Sundhu, Anosh Arshad
    Rottondi, Cristina
    Verticale, Giacomo
    2019 4TH INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATIONS AND SECURITY (ICCCS), 2019,
  • [10] Real-time monitoring of energy consumption of high-rise residential construction based on BIM building model
    Liu, Sai
    INTERNATIONAL JOURNAL OF CRITICAL INFRASTRUCTURES, 2021, 17 (04) : 317 - 329