Load Modeling and Voltage Optimization Using Smart Meter Infrastructure

被引:0
|
作者
Shah, Bimal [1 ]
Bose, Anjan [1 ]
Srivastava, Anurag [1 ]
机构
[1] Washington State Univ, Sch Elect Engn & Comp Sci, Pullman, WA 99164 USA
关键词
Conservation Voltage Reduction; Energy Savings; Load Modeling; Peak Load Reduction; Smart Metering Infrastructure; VVC&O (Volt-Var Control and Optimization);
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Voltage - Var Control and Optimization (VVC&O) mechanism in distribution system assisted by local controllers and Distributed Management System (DMS) helps in meeting operating criterion and achieving energy savings. Conservation Voltage Reduction (CVR) with VVC&O allows reduction in peak load and energy consumption, by having flat voltage profile near lower bound of ANSI Standards (114V), while maintaining power factor within limit. To estimate the energy saving, CVR factor is needed and accurate load modeling is required to estimate CVR factors. In this work, distribution system was modeled and simulated utilizing data from one of the feeder in Pullman, WA. This paper presents the results of the study done on improving the VVC capabilities by integrating Smart Meter Infrastructure. Load Modeling was done by observing the behavior of loads at each house and comparing the smart meter data with the simulation results. Precision of developed load model provides enough information to make a decision on required changes in voltage at a substation at a given time for energy saving without violating operation criterion. Results of VVC&O show that energy saving of 4-5% can be achieved at the typical distribution substation.
引用
收藏
页数:6
相关论文
共 50 条
  • [31] Forecasting Demand Flexibility of Aggregated Residential Load Using Smart Meter Data
    Ponocko, Jelena
    Milanovic, Jovica V.
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 2018, 33 (05) : 5446 - 5455
  • [32] Improving Load Forecast Accuracy by Clustering Consumers using Smart Meter Data
    Shahzadeh, Abbas
    Khosravi, Abbas
    Nahavandi, Saeid
    [J]. 2015 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2015,
  • [33] Estimation of distribution transformer kVA load using residential smart meter data
    Usman, Hafiz M.
    ElShatshat, Ramadan
    El-Hag, Ayman H.
    Jabr, Rabih A.
    [J]. ELECTRIC POWER SYSTEMS RESEARCH, 2022, 204
  • [34] HVAC load Disaggregation using Low-resolution Smart Meter Data
    Liang, Ming
    Meng, Yao
    Lu, Ning
    Lubkeman, David
    Kling, Andrew
    [J]. 2019 IEEE POWER & ENERGY SOCIETY INNOVATIVE SMART GRID TECHNOLOGIES CONFERENCE (ISGT), 2019,
  • [35] Power Usage Spike Detection using Smart Meter Data for Load Profiling
    Wang, Qingmai
    Yu, Xinghuo
    Chou, Pauline
    Savage, David
    Zhang, Xiuzhen
    Zhong, Jiangxia
    [J]. PROCEEDINGS 2016 IEEE 25TH INTERNATIONAL SYMPOSIUM ON INDUSTRIAL ELECTRONICS (ISIE), 2016, : 732 - 737
  • [36] Demand Side Load Management using GSM enabled Smart Energy Meter
    Jaiswal, Supriya
    Ballal, M. S.
    Kashif, Syed M.
    Meena, Ramavatar
    [J]. 2017 7TH INTERNATIONAL CONFERENCE ON POWER SYSTEMS (ICPS), 2017, : 49 - 54
  • [37] State estimation of medium voltage distribution networks using smart meter measurements
    Al-Wakeel, Ali
    Wu, Jianzhong
    Jenkins, Nick
    [J]. APPLIED ENERGY, 2016, 184 : 207 - 218
  • [38] Automating Energy Demand Modeling and Forecasting Using Smart Meter Data
    Amin, Poojitha
    Cherkasova, Ludmila
    Aitken, Rob
    Kache, Vikas
    [J]. 2019 IEEE INTERNATIONAL CONGRESS ON INTERNET OF THINGS (IEEE ICIOT 2019), 2019, : 133 - 137
  • [39] SECURE SMART METER INFRASTRUCTURE IN MULTI-DWELLING ENVIRONMENT
    Vaidya, Binod
    Makrakis, Dimitrios
    Mouftah, Hussein
    [J]. 2012 25TH IEEE CANADIAN CONFERENCE ON ELECTRICAL & COMPUTER ENGINEERING (CCECE), 2012,
  • [40] Development of a smart electricity meter for households based on existing infrastructure
    Perekalskiy, I. N.
    Kokin, S. E.
    [J]. 2020 4TH INTERNATIONAL WORKSHOP ON RENEWABLE ENERGY AND DEVELOPMENT (IWRED 2020), 2020, 510