Kalman Filter Based Approach for ZIP Load Modeling for Aggregate Loads

被引:2
|
作者
Zhang, Yiqi [1 ]
Liao, Yuan [1 ]
Jones, Evan [1 ]
Jewell, Nicholas [2 ]
Ionel, Dan M. [1 ]
机构
[1] Univ Kentucky, Dept Elect & Comp Engn, Lexington, KY 40506 USA
[2] LG&E & KU, Dept Elect Engn & Planning, Louisville, KY USA
关键词
Load model; ZIP load model; parameter estimation; Kalman filter;
D O I
10.1109/KPEC51835.2021.9446202
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Constant impedance, constant current, constant power (ZIP) load modeling has been used in various power system applications. It is of great interest to accurately estimate ZIP parameters. This paper presents the Kalman filtering based technique for estimating load ZIP parameters. In addition, aggregate load modeling is a common practice in utility companies. However, there are certain factors that can affect estimation results. This paper formulates the aggregate ZIP load modeling and provides insights into the effects of load connections and voltage unbalance on ZIP load modeling. The effects of voltage unbalance and load connection type on ZIP load estimation are illustrated through examples. Representative case studies based on the IEEE 34-bus system built in OpenDSS are reported.
引用
收藏
页数:6
相关论文
共 50 条
  • [1] ZIP load modeling for single and aggregate loads and CVR factor estimation
    Zhang, Yiqi
    Liao, Yuan
    Jones, Evan
    Jewell, Nicholas
    Ionel, Dan
    [J]. INTERNATIONAL JOURNAL OF EMERGING ELECTRIC POWER SYSTEMS, 2022, 23 (06) : 839 - 858
  • [2] Assessment of Conservation Voltage Reduction by Unscented Kalman Filter based Load Modeling
    Wang, Zhaoyu
    [J]. 2016 IEEE POWER AND ENERGY SOCIETY GENERAL MEETING (PESGM), 2016,
  • [3] A Kalman filter approach to traffic modeling and prediction
    Grindey, GJ
    Amin, SM
    Rodin, EY
    Garcia-Ortiz, A
    [J]. INTELLIGENT TRANSPORTATION SYSTEMS, 1998, 3207 : 234 - 241
  • [4] COMPONENT BASED AGGREGATE LOAD MODELLING OF MODERN LOADS
    Neupane, Pradip
    Silwal, Bishal
    Katuwal, Sagun
    Adhikary, Brijesh
    [J]. IFAC PAPERSONLINE, 2022, 55 (09): : 395 - 400
  • [5] An approach for fuzzy Kalman filter modeling based on evolving clustering of experimental data
    Pires, Danubia
    Serra, Ginalber
    [J]. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2018, 35 (02) : 1819 - 1834
  • [6] A Geometric Approach to Aggregate Flexibility Modeling of Thermostatically Controlled Loads
    Zhao, Lin
    Zhang, Wei
    Hao, He
    Kalsi, Karanjit
    [J]. IEEE Transactions on Power Systems, 2017, 32 (06) : 4721 - 4731
  • [7] Augmented Kalman filter based moving vehicle loads online identification
    Zhang, Chaodong
    Li, Jian'an
    Zhang, Hao
    [J]. Zhendong yu Chongji/Journal of Vibration and Shock, 2022, 41 (02): : 87 - 95
  • [8] Kalman-filter based estimation of electric load composition with non-ideal transformer modeling
    Lee, Soon
    Baek, Seung-Mook
    Park, Jung-Wook
    Moon, Young-Hyun
    [J]. IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES, 2007, E90A (12) : 2877 - 2883
  • [9] Speed and Load Torque Estimation of SPMSM based on Kalman Filter
    Wang, Hui
    Wang, Yunkuan
    Wang, Xinbo
    [J]. 2015 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION, 2015, : 808 - 813
  • [10] Improved Random Load Processing Algorithm Based on Kalman Filter
    Gu, Yong
    Zhu, Yun
    Zhu, Desong
    [J]. PROCEEDINGS OF THE 2015 INTERNATIONAL SYMPOSIUM ON COMPUTERS & INFORMATICS, 2015, 13 : 255 - 263