Soft Transformer Energization: Ramping Time Estimation Method for Inrush Current Mitigation

被引:1
|
作者
Alassi, Abdulrahman [1 ,2 ]
Ahmed, Khaled [2 ]
Egea-Alvarez, Agusti [2 ]
Foote, Colin [3 ]
机构
[1] Iberdrola Innovat Midde East, Doha, Qatar
[2] Univ Strathclyde, Glasgow, Lanark, Scotland
[3] ScottishPower Energy Networks, Glasgow, Lanark, Scotland
关键词
power transformers; soft energization; voltage ramp; MATLAB/Simulink; CURRENT REDUCTION; PART I;
D O I
10.1109/UPEC50034.2021.9548203
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
Uncontrolled transformer energization is known to cause high magnitude inrush currents that can reach up to 10 times transformer rating. Several techniques are proposed in literature to mitigate this issue, including soft transformer energization using a voltage ramp. This technique is regaining more traction with the increased use of converters-based generation. Defining the required voltage ramping time for effective inrush current mitigation is important to avoid fast ramps that can still cause large inrush currents. This paper proposes a model-based ramping time estimation technique that can be used to identify the minimum-adequate voltage ramp time for a given set of constraints, transformer model and network configuration. Key ramping time influencing factors are defined as: residual flux, source to energized core effective impedance and control, in addition to core saturation characteristics. The proposed method considers multiple simulation steps to identify the minimum required ramping time. Simulation case study is presented for a voltage source energization of a 53 MVA three-phase delta-wye transformer, demonstrating the technique capability of determining appropriate ramping times for effective inrush current mitigation. Sensitivity analysis are also carried out to illustrate the impact of varying key parameters such as the transformer core saturation characteristics on the results.
引用
收藏
页数:6
相关论文
共 50 条
  • [41] Inrush current method of transformer based on wavelet packet and neural network
    Wang, Wei
    Yang, Lin
    Jin, Tao
    Liu, Hong
    Hu, Fan
    Wu, Dongxun
    JOURNAL OF ENGINEERING-JOE, 2019, (16): : 1257 - 1260
  • [43] Experimental study of transformer residual flux and the method of restraining inrush current
    Hase, Yoshihide
    Kamesawa, Tomoyuki
    Inoue, Shinji
    Yamamura, Shunichiro
    IEEJ Transactions on Power and Energy, 2013, 133 (07) : 606 - 615
  • [44] Mitigation of transformer-energizing inrush current using grid-connected photovoltaic system
    Ahmed, Abdelsalam A.
    Abdelsalam, Hany A.
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2016, 79 : 312 - 321
  • [45] Research on Real Time Simulation and Protection Test of Power Transformer Inrush Current
    Liu, Jun
    Xiao, Shiwu
    Liang, Xiaojiao
    Liu, Huanju
    Zou, Hao
    PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON ELECTROMECHANICAL CONTROL TECHNOLOGY AND TRANSPORTATION, 2015, 41 : 111 - 115
  • [46] A new method to identify inrush current based on error estimation
    He, Benteng
    Zhang, Xuesong
    Bo, Zhiqian Q.
    IEEE TRANSACTIONS ON POWER DELIVERY, 2006, 21 (03) : 1163 - 1168
  • [47] Effective suppression method of three-phase transformer's inrush current
    Cheng, CL
    Lin, CE
    Hou, KC
    Hsia, YF
    2002 IEEE REGION 10 CONFERENCE ON COMPUTERS, COMMUNICATIONS, CONTROL AND POWER ENGINEERING, VOLS I-III, PROCEEDINGS, 2002, : 2030 - 2033
  • [48] Transformer excitation inductance calculation and inrush current identification method by filtering the zero sequence current
    Guangxi University, Nanning 530004, China
    不详
    Dianli Xitong Zidonghue, 2008, 11 (30-33+65): : 30 - 33
  • [49] Flux Estimation Techniques for Inrush Current Mitigation of Line-Interactive UPS Systems
    Chen, Yu-Hsing
    Cheng, Po-Tai
    IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 2011, 47 (02) : 901 - 911
  • [50] Research method of identifying transformer inrush current and fault current based on VMD-HHT
    Jiao, Shangbin
    Chang, Yuan
    Zhang, Qing
    PROCEEDINGS OF THE 38TH CHINESE CONTROL CONFERENCE (CCC), 2019, : 7340 - 7345