Detection of Power Quality Disturbances in the Utility Grid using Stockwell Transform

被引:0
|
作者
Sharma, Ankit Kumar [1 ]
Mahela, Om Prakash [2 ]
Ola, Sheesh Ram [1 ]
机构
[1] Apex Inst Engn & Technol, Jaipur, Rajasthan, India
[2] Indian Inst Technol, Jodhpur, Rajasthan, India
关键词
Power quality; power system; MATLAB/Simulink; transmission line; Stockwell transform; WAVELET; CLASSIFICATION; DECOMPOSITION;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Recently the open-access and competitive market power policy has been adopted by the utilities. Now, the electricity consumers are in a position to demand and expect a higher quality of service. The utilities and power providers have to provide a high quality of service to remain competitive as well as to retain or attract the customers. To achieve this goal an efficient power quality (PQ) monitoring and analysis system is required. This paper presents an S-transform based technique for the detection of power system operational events and power quality disturbances associated with these events. The power quality disturbances associated with the power system operational events such as switching on and off the loads, switching on and off the capacitor banks, tripping and reclosing the transmission lines, outage of the generator and utility network has been investigated effectively. The detailed simulation study of power quality disturbances has been carried out in MAT LAB/Simulink environment.
引用
收藏
页数:5
相关论文
共 50 条
  • [41] Voltage-Based Hybrid Algorithm Using Parameter Variations and Stockwell Transform for Islanding Detection in Utility Grids
    Mahela, Om Prakash
    Sharma, Yagya
    Ali, Shoyab
    Khan, Baseem
    Garg, Akhil Ranjan
    INFORMATICS-BASEL, 2021, 8 (02):
  • [42] Transient Disturbances and Islanding Detection in Micro Grid using Discrete Wavelet Transform
    Banerjee, Sannistha
    Bhowmik, Partha Sarathee
    2020 IEEE CALCUTTA CONFERENCE (CALCON), 2020, : 396 - 401
  • [43] A Comprehensive Overview on Modified Versions of Stockwell Transform For Power Quality Monitoring
    Kumar, Rajat
    Saxena, Abhinav
    Kumar, Raj
    Marwaha, Sanjay
    Singh, Jay
    Singh, Gyanendra Kumar
    IEEE ACCESS, 2022, 10 : 91963 - 91975
  • [44] Efficient automated detection of power quality disturbances using nonsubsampled contourlet transform & PCA-SVM
    Sinha, Pampa
    Paul, Kaushik
    Mohanty, Asit
    Elzein, Im
    Mishra, Chandra Sekhar
    Mahmoud, Mohamed Metwally
    Mbadjoun Wapet, Daniel Eutyche
    Al Ayidh, Abdulrahman
    Althobaiti, Ahmed
    Hussein, Hany S.
    Alghamdi, Thamer A. H.
    Ewais, Ahmed M.
    ENERGY EXPLORATION & EXPLOITATION, 2025,
  • [45] Detection and Classification of Complex Power Quality Disturbances Using Hilbert Transform and Rule Based Decision Tree
    Saini, Rahul
    Mahela, Om Prakash
    Sharma, Deepak
    2018 IEEE 8TH POWER INDIA INTERNATIONAL CONFERENCE (PIICON), 2018,
  • [46] Detection and classification of power quality disturbances using parallel neural networks based on discrete wavelet transform
    Garousi, Maryam Rahmati
    Shakarami, Mahmoud Reza
    Namdari, Farhad
    JOURNAL OF ELECTRICAL SYSTEMS, 2016, 12 (01) : 158 - 173
  • [47] Detection and Analysis of Power System Faults in the Presence of Wind Power Generation Using Stockwell Transform Based Median
    Ola, Sheesh Ram
    Saraswat, Amit
    Goyal, Sunil Kumar
    Jhajharia, S. K.
    Mahela, Om Prakash
    INTELLIGENT COMPUTING TECHNIQUES FOR SMART ENERGY SYSTEMS, 2020, 607 : 319 - 329
  • [48] Detection of Power Quality Disturbances Using Symbolic Dynamics
    Gupta, Manoj
    Kumar, Rajesh
    2014 RECENT ADVANCES AND INNOVATIONS IN ENGINEERING (ICRAIE), 2014,
  • [49] Automated detection of microaneurysms using Stockwell transform and statistical features
    Deepa, V.
    Kumar, C. Sathish
    Andrews, Sheena Susan
    IET IMAGE PROCESSING, 2019, 13 (08) : 1341 - 1348
  • [50] Energy operator and wavelet transform approach to online detection of power quality disturbances
    Huang, Wenqing
    Dai, Yuxing
    2006 8TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING, VOLS 1-4, 2006, : 3035 - +