A REVIEW ON DETECTION AND CLASSIFICATION OF POWER QUALITY DISTURBANCES IN EMERGING POWER SYSTEM WITH DISTRIBUTED GENERATION

Authors

  • Ravishankar S. Kankale Assistant Professor Department of Electrical Engineering, SSGMCE, Shegaon
  • Sudhir R. Paraskar Professor & Head, Department of Electrical Engineering, SSGMCE, Shegaon
  • Saurabh S. Jadhao Assistant Professor Department of Electrical Engineering, SSGMCE, Shegaon

DOI:

https://doi.org/10.17605/OSF.IO/S3AZN

Keywords:

Distributed Generation, Power Quality Disturbances, Signal Processing Techniques, Artificial Intelligence Techniques

Abstract

Nowadays, the ever-increasing power demand is fed by using renewable energy-based distributed generation (DG). Most of the renewable energy sourced distributed generation is based on power electronic converters. The integration of such distributed generation in a conventional distribution network becomes a major source of power quality disturbances (PQDs). In an emerging power system, the power electronic converters in the DG system, non-linear loads, switching events, and various power system faults are the major causes of power quality disturbances. These disturbances causing problems such as malfunctioning or failure of end-user equipment. Hence, it is necessary to monitor the power quality disturbances. The ongoing research is now focused on this area. A lot of research literature is available in the area of power quality. Due to the high penetration of renewable energy-based DG, the classification of power quality disturbances in the emerging power system becomes an important issue. This paper presents a review of signal processing, feature extraction, and classification techniques used for the detection and classification of power quality disturbances in emerging power system with distributed generation. This information will help researchers working in this field. A comparison of various signal processing and artificial intelligence techniques used for monitoring of PQDs has been tabulated. Major issues and major challenges in classifying power quality disturbances are analyzed in-depth and presented. This review further explores the opportunities for new researchers in the field of power quality disturbances detection and classification.

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References

Y. Xu, Y. Gao, Z. Li and M. Lu, "Detection and Classification of Power Quality Disturbances in Distribution Networks Based on VMD and DFA," in CSEE Journal of Power and Energy Systems, vol. 6, no. 1, pp. 122-130, March 2020.

R. S. H., S. R. Mohanty, N. Kishor and A. T. K., "Real-Time Implementation of Signal Processing Techniques for Disturbances Detection," in IEEE Transactions on Industrial Electronics, vol. 66, no. 5, pp. 3550-3560, May 2019.

P. K. Ray, S. R. Mohanty and N. Kishor,"Classification of Power Quality Disturbances Due to Environmental Characteristics in Distributed Generation System," in IEEE Transactions on Sustainable Energy, vol. 4, no. 2, pp. 302-313, April 2013.

T. Chakravorti, R.K. Patnaik and P. K. Dash, "Detection and Classification of Islanding and Power Quality Disturbances in Microgrid using Hybrid Signal Processing and Data Mining Techniques," in IET Signal Processing, vol. 12, no. 1, pp. 82-94, 2 2018.

P. K. Ray, N. Kishor and S. R. Mohanty, "Islanding and Power Quality Disturbance Detection in Grid-Connected Hybrid Power System Using Wavelet and S-Transform,” in IEEE Transactions on Smart Grid, vol. 3, no. 3, pp. 1082-1094, Sept. 2012.

J. M. Sexauer and S. Mohagheghi, "Voltage Quality Assessment in a Distribution System with Distributed Generation-A Probabilistic Load Flow Approach," in IEEE Transactions on Power Delivery, vol. 28, no. 3, pp. 1652-1662, July 2013.

Y. Wang, A. Raza, F. P. Mohammed, J. Ravishankar and T. Phung, "Detection and Classification of Disturbances in the Islanded Micro-Grid by Using Wavelet Transformation and Feature Extraction Algorithm," in The Journal of Engineering, vol. 2019, no. 18, pp. 5284-5286, 7 2019.

P. D. Achlerkar, S. R. Samantaray and M. Sabarimalai Manikandan, "Variational Mode Decomposition and Decision Tree Based Detection and Classification of Power Quality Disturbances in Grid-Connected Distributed Generation System," in IEEE Transactions on Smart Grid, vol. 9, no. 4, pp. 3122-3132, July 2018.

P. K. Ray, S. R. Mohanty, N. Kishor and J. P. S. Catalão, "Optimal Feature and Decision Tree-Based Classification of Power Quality Disturbances in Distributed Generation Systems," in IEEE Transactions on Sustainable Energy, vol. 5, no. 1, pp. 200-208, Jan. 2014.

A. G. Shaik and O. P. Mahela, “Power Quality Assessment and Event Detection in Hybrid Power System,” in Electric Power Systems Research, Volume 161, August 2018, Pages 26-44.

B. Biswal and S. Mishra, "Power Signal Disturbance Identification and Classification using a Modified Frequency Slice Wavelet Transform," in IET Generation, Transmission & Distribution, vol. 8, no. 2, pp. 353-362, February 2014.

S. Pradhan, B. Singh and B. K. Panigrahi, "A Digital Disturbance Estimator (DDE) for Multiobjective Grid Connected Solar PV Based Distributed Generating System," in IEEE Transactions on Industry Applications, vol. 54, no. 5, pp. 5318-5330, Sept.-Oct. 2018.

P. K. Ray, Soumya R. Mohanty and N. Kishor, “Disturbance Detection in Grid-Connected Distributed Generation System Using Wavelet and S-Transform,” in Electric Power Systems Research, Volume 81, Issue 3, March 2011, Pages 805-819.

O. Cortes-Robles, E. Barocio, J. Segundo, D. Guillen and J.C. Olivares-Galvan, “A Qualitative-Quantitative Hybrid Approach for Power Quality Disturbance Monitoring on Microgrid Systems,” in Measurement, Volume 154, 15 March 2020, 107453.

Ghada S. Elbasuony, Shady H.E. Abdel Aleem, Ahmed M. Ibrahim and Adel M. Sharaf, “A Unified Index for Power Quality Evaluation in Distributed Generation Systems,” in Energy, Volume 149, 15 April 2018, Pages 607-622.

P. K. Dash, Malhar Padhee and S.K. Barik, “Estimation of Power Quality Indices in Distributed Generation Systems during Power Islanding Conditions,” in International Journal of Electrical Power & Energy Systems, Volume 36, Issue 1, March 2012, Pages 18-30.

M. Jasinski, T. Sikorski and K. Borkowski, “Clustering as a Tool to Support the Assessment of Power Quality in Electrical Power Networks with Distributed Generation in the Mining Industry,” in Electric Power Systems Research, Volume 166, January 2019, Pages 52-60.

T. Chakravorti, N.R. Nayak, R. Bisoi, P.K. Dash and L. Tripathi, “A New Robust Kernel Ridge Regression Classifier for Islanding and Power Quality Disturbances in a Multi Distributed Generation Based Microgrid,” in Renewable Energy Focus, Volume 28, March 2019, Pages 78-99.

S.Wang and H. Chen, “A Novel Deep Learning Method for the Classification of Power Quality Disturbances Using Deep Convolutional Neural Network,” in Applied Energy, Volume 235, 1 February 2019, Pages 1126-1140.

L. Lin, D.Wang, S. Zhao, L. Chen and N. Huang, "Power Quality Disturbance Feature Selection and Pattern Recognition Based on Image Enhancement Techniques," in IEEE Access, vol. 7, pp. 67889-67904, 2019.

M. Jaya Bharata Reddy, K. Sagar and D. K. Mohanta, "A Multifunctional Real-Time Power Quality Monitoring System using Stockwell Transform," in IET Science, Measurement & Technology, vol. 8, no. 4, pp. 155-169, July 2014.

C. B. Khadse, M. A. Chaudhari and V. B. Borghate, "A Laboratory Set-Up for Power Quality Disturbance Generator and Real Time Power Quality Monitoring," 2016 IEEE International WIE Conference on Electrical and Computer Engineering (WIECONECE), Pune, 2016, pp. 61-64.

S. H. Asman, A. Farid Abidin and M. A. Talib Mat Yusoh, "LabVIEW Implementation for Power Disturbances Classification," 2018 IEEE 7th International Conference on Power and Energy (PECon), Kuala Lumpur, Malaysia, 2018, pp. 123-127.

M. Nicola, C. Nicola, S. Popescu, D. Sacerdo¸tianu and M. Du¸t˘a, "Power Quality Analysis System Based on LabVIEW Real-Time and Reconfigurable FPGA Modules UsingWavelet Transform," 2018 International Conference on Applied and Theoretical Electricity (ICATE), Craiova, 2018, pp. 1-6.

Aleksandar M. Stanisavljevic, Vladimir A. Kati ´ c, Boris P. Dumni ´ c and Bane P. ´ Popadic, “A Comprehensive Overview of Digital Signal Processing Methods for ´ Voltage Disturbance Detection and Analysis in Modern Distribution Grids with Distributed Generation,” in Acta Polytechnica Hungarica. 16. 2019-125.

S. Khokhar, A. A. B. M. Zin, A. S. B. Mokhtar and M. Pesaran, “A Comprehensive Overview on Signal Processing and Artificial Intelligence Techniques Applications in Classification of Power Quality Disturbances,” in Renewable and Sustainable Energy Reviews, Volume 51, November 2015, Pages 1650-1663.

O. Palizban, K. Kauhaniemi and J. M. Guerrero, “Microgrids in Active Network Management – Part II System Operation, Power Quality and Protection,” in Renewable and Sustainable Energy Reviews, Volume 36, August 2014, Pages 440-451.

M. Mishra, “Power Quality Disturbance Detection and Classification using Signal Processing and Soft Computing Techniques: A Comprehensive Review,” in International Transactions on Electrical Energy Systems, March 2019.

E. Hossain, M. R. Tür, S. Padmanaban, S. Ay and I. Khan, "Analysis and Mitigation of Power Quality Issues in Distributed Generation Systems Using Custom Power Devices," in IEEE Access, vol. 6, pp. 16816-16833, 2018.

R. Dugan, M. McGranaghan, S. Santoso and H. W. Beaty, “Electrical Power Systems Quality,” third Edition, McGraw-Hill Education, New York, 2012.

O. Ellabban, H. Abu-Rub, and F. Blaabjerg, “Renewable energy resources: Current status, future prospects and their enabling technology,” Renewable and Sustainable Energy Reviews, vol. 39, pp. 748–764, 2014.

Y. Han, Y. Feng, P. Yang, L. Xu, Y. Xu, and F. Blaabjerg, “Cause, classification of voltage sag, and voltage sag emulators and applications: A comprehensive overview,” IEEE Access, 2019.

M. D. Borrás, J. C. Bravo, and J. C. Montaño, “Disturbance ratio for optimal multi-event classification in power distribution networks,” IEEE Transactions on Industrial Electronics, vol. 63, no. 5, pp. 3117–3124, 2016.

S. D. Ahmed, F. S. M. Al-Ismail, M. Shafiullah, F. A. Al-Sulaiman, and I. M. El-Amin, “Grid integration challenges of wind energy: A review,” IEEE Access, vol. 8, pp. 10 857–10 878, 2020.

H. Shareef, A. Mohamed, and A. A. Ibrahim, “An image processing-based method for power quality event identification,” International Journal of Electrical Power & Energy Systems, vol. 46, pp. 184–197, 2013.

H. JIANG, Y. ZHENG, Z. WANG, L. CHEN, and J. PENG, “An image processing-based method for transient power quality classification,” Power System Protection and Control, vol. 43, no. 13, pp. 72–78, 2015.

L. Lin, D. Wang, S. Zhao, L. Chen, and N. Huang, “Power quality disturbance feature selection and pattern recognition based on image enhancement techniques,” IEEE Access, vol. 7, pp. 67 889–67 904, 2019.

D. Granados-Lieberman, R. Romero-Troncoso, R. Osornio-Rios, A. Garcia-Perez, and E. Cabal-Yepez, “Techniques and methodologies for power quality analysis and disturbances classification in power systems: a review,” IET Generation, Transmission & Distribution, vol. 5, no. 4, pp. 519–529, 2011.

M. K. Saini and R. Kapoor, “Classification of power quality events–a review,” International Journal of Electrical Power & Energy Systems, vol. 43, no. 1, pp. 11–19, 2012.

O. P. Mahela, A. G. Shaik, and N. Gupta, “A critical review of detection and classification of power quality events,” Renewable and Sustainable Energy Reviews, vol. 41, pp. 495–505, 2015.

S. Avdakovic, A. Nuhanovic, M. Kusljugic, and M. Music, “Wavelet transform applications in power system dynamics,” Electric Power Systems Research, vol. 83, no. 1, pp. 237–245, 2012.

S. Khokhar, A. A. B. M. Zin, A. S. B. Mokhtar, and M. Pesaran, “A comprehensive overview on signal processing and artificial intelligence techniques applications in classification of power quality disturbances,” Renewable and Sustainable Energy Reviews, vol. 51, pp. 1650–1663, 2015.

R. X. Abhijith Augustine, Ruban Deva Prakash and M. C. Parassery, “Review of signal processing techniques for detection of power quality events,” American Journal of Engineering and Applied Sciences, vol. 9, pp. 364–370, 2016.

S. Vyas, R. Kumar, and R. Kavasseri, “Data analytics and computational methods for anti-islanding of renewable energy based distributed generators in power grids,” Renewable and Sustainable Energy Reviews, vol. 69, pp. 493–502, 2017.

O. A. Alimi, K. Ouahada, and A. M. Abu-Mahfouz, “A review of machine learning approaches to power system security and stability,” IEEE Access, vol. 8, pp. 113 512–113 531, 2020.

X. Liang, “Emerging power quality challenges due to integration of renewable energy sources,” IEEE Transactions on Industry Applications, vol. 53, no. 2, pp. 855–866, 2016.

G. S. Chawda and A. G. Shaik, “Performance evaluation of Adaline controlled dstatcom for multifarious load in weak ac grid,” in 2019 IEEE PES GTD Grand International Conference and Exposition Asia (GTD Asia), 2019, pp. 356–361.

G. S. Chawda, O. P. Mahela, N. Gupta, M. Khosravy, and T. Senjyu, “Incremental conductance-based particle swarm optimization algorithm for global maximum power tracking of solar-pv under nonuniform operating conditions,” Applied Sciences, vol. 10, no. 13, p. 4575, 2020.

A. Q. Al-Shetwi, M. Hannan, K. P. Jern, M. Mansur, and T. Mahlia, “Grid-connected renewable energy sources: Review of the recent integration requirements and control methods,” Journal of Cleaner Production, vol. 253, p. 119831, 2020.

O. P. Mahela, B. Khan, H. H. Alhelou, and P. Siano, “Power quality assessment and event detection in distribution network with wind energy penetration using stockwell transform and fuzzy clustering,” IEEE Transactions on Industrial Informatics, vol. 16, no. 11, pp. 6922–6932, 2020.

A. G. Shaik and O. P. Mahela, “Power quality assessment and event detection in hybrid power system,” Electric Power Systems Research, vol. 161, pp. 26–44, 2018.

O. P. Mahela and A. G. Shaik, “Power quality recognition in distribution system with solar energy penetration using s-transform and fuzzy cmeans clustering,” Renewable energy, vol. 106, pp. 37–51, 2017.

O. P. Mahela, B. Khan, H. H. Alhelou, and S. Tanwar, “Assessment of power quality in the utility grid integrated with wind energy generation,” IET Power Electronics, 2020.

G. S. Chawda and A. G. Shaik, “Smooth grid synchronization in weak ac grid with high wind energy penetration using distribution static compensator,” in 2019 2nd International Conference on Smart Grid and Renewable Energy (SGRE). IEEE, 2019, pp. 1–6.

C. Li and R. Reinmuller, “Open phase detection in der operation by using power quality data analytics,” IEEE Transactions on Power Delivery, pp. 1–1, 2020.

D. Pal and B. K. Panigrahi, “Analysis and mitigation of the impact of ancillary services on anti-islanding protection of distributed generators,” IEEE Transactions on Sustainable Energy, pp. 1–1, 2020.

A. A. Abdelsalam, A. A. Salem, E. S. Oda, and A. A. Eldesouky, “Islanding detection of microgrid incorporating inverter based dgs using long short-term memory network,” IEEE Access, vol. 8, pp. 106 471– 106 486, 2020.

H. J. Green and T. Wind, “The ieee grid interconnection standard: How will it affect wind power?” National Renewable Energy Lab., Golden, CO (US), Tech. Rep., 2000.

T. Lin and A. Domijan, “On power quality indices and real time measurement,” IEEE Transactions on power delivery, vol. 20, no. 4, pp. 2552– 2562, 2005.

G. S. Chawda et al., "Comprehensive Review on Detection and Classification of Power Quality Disturbances in Utility Grid with Renewable Energy Penetration," in IEEE Access, vol. 8, pp. 146807-146830, 2020, doi: 10.1109/ACCESS.2020.3014732.

S. De and S. Debnath, “Real-time cross-correlation-based technique for detection and classification of power quality disturbances,” IET Generation, Transmission & Distribution, vol. 12, no. 3, pp. 688–695, 2017.

A. F. Bastos and S. Santoso, “Universal waveshape-based disturbance detection in power quality data using similarity metrics,” IEEE Transactions on Power Delivery, 2019.

M. Garrido, “The feedforward short-time fourier transform,” IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 63, no. 9, pp. 868–872, 2016.

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Published

10-04-2021

How to Cite

[1]
Ravishankar S. Kankale, Sudhir R. Paraskar, and Saurabh S. Jadhao, “A REVIEW ON DETECTION AND CLASSIFICATION OF POWER QUALITY DISTURBANCES IN EMERGING POWER SYSTEM WITH DISTRIBUTED GENERATION”, IEJRD - International Multidisciplinary Journal, vol. 6, no. ICMRD21, p. 14, Apr. 2021.