An islanding detection methodology combining decision trees and Sandia frequency shift for inverter-based distributed generations
Abstract
Distributed generations (DGs) for grid-connected applications require an accurate and reliable islanding detection methodology (IDM) for secure system operation. This paper presents an IDM for grid-connected inverter-based DGs. The proposed method is a combination of passive and active islanding detection techniques for aggregation of their advantages and elimination/minimisation of the drawbacks. In the proposed IDM, the passive method utilises critical system attributes extracted from local voltage measurements at target DG locations as well as employs decision tree-based classifiers for characterisation and detection of islanding events. The active method is based on Sandia frequency shift technique and is initiated only when the passive method is unable to differentiate islanding events from other system events. Thus, the power quality degradation introduced into the system by active islanding detection techniques can be minimised. Furthermore, a combination of active and passive techniques allows detection of islanding events under low power mismatch scenarios eliminating the disadvantage associated with the use of passive techniques alone. Finally, detailed case study results demonstrate the effectiveness of the proposed method in detection of islanding events under various power mismatch scenarios, load quality factors and in the presence of single or multiple grid-connected inverter-based DG units.
- Authors:
-
- Univ. of Tennessee, Knoxville, TN (United States)
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Rutgers Univ., Piscataway, NJ (United States)
- Publication Date:
- Research Org.:
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1394131
- Grant/Contract Number:
- AC05-00OR22725
- Resource Type:
- Accepted Manuscript
- Journal Name:
- IET Generation, Transmission, & Distribution
- Additional Journal Information:
- Journal Volume: 11; Journal Issue: 16; Journal ID: ISSN 1751-8687
- Publisher:
- Institution of Engineering and Technology
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 24 POWER TRANSMISSION AND DISTRIBUTION; power generation economics; distributed power generation; power grids; pattern classification; power supply quality; decision trees; power system security; invertors; islanding detection methodology; power mismatch scenario; Sandia frequency shift technique; load quality factor
Citation Formats
Azim, Riyasat, Li, Fangxing, Xue, Yaosuo, Starke, Michael, and Wang, Honggang. An islanding detection methodology combining decision trees and Sandia frequency shift for inverter-based distributed generations. United States: N. p., 2017.
Web. doi:10.1049/iet-gtd.2016.1617.
Azim, Riyasat, Li, Fangxing, Xue, Yaosuo, Starke, Michael, & Wang, Honggang. An islanding detection methodology combining decision trees and Sandia frequency shift for inverter-based distributed generations. United States. https://doi.org/10.1049/iet-gtd.2016.1617
Azim, Riyasat, Li, Fangxing, Xue, Yaosuo, Starke, Michael, and Wang, Honggang. Fri .
"An islanding detection methodology combining decision trees and Sandia frequency shift for inverter-based distributed generations". United States. https://doi.org/10.1049/iet-gtd.2016.1617. https://www.osti.gov/servlets/purl/1394131.
@article{osti_1394131,
title = {An islanding detection methodology combining decision trees and Sandia frequency shift for inverter-based distributed generations},
author = {Azim, Riyasat and Li, Fangxing and Xue, Yaosuo and Starke, Michael and Wang, Honggang},
abstractNote = {Distributed generations (DGs) for grid-connected applications require an accurate and reliable islanding detection methodology (IDM) for secure system operation. This paper presents an IDM for grid-connected inverter-based DGs. The proposed method is a combination of passive and active islanding detection techniques for aggregation of their advantages and elimination/minimisation of the drawbacks. In the proposed IDM, the passive method utilises critical system attributes extracted from local voltage measurements at target DG locations as well as employs decision tree-based classifiers for characterisation and detection of islanding events. The active method is based on Sandia frequency shift technique and is initiated only when the passive method is unable to differentiate islanding events from other system events. Thus, the power quality degradation introduced into the system by active islanding detection techniques can be minimised. Furthermore, a combination of active and passive techniques allows detection of islanding events under low power mismatch scenarios eliminating the disadvantage associated with the use of passive techniques alone. Finally, detailed case study results demonstrate the effectiveness of the proposed method in detection of islanding events under various power mismatch scenarios, load quality factors and in the presence of single or multiple grid-connected inverter-based DG units.},
doi = {10.1049/iet-gtd.2016.1617},
journal = {IET Generation, Transmission, & Distribution},
number = 16,
volume = 11,
place = {United States},
year = {Fri Jul 14 00:00:00 EDT 2017},
month = {Fri Jul 14 00:00:00 EDT 2017}
}
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Works referenced in this record:
A New Heuristic Optimization Algorithm: Harmony Search
journal, February 2001
- Zong Woo Geem, ; Loganathan, G. V.
- SIMULATION, Vol. 76, Issue 2
Predicting islanding operation of grid connected PV inverters
journal, January 2000
- Smith, G. A.; Onions, P. A.; Infield, D. G.
- IEE Proceedings - Electric Power Applications, Vol. 147, Issue 1
Islanding Detection Assessment of Multi-Inverter Systems With Active Frequency Drifting Methods
journal, January 2008
- Lopes, Luiz A. C.; Zhang, Yongzheng
- IEEE Transactions on Power Delivery, Vol. 23, Issue 1
Performance of the OVP/UVP and OFP/UFP Method With Voltage and Frequency Dependent Loads
journal, April 2009
- Zeineldin, H. H.; Kirtley, J. L.
- IEEE Transactions on Power Delivery, Vol. 24, Issue 2
An Islanding Detection Method for Distributed Generations Using Voltage Unbalance and Total Harmonic Distortion of Current
journal, April 2004
- Jang, S. -I.; Kim, K. -H.
- IEEE Transactions on Power Delivery, Vol. 19, Issue 2
Assessment of ROCPAD Relay for Islanding Detection in Distributed Generation
journal, June 2011
- Samui, Ankita; Samantaray, S. R.
- IEEE Transactions on Smart Grid, Vol. 2, Issue 2
Data Mining Approach to Threshold Settings of Islanding Relays in Distributed Generation
journal, August 2007
- El-Arroudi, Khalil; Joos, Geza
- IEEE Transactions on Power Systems, Vol. 22, Issue 3
Comparative Analysis Between ROCOF and Vector Surge Relays for Distributed Generation Applications
journal, April 2005
- Freitas, W.; Xu, W.; Affonso, C. M.
- IEEE Transactions on Power Delivery, Vol. 20, Issue 2
Intelligent-Based Approach to Islanding Detection in Distributed Generation
journal, April 2007
- El-Arroudi, Khalil; Joos, Gza; Kamwa, Innocent
- IEEE Transactions on Power Delivery, Vol. 22, Issue 2
A Hybrid Islanding Detection Technique Using Voltage Unbalance and Frequency Set Point
journal, February 2007
- Menon, Vivek; Nehrir, M. Hashem
- IEEE Transactions on Power Systems, Vol. 22, Issue 1
Synchronous Distributed Generation Islanding Protection Using Intelligent Relays
journal, December 2012
- Far, Hamed Golestani; Rodolakis, Anthony J.; Joos, Geza
- IEEE Transactions on Smart Grid, Vol. 3, Issue 4
Analysis and performance assessment of the active frequency drift method of islanding prevention
journal, January 1999
- Ropp, M. E.; Begovic, M.; Rohatgi, A.
- IEEE Transactions on Energy Conversion, Vol. 14, Issue 3
Radial distribution test feeders
journal, January 1991
- Kersting, W. H.
- IEEE Transactions on Power Systems, Vol. 6, Issue 3
Distributed generation islanding-implications on power system dynamic performance
conference, January 2002
- Walling, R. A.; Miller, N. W.
- IEEE PES Summer Meeting, IEEE Power Engineering Society Summer Meeting,
New loss of mains detection algorithm for embedded generation using rate of change of voltage and changes in power factors
conference, January 2001
- Salman, S. K.
- 7th International Conference on Developments in Power Systems Protection (DPSP 2001)
A Pattern Recognition Approach for Detecting Power Islands Using Transient Signals—Part I: Design and Implementation
journal, October 2010
- Lidula, N. W. A.; Rajapakse, A. D.
- IEEE Transactions on Power Delivery, Vol. 25, Issue 4
A decision tree based approach for microgrid islanding detection
conference, February 2015
- Azim, Riyasat; Zhu, Yongli; Saleem, Hira Amna
- 2015 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)
Instability criterion to eliminate the Non-Detection Zone of the Sandia Frequency Shift method
conference, March 2009
- Zeineldin, H. H.; Kennedy, S.
- 2009 IEEE/PES Power Systems Conference and Exposition (PSCE)
Works referencing / citing this record:
Islanding detection method based on S transform and ANFIS
journal, September 2018
- Yu, Songsen; Yin, Lulin
- Journal of Renewable and Sustainable Energy, Vol. 10, Issue 5
An Effective Passive Islanding Detection Algorithm for Distributed Generations
journal, August 2019
- Abyaz, Arash; Panahi, Habib; Zamani, Reza
- Energies, Vol. 12, Issue 16
A combined islanding detection algorithm for grid connected multiple microgrids for enhanced microgrid utilisation
journal, November 2019
- Radhakrishnan, Rohikaa Micky; Sankar, Ashok; Rajan, Sunitha
- International Transactions on Electrical Energy Systems, Vol. 30, Issue 2
Microgrid Islanding Detection Based on Mathematical Morphology
journal, October 2018
- Ghalavand, Fatemeh; Alizade, Behzad; Gaber, Hossam
- Energies, Vol. 11, Issue 10