Islanding Detection Technique based on Karl Pearson’s Coefficient of Correlation for Distribution Network with High Penetration of Distributed Generations
-
Karan Sareen
,
Bhavesh R Bhalja
Abstract
This article proposes a new Karl Pearson’s coefficient of correlation (‘r’) based islanding detection scheme which utilizes negative sequence voltage and voltage unbalance signal. In order to check the legitimacy of the proposed technique, large numbers of non-islanding and islanding events are generated by modeling IEEE 34-bus network. This scheme detects islanding situation even under 0 % power mis-match condition and thus, reduces the non detection zone (NDZ). Furthermore, the proposed technique detects islanding situation quickly as well as remains stable during the critical non-islanding situation like faults on adjoining feeder having varying location and fault resistance. Moreover, the proposed technique remains immune to variation in external system condition and fundamental frequency. The performance of the proposed technique is comprehensively compared with the schemes currently reported in the literature. This comparison apparently demonstrates the benefits of the proposed technique over existing schemes.
Appendix
| 1. Synchronous Generators Parameters | |
| Rated RMS Line-to-Neutral voltage(Vrms) | : 0.133 [kV] |
| Rated RMS Line current (Irms) | : 2.510 [kA] |
| Base Angular Frequency (ω) | : 314.15[rad] |
| Inertia Constant (H) | : 3.117[s] |
| Mechanical Friction and windage (Dm) | : 0.04 [pu] |
| Neutral Series Resistance (Rs) | : 1.0E5[pu] |
| Neutral Series Reactance (Xs) | : 0 [pu] |
| Iron Loss Resistance (Rm) | : 0.5 [pu] |
| Exciter Parameters | |
| Rectifier smoothing time constant (T1) | : 0.02 [s] |
| Controller lead time constant (TA) | : 0.12 [s] |
| Controller lag time constant (TB) | : 0.07 [s] |
| Exciter time constant (TE) | : 0.02 [s] |
| Exciter gain (K) | : 100[pu] |
| Maximum field voltage (EMAX) | : 5 [pu] |
| Minimum field voltage (EMIN) | : -5[pu] |
| L-G Voltage base (KV,RMS) | : 0.133 [kV] |
| Line current base (KA, RMS) | : 2.510 [kA] |
| 2. Solar Panel Parameters | |
| Rated Line-to-Neutral voltage (Vrms) at the output terminal of inverter | :0.133 [kV] |
| Rated RMS Line current (Irms) at the output terminal of inverter | :1.250 [kA] |
| Solar Radiation | :622.222[Watt/ m2] |
| Temperature | : 50 [0C] |
| DC bus voltage at the input terminal of three-phase inverter | : 0.500 [kV] |
| DC voltage at input terminal of step down chopper (or at the output terminal of PV array) | : 1.100 [kV] |
| DC current at input terminal of step down chopper (or at the output terminal of PV array) | : 0.13 [kA] |
References
[1] IEEE Standard 1547-2003:Interconnecting distributed resources in to electric power systems, July 2003.Search in Google Scholar
[2] Xu W, Zhang G, Li C, Wang W, Wang G, Kliber J. A power line signaling based technique for anti-islanding protection of distributed generators-part i: scheme and analysis. IEEE Trans Power Deliv. 2007;22(3):1758–66.10.1109/TPWRD.2007.899618Search in Google Scholar
[3] Wang G, Kliber J, Zhang G, Xu W, Howell B, Palladino T. A power line signaling based technique for anti-islanding protection of distributed generators-part ii: field test results. IEEE Trans Power Deliv. 2007;22(3):1767–72.10.1109/TPWRD.2007.899620Search in Google Scholar
[4] Hosani MA, Qu Z, Zeineldin HH. A transient stiffness measure for islanding detection of Multi-DG systems. IEEE Trans Power Delivery. 2015;30(2):986–95.10.1109/TPWRD.2014.2360876Search in Google Scholar
[5] Menon V, Nehrir MH. A hybrid islanding detection technique using voltage unbalance and frequency set point. IEEE Trans Power Syst. 2007;22(1):442–48.10.1109/TPWRS.2006.887892Search in Google Scholar
[6] Freitas W, Xu W, Affonso CM, Huang Z. Comparative analysis between ROCOF and vector surge relays for distributed generation applications. IEEE Trans Power Deliv. 2005;20(2):1315–24.10.1109/TPWRD.2004.834869Search in Google Scholar
[7] Mahat P, Chen Z, Bak-Jensen B. A hybrid islanding detection technique using average rate of voltage change and real power shift. IEEE Trans Power Deliv. 2009;24(2):764–71.10.1109/TPWRD.2009.2013376Search in Google Scholar
[8] Mohammadzadeh Niaki AH, Afsharnia S. A new passive islanding detection method and its performance evaluation for multi-DG systems. Electr Power Syst Res. 2014;110:180–87.10.1016/j.epsr.2014.01.016Search in Google Scholar
[9] Shah PH, Bhalja BR. A new rate of change of impedance-based islanding detection scheme in presence of distributed generation. Electric Power Compon Syst. 2014;42(7):1172–80.10.1080/15325008.2014.921951Search in Google Scholar
[10] Liu N, Abdualah A, Chris D, Chang L, Su J. Passive islanding detection approach based on tracking the frequency dependent impedance change. IEEE Trans Power Deliv. 2015 ;30(6):2570–80.10.1109/TPWRD.2015.2418580Search in Google Scholar
[11] Samantary SR, Samui A, Chitti Babu B. Time frequency transform based islanding detection in distributed generation. IET Renewable Power Gener. 2011 June;5(6):431–38.10.1049/iet-rpg.2010.0166Search in Google Scholar
[12] Hanif M, Basu M, Gaughan K. Development of EN50438 compliant wavelet based islanding detection technique for three-phase static distributed generation systems. IET Renewable Power Gener. 2012 ;6(4):289–301.10.1049/iet-rpg.2011.0290Search in Google Scholar
[13] Ray PK, Kishor N, Mohanty SR. Islanding and power quality disturbance detection in grid-connected hybrid power system using wavelet and S-transform. IEEE Trans Smart Grid. 2012;3(3):1082–94.10.1109/TSG.2012.2197642Search in Google Scholar
[14] Dash PK, Padhee M, Panigrahi TK. A hybrid time-frequency approach based fuzzy logic system for power islanding detection in grid connected distributed generation. Int J Electrical Power Energy Syst. 2012;42(1):453–64.10.1016/j.ijepes.2012.04.003Search in Google Scholar
[15] Samui A, Samantaray SR. Wavelet Singular Entropy based islanding detection in distributed generation. IEEE Trans Power Deliv. 2013;28(1):411–18.10.1109/TPWRD.2012.2220987Search in Google Scholar
[16] Alshareef S, Talwar S, Morsi WG. A new approach based on wavelet design and machine learning for islanding detection of distributed generation. IEEE Trans Smart Grid. 2014 ;5(4):1575–83.10.1109/TSG.2013.2296598Search in Google Scholar
[17] Mohanty SR, Kishor N, Ray PK, Catalão JPS. Comparative study of advanced signal processing techniques for islanding detection in a hybrid distributed generation system. IEEE Trans Sustainable Energy. 2015;6(1):122–31.10.1109/TSTE.2014.2362797Search in Google Scholar
[18] Khamis A, Shareef H, Mohamed A. Islanding detection and load shedding scheme for radial distribution systems integrated with dispersed generations. IET Gener Transm Distrib. 2015;9(4):1–15.10.1049/iet-gtd.2015.0263Search in Google Scholar
[19] Matic-Cuka B, Kezunovic M. Islanding detection for inverter-based distributed generation using support vector machine. IEEE Trans Smart Grid. 2014 ;5(6):2676–86.10.1109/TSG.2014.2338736Search in Google Scholar
[20] Laaksonen: H. Advanced islanding detection functionality for future electricity distribution networks. IEEE Trans Power Deliv. 2013;28(4):2056–64.10.1109/TPWRD.2013.2271317Search in Google Scholar
[21] Chen X, Li Y. An islanding detection algorithm for inverter-based distributed generation based on reactive power control. IEEE Trans Power Deliv. 2014;29(9):4672–83.10.1109/TPEL.2013.2284236Search in Google Scholar
[22] Bejmert D, Sidhu TS. Investigation into islanding detection with capacitor insertation-based method. IEEE Trans Power Deliv. 2014;29(6):2485–92.10.1109/TPWRD.2014.2347032Search in Google Scholar
[23] Faqhruldin ON, El-Saadany EF, Zeineldin HH. Auniversal islanding detection technique for distributed generation using pattern recognition. IEEE Trans Smart Grid. 2014;5(4):1985–92.10.1109/TSG.2014.2302439Search in Google Scholar
[24] Liu X, Lavertuy DM, Best RJ, Li K, Morrow DJ, McLoone S. Principal component analysis of wide-area phasor measurements for islanding detection-a geometric view. IEEE Trans Power Deliv. 2015;30(2):976–85.10.1109/TPWRD.2014.2348557Search in Google Scholar
[25] Guo Y, Li K, Laverty DM, Xue Y. Synchrophasor based islanding detection for distributed generation systems using systematic principal component analysis approaches. IEEE Trans Power Deliv. 2015 December;30(6):2544–52.10.1109/TPWRD.2015.2435158Search in Google Scholar
[26] Anderson PM. Power system protection. New York: IEEE Press, 1999.10.1109/9780470545591Search in Google Scholar
[27] Upton Graham, Cook Ian. Dictionary of statistics. New York: Oxford University Press, 2008.10.1093/acref/9780199541454.001.0001Search in Google Scholar
[28] IEEE PES Distribution Test Feeders. Technical Report, IEEE PES Distribution System Analysis Subcommittee’s Distribution Test Feeder Working Group, 2010, http://ewh.ieee.org/soc/pes/dsacom/testfeeders/Search in Google Scholar
[29] ‘PSCAD/EMTDC user’s manual,’ version 4.2, Manitoba HVDC Research Centre, Winnipeg, MB, Canada, 2003.Search in Google Scholar
[30] Sareen K, Bhalja BR, Maheshwari RP. Universal islanding detection technique based on rate of change of sequence components of currents for distributed generations. IET Renewable Power Gener. 2016;10(2):228–37.10.1049/iet-rpg.2015.0157Search in Google Scholar
[31] Dryden I, Mardia K. Statistical shape analysis. vol. 4. Hoboken, NJ, USA: Wiley; 1998.Search in Google Scholar
[32] Kresta J, Young J, Mason R. Multivariate control charts for individual observations. Can J Chem Eng. 1991;69(1):35–47.10.1002/cjce.5450690105Search in Google Scholar
© 2018 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
- Optimal Phasor Measurement Unit Placement for Numerical Observability Using A Two-Phase Branch-and-Bound Algorithm
- Reinforcement of Topologically Weak Power Networks Through Network Structural Characteristics Theory
- Multi-Terminal High Voltage Direct Current Transmission System with DC Resonant Semiconductor Breakers
- Islanding Detection Technique based on Karl Pearson’s Coefficient of Correlation for Distribution Network with High Penetration of Distributed Generations
- Real Time Harmonic Mitigation Using Fuzzy Based Highly Reliable Three Dual-Buck Full-Bridge APF for Dynamic Unbalanced Load
- An Autonomous Residential Smart Distribution Board: A Panacea for Demand Side Energy Management for Non-Smart Grid Networks
- Droop based Demand Dispatch for Residential Loads in Smart Grid Application
- Asynchronous Method for Frequency Regulation by Dispersed Plug-in Electric Vehicles
- A New Hybrid Protection Algorithm for Protection of Power Transformer Based on Discrete Wavelet Transform and ANFIS Inference Systems
- Experimental Identification using Equivalent Circuit Model for Lithium-Ion Battery
- Fault Identification and Location for Distribution Network with Distributed Generations
- Investigation of the Influence of Direct Current Bias on Transformer Vibration
Articles in the same Issue
- Optimal Phasor Measurement Unit Placement for Numerical Observability Using A Two-Phase Branch-and-Bound Algorithm
- Reinforcement of Topologically Weak Power Networks Through Network Structural Characteristics Theory
- Multi-Terminal High Voltage Direct Current Transmission System with DC Resonant Semiconductor Breakers
- Islanding Detection Technique based on Karl Pearson’s Coefficient of Correlation for Distribution Network with High Penetration of Distributed Generations
- Real Time Harmonic Mitigation Using Fuzzy Based Highly Reliable Three Dual-Buck Full-Bridge APF for Dynamic Unbalanced Load
- An Autonomous Residential Smart Distribution Board: A Panacea for Demand Side Energy Management for Non-Smart Grid Networks
- Droop based Demand Dispatch for Residential Loads in Smart Grid Application
- Asynchronous Method for Frequency Regulation by Dispersed Plug-in Electric Vehicles
- A New Hybrid Protection Algorithm for Protection of Power Transformer Based on Discrete Wavelet Transform and ANFIS Inference Systems
- Experimental Identification using Equivalent Circuit Model for Lithium-Ion Battery
- Fault Identification and Location for Distribution Network with Distributed Generations
- Investigation of the Influence of Direct Current Bias on Transformer Vibration
