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Protection and Monitoring of Digital Energy Systems Operation

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Energy Systems Transition

Part of the book series: Power Systems ((POWSYS))

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Abstract

Digital transition of energy systems encloses all major parts of the electric grids, including power system protection and monitoring. This chapter first accurately reviews the basics of smart microgrid protection since the definitions vary from a reference to another. Then it focuses on the fault responses of inverter-based resources (IBRs), as those are emerging technologies that will be playing the great role of interfacing primary energy resources and the grid. In particular, for materialization of net-zero carbon emission in electricity generation, the use of IBRs is indispensable. However, the non-universal and software-defined IBR fault responses make conventional relays such as overcurrent, directional, and distance relays inapplicable in heavily IBR-based grids. Therefore, the discrepancy between conventional and IBR fault responses is elaborated, and possible solutions to the looming protection issues are discussed. The shortcomings and merits of each solution are also discussed.

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References

  1. Mahmood A, Javaid N, Razzaq S (2015) A review of wireless communications for smart grid. Renew Sust Energ Rev 41:248–260. https://doi.org/10.1016/j.rser.2014.08.036

    Article  Google Scholar 

  2. Gao J et al (2018) Grid monitoring: secured sovereign blockchain based monitoring on smart grid. IEEE Access 6:9917–9925. https://doi.org/10.1109/ACCESS.2018.2806303

    Article  Google Scholar 

  3. Alagoz BB, Kaygusuz A, Karabiber A (2012) A user-mode distributed energy management architecture for smart grid applications. Energy 44(1):167–177. https://doi.org/10.1016/j.energy.2012.06.051

    Article  Google Scholar 

  4. Ci S, Lin N, Zhou Y, Li H, Yang Y. A new digital power supply system for Fog and Edge computing. In: 2018 14th International Wireless Communications & Mobile Computing Conference (IWCMC), 25–29 June 2018, pp 1513–1517. https://doi.org/10.1109/IWCMC.2018.8450497

  5. Manohar M, Koley E, Ghosh S (2018) Microgrid protection under wind speed intermittency using extreme learning machine. Comput Electr Eng 72:369–382. https://doi.org/10.1016/j.compeleceng.2018.10.005

    Article  Google Scholar 

  6. Rehmani MH, Reisslein M, Rachedi A, Erol-Kantarci M, Radenkovic M (2018) Integrating renewable energy resources into the smart grid: recent developments in information and communication technologies. IEEE Trans Ind Inf 14(7):2814–2825. https://doi.org/10.1109/TII.2018.2819169

    Article  Google Scholar 

  7. Jalilzadeh Hamidi R, Ahmadian A, Patil R, Asadinejad A (2019) Optimal time-current graded coordination of multistage inverse-time overcurrent relays in distribution networks. Int Trans Electr Energy Syst 29(5):e2841. https://doi.org/10.1002/2050-7038.2841

    Article  Google Scholar 

  8. Hamidi RJ, Livani H (2019) A recursive method for traveling-wave arrival-time detection in power systems. IEEE Trans Power Delivery 34(2):710–719. https://doi.org/10.1109/TPWRD.2018.2877705

    Article  Google Scholar 

  9. Department of Energy’s Advanced Grid Research and Development. https://www.smartgrid.gov/adms_research_and_development (accessed)

  10. Li C, Rakhra P, Norman P, Niewczas P, Burt G, Clarkson P (2020) Modulated low fault-energy protection scheme for DC smart grids. IEEE Trans Smart Grid 11(1):84–94. https://doi.org/10.1109/TSG.2019.2917540

    Article  Google Scholar 

  11. Rahman Fahim S, Sarker SK, Muyeen SM, Sheikh MRI, Das SK (2020) Microgrid fault detection and classification: machine learning based approach, comparison, and reviews. Energies 13(13):3460. [Online]. Available: https://www.mdpi.com/1996-1073/13/13/3460

    Article  Google Scholar 

  12. Lotfifard S, Faiz J, Kezunovic M (2012) Over-current relay implementation assuring fast and secure operation in transient conditions. Electr Power Syst Res 91:1–8. https://doi.org/10.1016/j.epsr.2012.02.001

    Article  Google Scholar 

  13. Yousaf M, Muttaqi KM, Sutanto D (2021) A control strategy to mitigate the sensitivity deterioration of overcurrent protection in distribution networks with the higher concentration of the synchronous and inverter-based DG units. IEEE Trans Ind Appl 57(3):2298–2306. https://doi.org/10.1109/TIA.2021.3057304

    Article  Google Scholar 

  14. Pandya HS, Pandeji DM, Iyer RK, Purohit PM. Digital protection strategy of microgrid with relay time grading using particle swarm optimization. In: 2015 5th Nirma University International Conference on Engineering (NUiCONE), 26–28 Nov 2015, pp 1–6. https://doi.org/10.1109/NUICONE.2015.7449612

  15. Guo L, Ye C, Ding Y, Wang P (2021) Allocation of centrally switched fault current limiters enabled by 5G in transmission system. IEEE Trans Power Delivery 36(5):3231–3241. https://doi.org/10.1109/TPWRD.2020.3037193

    Article  Google Scholar 

  16. Nikolaidis VC, Tsimtsios AM, Safigianni AS (2018) Investigating particularities of infeed and fault resistance effect on distance relays protecting radial distribution feeders with DG. IEEE Access 6:11301–11312. https://doi.org/10.1109/ACCESS.2018.2804046

    Article  Google Scholar 

  17. Biswas S, Centeno V. A communication based infeed correction method for distance protection in distribution systems. In: 2017 North American Power Symposium (NAPS), 17–19 Sept 2017, pp 1–5. https://doi.org/10.1109/NAPS.2017.8107226

  18. Usama M et al (2021) A comprehensive review on protection strategies to mitigate the impact of renewable energy sources on interconnected distribution networks. IEEE Access 9:35740–35765. https://doi.org/10.1109/ACCESS.2021.3061919

    Article  Google Scholar 

  19. IEEE standard for interconnection and interoperability of distributed energy resources with associated electric power systems interfaces – Redline. In: IEEE Std 1547-2018 (Revision of IEEE Std 1547-2003) – Redline, 2018, pp 1–227

    Google Scholar 

  20. IEEE application guide for IEEE Std 1547(TM), IEEE standard for interconnecting distributed resources with electric power systems. In: IEEE Std 1547.2-2008, 2009, pp 1–217. https://doi.org/10.1109/IEEESTD.2008.4816078

  21. Makwana YM, Bhalja BR (2019) Experimental performance of an islanding detection scheme based on modal components. IEEE Trans Smart Grid 10(1):1025–1035. https://doi.org/10.1109/TSG.2017.2757599

    Article  Google Scholar 

  22. Reddy CR, Goud BS, Reddy BN, Pratyusha M, Kumar CVV, Rekha R. Review of islanding detection parameters in smart grids. In: 2020 8th International Conference on Smart Grid (icSmartGrid), 17–19 June 2020, pp 78–89. https://doi.org/10.1109/icSmartGrid49881.2020.9144923

  23. Fischer N. Protection of inverter-based resources. Energy Systems Integration Group. https://www.esig.energy/protection-of-inverter-based-resources/. Accessed 31 Dec 2021

  24. Nagpal M, Jensen M, Higginson M (2020) Protection challenges and practices for interconnecting inverter based resources to utility transmission systems. In: Impact of inverter based resources on utility transmission system protection. IEEE Power & Energy Society, USA

    Google Scholar 

  25. Kobet G, Pourbeik P (2019) Impact of inverter based generation on bulk power system dynamics and short-circuit performance. IEEE PES Resource Center

    Google Scholar 

  26. Keller J, Kroposki B (2010) Understanding fault characteristics of inverter-based distributed energy resources. National Renewable Energy Labratory, USA

    Book  Google Scholar 

  27. Khan MAU, Hong Q, Dyśko A, Booth C, Wang B, Dong X. Evaluation of fault characteristic in microgrids dominated by inverter-based distributed generators with different control strategies. In: 2019 IEEE 8th International Conference on Advanced Power System Automation and Protection (APAP), 21–24 Oct 2019, pp 846–849. https://doi.org/10.1109/APAP47170.2019.9224706

  28. Ravyts S, Broeck GVD, Hallemans L, Vecchia MD, Driesen J (2020) Fuse-based short-circuit protection of converter controlled low-voltage DC grids. IEEE Trans Power Electron 35(11):11694–11706. https://doi.org/10.1109/TPEL.2020.2988087

    Article  Google Scholar 

  29. Shuai Z, Shen C, Yin X, Liu X, Shen ZJ (2018) Fault analysis of inverter-interfaced distributed generators with different control schemes. IEEE Trans Power Delivery 33(3):1223–1235. https://doi.org/10.1109/TPWRD.2017.2717388

    Article  Google Scholar 

  30. IEEE standard conformance test procedures for equipment interconnecting distributed energy resources with electric power systems and associated interfaces. In: IEEE Std 1547.1-2020, pp 1–282, 2020. https://doi.org/10.1109/IEEESTD.2020.9097534

  31. Castilla M, Miret J, Camacho A, Matas J, Vicuna LG d (2013) Reduction of current harmonic distortion in three-phase grid-connected photovoltaic inverters via resonant current control. IEEE Trans Ind Electron 60(4):1464–1472. https://doi.org/10.1109/TIE.2011.2167734

    Article  Google Scholar 

  32. Han H, Hou X, Yang J, Wu J, Su M, Guerrero JM (2016) Review of power sharing control strategies for islanding operation of AC microgrids. IEEE Trans Smart Grid 7(1):200–215. https://doi.org/10.1109/TSG.2015.2434849

    Article  Google Scholar 

  33. Kelly D, Mysore P, Mohan N. A novel control scheme for utility-scale inverter-based resources to emulate synchronous generator fault response and retain existing protection infrastructure. In: 2021 74th Conference for Protective Relay Engineers (CPRE), 22–25 Mar 2021, pp 1–7. https://doi.org/10.1109/CPRE48231.2021.9429836

  34. Banaiemoqadam A, Hooshyar A, Azzouz MA (2021) A comprehensive dual current control scheme for inverter-based resources to enable correct operation of protective relays. IEEE Trans Power Delivery 36(5):2715–2729. https://doi.org/10.1109/TPWRD.2020.3025878

    Article  Google Scholar 

  35. Soleimanisardoo A, Karegar HK, Zeineldin HH (2019) Differential frequency protection scheme based on off-nominal frequency injections for inverter-based islanded microgrids. IEEE Trans Smart Grid 10(2):2107–2114. https://doi.org/10.1109/TSG.2017.2788851

    Article  Google Scholar 

  36. Khan MAU, Hong Q, Dyśko A, Booth C. An active protection scheme For islanded microgrids. In: 15th International conference on developments in power system protection (DPSP 2020), 9–12 Mar 2020, pp 1–6. https://doi.org/10.1049/cp.2020.0020

  37. Hamidi RJ, Livani H, Rezaiesarlak R (2017) Traveling-wave detection technique using short-time matrix pencil method. IEEE Trans Power Delivery 32(6):2565–2574. https://doi.org/10.1109/TPWRD.2017.2685360

    Article  Google Scholar 

  38. Wei S, Yanfeng G, Yan L. Traveling-wave-based fault location algorithm for star-connected hybrid multi-terminal HVDC system. In: 2017 IEEE conference on energy internet and energy system integration (EI2), 26–28 Nov 2017, pp 1–5. https://doi.org/10.1109/EI2.2017.8245645

  39. Hamidi RJ, Livani H. A travelling wave-based fault location method for hybrid three-terminal circuits. In: 2015 IEEE Power & Energy Society general meeting, 26–30 July 2015, pp 1–5. https://doi.org/10.1109/PESGM.2015.7286247

  40. Lee JW, Kim WK, Han J, Jang WH, Kim CH (2016) Fault area estimation using traveling wave for wide area protection. J Mod Power Syst Clean Energy 4(3):478–486. https://doi.org/10.1007/s40565-016-0222-7

    Article  Google Scholar 

  41. Selinc. “SEL-T400L”. https://selinc.com/products/T400L/ (accessed)

  42. He J, Liu L, Li W, Zhang M (2016) Development and research on integrated protection system based on redundant information analysis. Prot Control Mod Power Syst 1(1):13. https://doi.org/10.1186/s41601-016-0024-y

    Article  Google Scholar 

  43. Jurišić G, Havelka J, Capuder T, Sučić S (2018) Laboratory test bed for analyzing fault-detection reaction times of protection relays in different substation topologies. Energies 11(9):2482. [Online]. Available: https://www.mdpi.com/1996-1073/11/9/2482

    Article  Google Scholar 

  44. Hamidi RJ, Khodabandehlou H, Livani H, Fadali MS. Application of distributed compressive sensing to power system state estimation. In: 2015 North American Power Symposium (NAPS), 4–6 Oct 2015, pp 1–6. https://doi.org/10.1109/NAPS.2015.7335114

  45. Hamidi RJ, Khodabandelou H, Livani H, Sami-Fadali M. Hybrid state estimation using distributed compressive sensing. In: 2016 IEEE Power and Energy Society General Meeting (PESGM), 17–21 July 2016, pp 1–5. https://doi.org/10.1109/PESGM.2016.7742038

  46. Abur A, Gómez Expósito A (2004) Power system state estimation theory and implementation, 1st edn. Taylor & Francis Group, Coca Raton, FL, p 327

    Google Scholar 

  47. Wen J, Liu WHE, Arons PL, Pandey SK (2014) Evolution pathway towards wide area monitoring and protection—a real-world implementation of centralized RAS system. IEEE Trans Smart Grid 5(3):1506–1513. https://doi.org/10.1109/TSG.2013.2278660

    Article  Google Scholar 

  48. Eissa MM (2019) A novel centralized wide area protection “CWAP” in phase portrait based on pilot wire including phase comparison. IEEE Trans Smart Grid 10(3):2671–2682. https://doi.org/10.1109/TSG.2018.2808207

    Article  Google Scholar 

  49. Ivanković I, Kuzle I, Holjevac N (2017) Wide area information-based transmission system centralized out-of-step protection scheme. Energies 10(5):633. [Online]. Available: https://www.mdpi.com/1996-1073/10/5/633

    Article  Google Scholar 

  50. W. G. C-6. Wide area protection and emergency control. IEEE Power Engineering Society, USA

    Google Scholar 

  51. Carrasco JM et al (2006) Power-electronic systems for the grid integration of renewable energy sources: a survey. IEEE Trans Ind Electron 53(4):1002–1016. https://doi.org/10.1109/TIE.2006.878356

    Article  Google Scholar 

  52. Blaabjerg F, Teodorescu R, Liserre M, Timbus AV (2006) Overview of control and grid synchronization for distributed power generation systems. IEEE Trans Ind Electron 53(5):1398–1409. https://doi.org/10.1109/TIE.2006.881997

    Article  Google Scholar 

  53. Atzori L, Iera A, Morabito G (2010) The internet of things: a survey. Comput Netw 54(15):2787–2805. https://doi.org/10.1016/j.comnet.2010.05.010

    Article  MATH  Google Scholar 

  54. Liao W, Salinas S, Li M, Li P, Loparo KA (2017) Cascading failure attacks in the power system: a stochastic game perspective. IEEE Internet Things J 4(6):2247–2259. https://doi.org/10.1109/JIOT.2017.2761353

    Article  Google Scholar 

  55. Santos D, Ferreira JC (2019) IoT power monitoring system for smart environments. Sustainability 11(19):5355. [Online]. Available: https://www.mdpi.com/2071-1050/11/19/5355

    Article  Google Scholar 

  56. Lee I, Lee K (2015) The internet of things (IoT): applications, investments, and challenges for enterprises. Bus Horiz 58(4):431–440. https://doi.org/10.1016/j.bushor.2015.03.008

    Article  Google Scholar 

  57. Srivastava D, Tripathi MM. Transformer health monitoring system using internet of things. In: 2018 2nd IEEE international conference on power electronics, intelligent control and energy systems (ICPEICES), 22–24 Oct 2018, pp 903–908. https://doi.org/10.1109/ICPEICES.2018.8897325

  58. Jamal H, Khan MFN, Anjum A, Janjua MK. Thermal monitoring and protection for distribution transformer under residential loading using internet of things. In: 2018 IEEE global conference on internet of things (GCIoT), 5–7 Dec 2018, pp 1–6. https://doi.org/10.1109/GCIoT.2018.8620135

  59. Bhattarai BP et al (2019) Big data analytics in smart grids: state-of-the-art, challenges, opportunities, and future directions. IET Smart Grid 2(2):141–154. https://doi.org/10.1049/iet-stg.2018.0261

    Article  MathSciNet  Google Scholar 

  60. Koranne S (2011) Artificial intelligence and optimization. In: Handbook of open source tools. Springer, Boston, MA, pp 391–392. ch. 18

    Google Scholar 

  61. Gururajapathy SS, Mokhlis H, Illias HA (2017) Fault location and detection techniques in power distribution systems with distributed generation: a review. Renew Sust Energ Rev 74:949–958. https://doi.org/10.1016/j.rser.2017.03.021

    Article  Google Scholar 

  62. Grosan C, Abraham A (2011) Rule-based expert systems. Springer, Berlin

    Book  MATH  Google Scholar 

  63. Orduna E, Garces F, Handschin E (2003) Algorithmic-knowledge-based adaptive coordination in transmission protection. IEEE Trans Power Delivery 18(1):61–65. https://doi.org/10.1109/TPWRD.2002.806683

    Article  Google Scholar 

  64. Kawahara K, Sasaki H, Kubokawa J, Asahara H, Sugiyama K (1998) A proposal of a supporting expert system for outage planning of electric power facilities retaining high power supply reliability. IEEE Trans Power Syst 13(4):1453–1458. https://doi.org/10.1109/59.736289

    Article  Google Scholar 

  65. Bahmanyar AR, Karami A (2014) Power system voltage stability monitoring using artificial neural networks with a reduced set of inputs. Int J Electr Power Energy Syst 58:246–256. https://doi.org/10.1016/j.ijepes.2014.01.019

    Article  Google Scholar 

  66. Siddiqui SA, Verma K, Niazi KR, Fozdar M (2018) Real-time monitoring of post-fault scenario for determining generator coherency and transient stability through ANN. IEEE Trans Ind Appl 54(1):685–692. https://doi.org/10.1109/TIA.2017.2753176

    Article  Google Scholar 

  67. Yang Z, Zhou Q, Wu X, Zhao Z (2019) A novel measuring method of interfacial tension of transformer oil combined PSO optimized SVM and multi frequency ultrasonic technology. IEEE Access 7:182624–182631. https://doi.org/10.1109/ACCESS.2019.2954899

    Article  Google Scholar 

  68. Zhang S, Mishra Y, Shahidehpour M (2016) Fuzzy-logic based frequency controller for wind farms augmented with energy storage systems. IEEE Trans Power Syst 31(2):1595–1603. https://doi.org/10.1109/TPWRS.2015.2432113

    Article  Google Scholar 

  69. Mokhlis H, Li H (2011) Non-linear representation of voltage sag profiles for fault location in distribution networks. Int J Electr Power Energy Syst 33(1):124–130. https://doi.org/10.1016/j.ijepes.2010.06.020

    Article  Google Scholar 

  70. Prasad A, Belwin Edward J, Ravi K (2018) A review on fault classification methodologies in power transmission systems: part—I. J Electr Syst Inf Technol 5(1):48–60. https://doi.org/10.1016/j.jesit.2017.01.004

    Article  Google Scholar 

  71. Silva INd, Spatti DH, Flauzino RA, Liboni LHB, Alves SFdR (2017) Artificial Neural network architectures and training processes. In: Artificial neural networks. Springer, Switzerland, pp 25–27. ch. 2

    Google Scholar 

  72. Orille-Fernandez AL, Ghonaim NKI, Valencia JA (2001) A FIRANN as a differential relay for three phase power transformer protection. IEEE Trans Power Delivery 16(2):215–218. https://doi.org/10.1109/61.915485

    Article  Google Scholar 

  73. Dezelak K, Pihler J, Stumberger G, Klopcic B, Dolinar D (2010) Artificial neural network applied for detection of magnetization level in the magnetic core of a welding transformer. IEEE Trans Magn 46(2):634–637. https://doi.org/10.1109/TMAG.2009.2031976

    Article  Google Scholar 

  74. Ghoneim SSM, Taha IBM, Elkalashy NI (2016) Integrated ANN-based proactive fault diagnostic scheme for power transformers using dissolved gas analysis. IEEE Trans Dielectr Electr Insul 23(3):1838–1845. https://doi.org/10.1109/TDEI.2016.005301

    Article  Google Scholar 

  75. Silva AF, Silveira EG, Alipio R (2021) Artificial neural network applied to differential protection of power transformers. J Control Autom Electr Syst. https://doi.org/10.1007/s40313-021-00845-3

  76. Gketsis ZE, Zervakis ME, Stavrakakis G (2009) Detection and classification of winding faults in windmill generators using wavelet transform and ANN. Electr Power Syst Res 79(11):1483–1494. https://doi.org/10.1016/j.epsr.2009.05.001

    Article  Google Scholar 

  77. Barakat ZA, Hajjar AA, Kherbek T, Alhelou HH (2019) Discriminating between loss of excitation and power swings in synchronous generator based on ANN. J Control Autom Electr Syst 4:545–556

    Article  Google Scholar 

  78. Upendar J, Gupta CP, Singh GK, Ramakrishna G (2010) PSO and ANN-based fault classification for protective relaying. IET Gener Transm Distrib 4(10):1197–1212. https://doi.org/10.1049/iet-gtd.2009.0488

    Article  Google Scholar 

  79. Fathabadi H (2016) Novel filter based ANN approach for short-circuit faults detection, classification and location in power transmission lines. Int J Electr Power Energy Syst 74:374–383. https://doi.org/10.1016/j.ijepes.2015.08.005

    Article  Google Scholar 

  80. Abdullah A (2018) Ultrafast transmission line fault detection using a DWT-based ANN. IEEE Trans Ind Appl 54(2):1182–1193. https://doi.org/10.1109/TIA.2017.2774202

    Article  MathSciNet  Google Scholar 

  81. Rathore B, Mahela OP, Khan B, Alhelou HH, Siano P (2021) Wavelet-alienation-neural-based protection scheme for STATCOM compensated transmission line. IEEE Trans Industr Inform 17(4):2557–2565. https://doi.org/10.1109/TII.2020.3001063

    Article  Google Scholar 

  82. Bretas AS, Pires L, Moreto M, Salim RH (2010) A BP neural network based technique for HIF detection and location on distribution systems with distributed generation. In: Computational intelligence. Springer, Berlin

    Google Scholar 

  83. Kalech M (2019) Cyber-attack detection in SCADA systems using temporal pattern recognition techniques. Comput Secur 84:225–238. https://doi.org/10.1016/j.cose.2019.03.007

    Article  Google Scholar 

  84. Ali SS, Choi BJ (2020) State-of-the-art artificial intelligence techniques for distributed smart grids: a review. Electronics 9(6):1030. [Online]. Available: https://www.mdpi.com/2079-9292/9/6/1030

    Article  Google Scholar 

  85. Mousavian S, Valenzuela J, Wang J (2013) Real-time data reassurance in electrical power systems based on artificial neural networks. Electr Power Syst Res 96:285–295. https://doi.org/10.1016/j.epsr.2012.11.015

    Article  Google Scholar 

  86. Zhang Y, Lin F, Wang K (2020) Robustness of short-term wind power forecasting against false data injection attacks. Energies 13(15):3780. [Online]. Available: https://www.mdpi.com/1996-1073/13/15/3780

    Article  Google Scholar 

  87. Khoshdeli M, Niazazari I, Hamidi RJ, Livani H, Parvin B. Electromagnetic transient events (EMTE) classification in transmission grids. In: 2017 IEEE Power & Energy Society General Meeting, 16–20 July 2017, pp 1–5. https://doi.org/10.1109/PESGM.2017.8273984

  88. Niazazari I, Jalilzadeh Hamidi R, Livani H, Arghandeh R (2020) Cause identification of electromagnetic transient events using spatiotemporal feature learning. Int J Electr Power Energy Syst 123:106255. https://doi.org/10.1016/j.ijepes.2020.106255

    Article  Google Scholar 

  89. Pisner DA, Schnyer DM (2020) Support vector machine. In: Machine learning methods and applications to brain disorders. Elsevier, London, pp 101–121. ch. 6

    Google Scholar 

  90. Bigdeli M, Vakilian M, Rahimpour E (2012) Transformer winding faults classification based on transfer function analysis by support vector machine. IET Electr Power Appl 6(5):268–276. [Online]. Available: https://digital-library.theiet.org/content/journals/10.1049/iet-epa.2011.0232

    Article  Google Scholar 

  91. Jiao Z, Li Z (2018) Novel magnetization hysteresis-based power-transformer protection algorithm. IEEE Trans Power Delivery 33(5):2562–2570. https://doi.org/10.1109/TPWRD.2018.2837022

    Article  Google Scholar 

  92. Simões LD, Costa HJD, Aires MNO, Medeiros RP, Costa FB, Bretas AS (2021) A power transformer differential protection based on support vector machine and wavelet transform. Electr Power Syst Res 197:107297. https://doi.org/10.1016/j.epsr.2021.107297

    Article  Google Scholar 

  93. Pajuelo E, Gokaraju R, Sachdev MS (2013) Identification of generator loss-of-excitation from power-swing conditions using a fast pattern classification method. IET Gener Transm Distrib 7(1):24–36. [Online]. Available: https://digital-library.theiet.org/content/journals/10.1049/iet-gtd.2012.0340

    Article  Google Scholar 

  94. Rasoulpour M, Amraee T, Sedigh AK (2020) A relay logic for total and partial loss of excitation protection in synchronous generators. IEEE Trans Power Delivery 35(3):1432–1442. https://doi.org/10.1109/TPWRD.2019.2945259

    Article  Google Scholar 

  95. El-Saadawi M, Hatata A (2017) A novel protection scheme for synchronous generator stator windings based on SVM. Prot Control Mod Power Syst 2(1):24. https://doi.org/10.1186/s41601-017-0057-x

    Article  Google Scholar 

  96. Jaya Bharata Reddy M, Gopakumar P, Mohanta DK (2016) A novel transmission line protection using DOST and SVM. Eng Sci Technol Int J 19(2):1027–1039. https://doi.org/10.1016/j.jestch.2015.12.011

    Article  Google Scholar 

  97. Muzzammel R, Raza A (2020) A support vector machine learning-based protection technique for MT-HVDC systems. Energies 13(24):6668. [Online]. Available: https://www.mdpi.com/1996-1073/13/24/6668

    Article  Google Scholar 

  98. Salat R, Osowski S (2004) Accurate fault location in the power transmission line using support vector machine approach. IEEE Trans Power Syst 19(2):979–986. https://doi.org/10.1109/TPWRS.2004.825883

    Article  Google Scholar 

  99. Janik P, Lobos T (2006) Automated classification of power-quality disturbances using SVM and RBF networks. IEEE Trans Power Delivery 21(3):1663–1669. https://doi.org/10.1109/TPWRD.2006.874114

    Article  Google Scholar 

  100. Ravikumar B, Thukaram D, Khincha HP (2008) Knowledge-based approach using support vector machine for transmission line distance relay co-ordination. J Electr Eng Technol 3(3):363–372. https://doi.org/10.5370/JEET.2008.3.3.363

    Article  Google Scholar 

  101. Parikh UB, Das B, Maheshwari R (2010) Fault classification technique for series compensated transmission line using support vector machine. Int J Electr Power Energy Syst 32(6):629–636. https://doi.org/10.1016/j.ijepes.2009.11.020

    Article  Google Scholar 

  102. Zhang Y, Wang L, Sun W, Green IRC, Alam M (2011) Distributed intrusion detection system in a multi-layer network architecture of smart grids. IEEE Trans Smart Grid 2(4):796–808. https://doi.org/10.1109/TSG.2011.2159818

    Article  Google Scholar 

  103. Sun CC, Cardenas DJS, Hahn A, Liu CC (2021) Intrusion detection for cybersecurity of smart meters. IEEE Trans Smart Grid 12(1):612–622. https://doi.org/10.1109/TSG.2020.3010230

    Article  Google Scholar 

  104. Rizwan ul H, Li C, Liu Y (2021) Online dynamic security assessment of wind integrated power system using SDAE with SVM ensemble boosting learner. Int J Electr Power Energy Syst 125:106429. https://doi.org/10.1016/j.ijepes.2020.106429

    Article  Google Scholar 

  105. Drucker H, Donghui W, Vapnik VN (1999) Support vector machines for spam categorization. IEEE Trans Neural Netw 10(5):1048–1054. https://doi.org/10.1109/72.788645

    Article  Google Scholar 

  106. Bejmert D, Rebizant W, Schiel L (2014) Transformer differential protection with fuzzy logic based inrush stabilization. Int J Electr Power Energy Syst 63:51–63. https://doi.org/10.1016/j.ijepes.2014.05.056

    Article  Google Scholar 

  107. Granados-Lieberman D, Razo-Hernandez JR, Venegas-Rebollar V, Olivares-Galvan JC, Valtierra-Rodriguez M (2021) Harmonic PMU and fuzzy logic for online detection of short-circuited turns in transformers. Electr Power Syst Res 190:106862. https://doi.org/10.1016/j.epsr.2020.106862

    Article  Google Scholar 

  108. Eristi H (2013) Fault diagnosis system for series compensated transmission line based on wavelet transform and adaptive neuro-fuzzy inference system. Measurement 46(1):393–401. https://doi.org/10.1016/j.measurement.2012.07.014

    Article  Google Scholar 

  109. Goli RK, Gafoor Shaik A, Tulasi Ram SS (2015) A transient current based double line transmission system protection using fuzzy-wavelet approach in the presence of UPFC. Int J Electr Power Energy Syst 70:91–98. https://doi.org/10.1016/j.ijepes.2015.01.024

    Article  Google Scholar 

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Hamidi, R.J., Bhadra, A.B. (2023). Protection and Monitoring of Digital Energy Systems Operation. In: Energy Systems Transition. Power Systems. Springer, Cham. https://doi.org/10.1007/978-3-031-22186-6_5

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