148
Views
3
CrossRef citations to date
0
Altmetric
Research Articles

Solar Photovoltaic System Performance Improvement Using a New Fault Identification Technique

, , &
Pages 42-54 | Received 04 Mar 2023, Accepted 09 Jul 2023, Published online: 24 Jul 2023

References

  • B. P. Kumar, D. S. Pillai, N. Rajasekar, M. Chakkarapani, and G. S. Ilango, “Identification and localization of array faults with optimized placement of voltage sensors in a PV system,” IEEE Trans. Ind. Electron., vol. 68, no. 7, pp. 5921–5931, 2021. DOI: 10.1109/TIE.2020.2998750.
  • Y. Zhao, J. F. De Palma, J. Mosesian, R. Lyons, and B. Lehman, “Line-line fault analysis and protection challenges in solar photovoltaic arrays,” IEEE Trans. Ind. Electron., vol. 60, no. 9, pp. 3784–3795, 2013. DOI: 10.1109/TIE.2012.2205355.
  • D. S. Pillai and R. Natarajan, “A compatibility analysis on NEC, IEC, and UL standards for protection against line-line and line-ground faults in PV arrays,” IEEE J. Photovoltaics, vol. 9, no. 3, pp. 864–871, 2019. DOI: 10.1109/JPHOTOV.2019.2900706.
  • R. Hariharan, M. Chakkarapani, and G. Saravana Ilango, “Challenges in the detection of line-line faults in PV arrays due to partial shading,” 2016 International Conference on Energy Efficient Technologies for Sustainability (ICEETS), Nagercoil, India, 07–08 Apr. 2016, pp. 23–27. DOI: 10.1109/ICEETS.2016.7582893.
  • G. R. Venkatakrishnan et al., “Detection, location, and diagnosis of different faults in large solar PV system—a review,” Int. J. Low-Carbon Technol., vol. 18, pp. 659–674, Feb. 2023. DOI: 10.1093/ijlct/ctad018.
  • S. Rao, A. Spanias, and C. Tepedelenlioglu, “Solar array fault detection using neural networks,” 2019 IEEE International Conference on Industrial Cyber Physical Systems (ICPS), Taipei, Taiwan, 06–09 May 2019, pp. 196–200. DOI: 10.1109/ICPHYS.2019.8780208.
  • N. Ramachandran, S. Murugan, C. Vinayagam, and P. K. Balachandran, “Real-time implementation of a seven-level multilevel DC link inverter for solar PV system during partial shading,” Electric Power Compon. Syst., pp. 1–10, 2023. DOI: 10.1080/15325008.2023.2207177.
  • M. N. Akram and S. Lotfifard, “Modeling and health monitoring of DC side of photovoltaic array,” IEEE Trans. Sustain. Energy, vol. 6, no. 4, pp. 1245–1253, Oct. 2015. DOI: 10.1109/TSTE.2015.2425791.
  • Z. Yi and A. H. Etemadi, “Line-to-line fault detection for photovoltaic arrays based on multi-resolution signal decomposition and two-stage support vector machine,” IEEE Trans. Ind. Electron, vol. 64, no. 11, pp. 8546–8556, 2017. DOI: 10.1109/TIE.2017.2703681.
  • F. Harrou, B. Taghezouit, and Y. Sun, “Improved κnN-based monitoring schemes for detecting faults in PV systems,” IEEE J. Photovoltaics, vol. 9, no. 3, pp. 811–821, 2019. DOI: 10.1109/JPHOTOV.2019.2896652.
  • B. P. Kumar, G. S. Ilango, M. J. B. Reddy and N. Chilakapati, “Online fault detection and diagnosis in photovoltaic systems using wavelet packets,” IEEE J. Photovoltaics, vol. 8, no. 1, pp. 257–265, 2018. DOI: 10.1109/JPHOTOV.2017.2770159.
  • D. S. Pillai and N. Rajasekar, “An MPPT-based sensorless line-line and line-ground fault detection technique for PV systems,” IEEE Trans. Power Electron., vol. 34, no. 9, pp. 8646–8659, 2019. DOI: 10.1109/TPEL.2018.2884292.
  • R. Hariharan, M. Chakkarapani, G. Saravana Ilango, and C. Nagamani, “A method to detect photovoltaic array faults and partial shading in PV systems,” IEEE J. Photovoltaics, vol. 6, no. 5, pp. 1278–1285, 2016. DOI: 10.1109/JPHOTOV.2016.2581478.
  • S. Ganesan, P. W. David, P. K. Balachandran, and T. Senjyu, “Fault identification scheme for solar photovoltaic array in bridge and honeycomb configuration,” Electr. Eng., vol. 105, pp. 2443–2460, 2023. DOI: 10.1007/s00202-023-01816-4.
  • P. Jain et al., “A digital twin approach for fault diagnosis in distributed photovoltaic systems,” IEEE Trans. Power Electron., vol. 35, no. 1, pp. 940–956, 2020. DOI: 10.1109/TPEL.2019.2911594.
  • M. Patil, B. P. Kumar, and N. Karuppiah, “Detection and location of faults in photo voltaic systems,” 2023 2nd International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN), Villupuram, India, 21–22 Apr. 2023, pp. 1–6. DOI: 10.1109/ICSTSN57873.2023.10151647.
  • D. S. Pillai and N. Rajasekar, “A comprehensive review on protection challenges and fault diagnosis in PV systems,” Renew. Sustain. Energy Rev., vol. 91, pp. 18–40, 2018. DOI: 10.1016/j.rser.2018.03.082.
  • S. A. Zaki, H. Zhu, and J. Yao, “Fault detection and diagnosis of photovoltaic system using fuzzy logic control,” E3S Web Conf., vol. 107, pp. 02001, Jul. 2019. DOI: 10.1051/e3sconf/201910702001.
  • M. Hojabri, S. Kellerhals, G. Upadhyay, and B. Bowler, “IoT-based PV array fault detection and classification using embedded supervised learning methods,” Energies (Basel), vol. 15, no. 6, pp. 2097, Mar. 2022. DOI: 10.3390/en15062097.
  • M. M. Badr et al., “Fault identification of photovoltaic array based on machine learning classifiers,” IEEE Access, vol. 9, pp. 159113–159132, 2021. DOI: 10.1109/ACCESS.2021.3130889.
  • E. Lodhi et al., “An AdaBoost ensemble model for fault detection and classification in photovoltaic arrays,” IEEE J. Radio Freq. Identif., vol. 6, pp. 794–800, 2022. DOI: 10.1109/JRFID.2022.3212310.
  • S. Chandrasekharan, S. K. Subramaniam, and B. Natarajan, “Current indicator based fault detection algorithm for identification of faulty string in solar PV system,” IET Renew. Power Gen., vol. 15, no. 7, pp. 1596–1611, May 2021. DOI: 10.1049/rpg2.12135.
  • P. Guerriero, F. Di Napoli, G. Vallone, V. Dalessandro, and S. Daliento, “Monitoring and diagnostics of PV plants by a wireless self-powered sensor for individual panels,” IEEE J. Photovoltaics, vol. 6, no. 1, pp. 286–294, 2016. DOI: 10.1109/JPHOTOV.2015.2484961.
  • M. Alajmi, O. Aljasem, N. Ali, A. Alqurashi, and I. Abdel-Qader, “Fault detection and localization in solar photovoltaic arrays framework: hybrid methods of data-analysis and a network of voltage-current sensors,” IEEE International Conference on Electro Information Technology, vol. 2018-May, pp. 404–410, 2018. DOI: 10.1109/EIT.2018.8500264.
  • Y. A. Mahmoud, W. Xiao, and H. H. Zeineldin, “A parameterization approach for enhancing PV model accuracy,” IEEE Trans. Ind. Electron., vol. 60, no. 12, pp. 5708–5716, 2013. DOI: 10.1109/TIE.2012.2230606.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.