Smart Intelligent Monitoring and Maintenance Management of Photo-voltaic Systems

Marian kingsley-Amaehule, Roland Uhunmwangho, Nkolika Nwazor, Kenneth Okedu

Abstract


As the proliferation of solar photovoltaic (PV) system installation is on the rise, it is imperative to carry out new studies to monitor and optimize the maintenance management solar PVs. The existing solutions on the solar PVs monitoring and optimization are usually based on non-holistic approaches in solving the identified problem. In a bid to breach the research gap, this paper proposed and implemented a holistic model for solar PVs monitoring, maintenance, and management, considering Internet of Things (IoT). A mathematical model representing the solar PVs and the algorithms for its implementation were carried out, along with a designed embedded expert system as a proof of concept. Efforts were made to collect real-time data at both fog and cloud levels, in order to demonstrate the robustness of the control topology employed. The result analysis showed that the overall accuracy of the developed expert embedded system is 98.95%, which indicates that it can be used for effective and high reliability performance of solar PVs. Comparison of the sampled data collected at fog and cloud levels revealed that the system has 100% integrity in data communication as well as 98% availability while simultaneously carrying out fault identification, classification and immediate analyses of the variables in real time. The knowledge gained in this research could be extended as future directions in other engineering fields for asset maintenance management and artificial intelligence schemes.


Keywords


Solar photovoltaic system; real time monitoring; four-level algorithm; fault identification; fog and cloud.

Full Text:

PDF

References


K. E. Okedu, A. Alghaithi, “Comparative Study of the Internal Dynamic Failures of Grid-connected Solar PVs: The case of Oman Power Network”, Frontiers in Energy Research-Smart Grids, vol. 10, no. 858803, pp.1-15 2022, DOI: 10.3389/fenrg.2022.858803.

K. E. Okedu, and M. Al-Hashmi, “Assessment of the Cost of various Renewable Energy Systems to Provide Power for a Small Community: Case of Bukha, Oman”, International Journal of Smart Grid, vol.2, no. 3, pp. 172-182, 2018.

S. M. Fahad, m. Abdallah, M. Ismali and M. E. Ahmed, “Review on Advancement in Solar Photovoltaic Monitoring Systems,” ISSN, no. 8, pp. 901-917, 2021.

R. R. Vijaya, R. N V Ganapathi, S. V and P. Sugandha, “IOT based solar energy prophecy using RNN architecture,” in E3S Web of Conferences, India, 2020.

I. Amjad and T. I. M., “Design and Analysis of a Stand-Alone PV System for a Rural House in Pakistan,” International Journal of Photoenergy, vol. 2019, 2019.

A. Mohammadreza, M. K. Nallapaneni, E. Aref, A. Hamsa, K. V. d. O. Aline and S. C. Shauhrat, “Solar Pv Systems Design and Monitoring,” Photovoltaic Solar Energy Conversion-Technologies, Applications and Environmental Impacts, pp. 117-145, 2020.

C. Wael, M. Chaabane, M. Hatem and B. Philippe, “Performance Evaluation of a Solar Photovoltaic System,” Energy Report, pp. 400-406, 2018.

K. Ankit and K. g. Suresh, “Solar Photovoltaic Remote Monitoring System Using IoT,” in RISE, India, 2017.

A. Harraiz, A. Marugan and F. P. Marquez, “Photovoltaic Plant Condition Monitoring using Thermal images Analysis by Convolutional Neutral Network-based Structure,” Renewable Energy, vol. 153, pp. 334-348, 2020.

A. T. Felipe, C. F. Melo and C. G. L. Freitas, “Design and Development of an Online Smart monitoring and Diagnosis system for Photovoltais Destributed Generation,” Energies 2021, 14, 8552, 2021.

V. V. R. Raju, N. V. G. Raju, V. Shailaja and S. Padullaparti, “IOT based solar energy prophecy using RNN architecture,” E3S Web of Conferences, vol. 184, p. 1007, 2020.

M. Ali, “An IOT Based Approach for Monitoring Solar Power Consumption with AdaFruit Cloud,” International Journal of Engineering Applied Sciences and Technology, pp. 335-341, 2020.

M. Hassan, S. Saha and M. Haque, “A framework for the Performance Evaluation of Household Rooftop Solar,” International Journal of Electrical Power and Energy Systems, pp. 1-18, 2021.

F. Milad and P. Jafar Amiri, “Intelligent MPPT for photovoltaic panels using a novel fuzzy logic and artificial neural networks based on evolutionary algorithms,” Energy Reports, pp. 1338-1348, 2021.

ThingSpeak, “ThingSpeak for IoT Projects,” 5 December 2019. [Online]. Available: www.thingspeak.com. [Accessed 6 January 2022].




DOI (PDF): https://doi.org/10.20508/ijsmartgrid.v6i4.260.g246

Refbacks

  • There are currently no refbacks.


www.ijsmartgrid.com; www.ijsmartgrid.org

iilhcol@gmail.com; ijsmartgrid@nisantasi.edu.tr

Online ISSN: 2602-439X

Publisher: ilhami COLAK (istanbul Nisantasi Univ)

Cited in Google Scholar and CrossRef