Smart Intelligent Monitoring and Maintenance Management of Photo-voltaic Systems
Marian kingsley-Amaehule, Roland Uhunmwangho, Nkolika O. Nwazor, Kenneth E. 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.