photovoltaics

Fault Identification of Photovoltaic Array Based on Machine Learning Classifiers

1 min read ·
The Solar Photovoltaic (PV) industry has experienced significant growth over the past years due to the technology’s clear economic and environmental benefits. The world’s net electricity generation from grid-connected PV systems is expected to rise. Although PV systems don’t incorporate moving parts and usually require low maintenance, they are still subjected to diverse faults across the various system components. Proper fault detection and/or identification is thus necessary to avoid significant energy generation loss and large capital expenditures. Fault identification in Photovoltaic array

Ali Alhejab

Research Interests My research interest is to investigate and develop advanced fault detection and diagnosis techniques for photovoltaic (PV) systems. The performance of PV systems is highly dependent on the reliable and continuous operation of their components. Thus, identifying, and rectifying faults in PV systems is crucial to ensure their efficient and sustainable operation. Professional Profile 2023 - Present, Directed Research Student, KAUST, Thuwal, Saudi Arabia Education Profile Bachelor of Science in Electrical Engineering, King Fahd University of Petroleum and Minerals (KFUPM)