Fault Diagnostic Methodologies for Utility-Scale Photovoltaic Power Plants: A State of the Art Review. Sustainability
In 2021, Dr. Abbas Fardoun, Assistant Dean of the Faculty of Engineering at the Al Maaref University, participated in a journal paper titled "Fault Diagnostic Methodologies for Utility-Scale Photovoltaic Power Plants: A State of the Art Review".
This study involves a research team that includes Mr. Qamar Navid, Emirates Centre for Energy & Environment Research - United Arab Emirates University, Dr. Ahmed Hassan, Department of Architecture Engineering - College of Engineering at United Arab Emirates University, Dr. Rashad Ramzan, Department of Electrical Engineering - National University of Computer and Emerging Sciences, and Dr. Abdulrahman Alraeesi, Department of Chemical and Petroleum Engineering -United Arab Emirates University.
The study discusses in depth the state of the art of faults in utility PV plants and their identification, using electrical parameters, artificial intelligence, and thermal imaging. Furthermore, this article discusses the most effective and efficient monitoring techniques which are feasible for implementation.
Abstract:
The worldwide electricity supply network has recently experienced a huge rate of solar photovoltaic penetration. Grid-connected photovoltaic (PV) systems range from smaller custom built-in arrays to larger utility power plants. When the size and share of PV systems in the energy mix increases, the operational complexity and reliability of grid stability also increase. The growing concern about PV plants compared to traditional power plants is the dispersed existence of PV plants with millions of generators (PV panels) spread over kilometers, which increases the possibility of faults occurring and associated risk. As a result, a robust fault diagnosis and mitigation framework remain a key component of PV plants. Various fault monitoring and diagnostic systems are currently being used, defined by calculation of electrical parameters, extracted electrical parameters, artificial intelligence, and thermography. This article explores existing PV fault diagnostic systems in a detailed way and addresses their possible merits and demerits.
Keywords: utility-scale power plants; photovoltaic (PV); monitoring; fault diagnostics