Center for Environmental Research and Technology

Join us for another research seminar with Dr. Musa Yilmaz, Assistant Professor at Batman University and Visiting Researcher at CE-CERT! Explore the future of renewable energy with a focus on "Fault Detection in PV Panels using Digital Twin Technology."

Event Details:

• Speaker: Dr. Musa Yilmaz
• Date: January 23, 2024
• Location: Room 105
• Time: 3:00 PM - 4:00 PM
• RSVP: All are welcome and encouraged to join! Light snacks and refreshments will be provided.

About Dr. Musa Yilmaz: Musa Yilmaz (M’21–SM’22) earned his B.Sc., M.Sc., and Ph.D. in Electrical and Electronics Engineering, as well as a degree in Electrical Education from A.I.B.U. and Marmara University, Turkey, in 2001, 2004, and 2013, respectively. Currently holding the position of Assistant Professor at the Electrical and Electronics Engineering and Energy Engineering departments of Batman University. During 2015 to 2016, Dr. Yılmaz served as a visiting scholar at the Smart Grid Research Center (SMERC) at the University of California, Los Angeles (UCLA). His primary research interests encompass smart grid technologies and renewable energy. Dr. Yılmaz has been actively involved in extensive research in the areas of smart grid and solar energy. Additionally, he is a partner with Biosys LLC, a medical company. Dr. Yılmaz has demonstrated a strong commitment to academia and publishing. He held the prestigious role of Editor-in-Chief for the Balkan Journal of Electrical and Computer Engineering (BAJECE) and the European Journal of Technique (EJT).

Title: "Fault Detection in Photovoltaic Panels Using Digital Twin Technology: A Comprehensive Study"

Abstract: This paper conducts a comprehensive inquiry into the integration of Digital Twin technology for enhancing fault detection in Photovoltaic (PV) panels. As the global deployment of PV systems continues to rise, ensuring their consistent and fault-tolerant operation becomes imperative. Digital Twin technology emerges as a promising solution, replicating and simulating real-time behavior to facilitate precise fault detection and predictive maintenance for PV panels. The paper delves into Digital Twin principles, their application in the PV panel domain, and the formulation of an effective fault detection framework. The proposed methodology undergoes validation with real-world data, juxtaposed against traditional fault detection methods, revealing the transformative potential of Digital Twin technology in elevating the reliability and performance of PV systems. Concurrently, we present a meticulous evaluation of the sparse-RVFLN method for fault detection in PV systems. Leveraging extensive numerical simulations and empirical experiments, the efficacy of the proposed method is examined across diverse fault scenarios in ungrounded PV arrays. Utilizing simulations in PSCAD/EMTDC and MATLAB, the study explores varied operating conditions, spanning mismatch variations, environmental influences, and a spectrum of fault instances and impedances. The evaluation, inclusive of the introduction of artificial noise and detailed simulation outcomes, furnishes a robust understanding of the method's performance, crucial for its practical implementation.