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Ali Khan Niazi, Kamran

Ali Khan Niazi, Kamran

PROJECT TITLE: Hotspot Detection, Classification, and Mitigation Techniques for Enhanced Performance of Solar PV Systems 

PhD period: 2018.05.01 – 2021.04.30.
Section: Power Electronic Systems
Research Programmes: Photovoltaic Systems and Efficient and Reliable Power Electronics 
Supervisor: Yongheng Yang
Co-Supervisor: Dezso Sera
Contact Information

Collaborator: To be announced later. 
Funding: Self-funding and the Department of Energy Technology.


Photovoltaic (PV) systems for domestic power supply can greatly reduce greenhouse gases generation. They, in particular, have seen large growth due to decreasing costs and maturing technology of crystalline silicon (c-Si) based PV panels. These panels typically contain multiple solar cells to enhance panel voltage and are connected in series to provide inverter compatible voltages. These PV systems generally operate with a Performance Ratio (PR) of 60-78%. However, in some cases shading may reduce the PR to as low as 50%.

In addition to performance degradation due to shading, reliability is also an important concern for c-Si solar panels due to possible occurrence of hotspots (localized overheating). In severe cases, hotspots may result in irreversible panel malfunctioning by damaging the panel glass as well as its cells. Once a cell is degraded from hotspots, it often becomes a weak point in a PV string that causes severe performance reduction. If the damage is permanent, the entire set of cells need to be disconnected from the complete string, causing reduction in the overall power output.

Therefore, this research project is aimed to develop reliable, cost effective and efficient “hotspot detection, classification and mitigation techniques/topologies” for solar PV systems. These novel topologies will use machine learning on active sensor data to detect, mitigate and classify hotspots in solar PV modules. Additionally, classification of affected solar PV panels will be explored through thermographic data obtained from Unmanned Aerial Vehicle (UAV). More importantly, the project is expected to propose active bypassing techniques to improve the performance of PV systems.


Publications in journals and conference papers may be found at VBN.