8Clean Energy Capability Portfolio | Renewable Generation |
Competitive Advantage • Developed world-class characterisation systems specifically tailored for both silicon and non-silicon materials
• Extensive expertise in conducting temperature dependence measurements of electrical and optical properties of semiconductors , enabling comprehensive understanding of their behaviour
• Pioneered the application of machine learning algorithms in PV , revolutionising conventional measurement and inspection techniques by significantly augmenting their capabilities
• Developed novel automated decision-making platforms powered by machine learning , specifically designed for maintaining utilityscale PV plants and optimising end-of-life processes for PV modules
• Innovated a novel PV module specifically designed for agriPV ( agriculture and photovoltaic ) applications
Impact • Helping meet the ICCP report target of 8-10 TW peak power of installed PV by 2030 , through :
• developing innovative methods to quantify and identify the nature of defects in PV materials
• developing methods for early detection of degradation mechanisms across the entire PV chain
• optimising the decisions regarding end-of-life of PV modules
• developing new applications for PV systems , such as agriculture
• These developments will lead to lower production costs , higher efficiency solar cells , and more reliable PV systems
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Successful Applications • Determination of defect parameters responsible for LeTID in mc-Si wafers
• Determination of defect parameters in n-type float-zone wafers
• Development of photoluminescence imaging systems with spatially inhomogeneous illumination and at uniform excess carrier concentration
• Imaging of installed modules in solar field and on solar cars
• Machine learning applications for PV that significantly enhance existing capabilities
• Automated machine learning based decision-making platforms for maintaining utility-scale PV plants and optimising end-of-life processes for PV modules
Capabilities and Facilities • Lifetime measurements at a wide temperature range ( 80 – 680K )
• Lifetime measurements of metallised samples
• Current-voltage measurements at a wide temperature range ( 80 – 680K )
• Optical and spectral measurements at a wide temperature range ( 80 – 680K )
• Photoluminescence measurements at uniform excess carrier concentration
• A variety of machine learning algorithms
• Novel design for agriPV modules
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Our Collaborators • Sinton Instruments
• BT Imaging
• Meyer Burger
• Sunrise Solar Solutions
• JinkoSolar
• Neoen
• Spark Renewables
• Gentari
• Caelux
• Halocell
• RayGen Resources
• PV Industries
• Tindo Solar
More Information Professor Ziv Hameiri School of Photovoltaic and Renewable Energy Engineering T : + 61 2 9385 9475 E : ziv . hameiri @ unsw . edu . au
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