Extreme hail events pose a serious risk not just for people but also for business and assets. Due to their nature this is particularly true for utility-scale solar parks. Accurately assessing the risk of extreme hail is therefore critical when planning, developing, and operating large-scale solar farms. Yet, the challenge is compounded by limited, noisy historical data and the unpredictable nature of severe weather events. In this talk, I will show how a range of statistical and simulation methods can be used to estimate hail risk—even in situations with limited or noisy data.
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Speaker
Valerio Bonometti
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talks
Senior Data Scientist
Lightsource bp
Valerio Bonometti is a Senior Data Scientist currently working in the renewable energy sector at Lightsource bp. Before that I was a Data Scientist at Tesco where I worked both in the Forecasting and in the Search and Recommendation teams. I hold an industrial PhD in computer science from the University of York carried out full-time within a major Japanese video-game publisher (Square Enix) in London. My thesis focused on how to blend neuroscientific theories of motivation with deep learning model for estimating motivational states and predicting behavioral engagement. Before that I was a research intern between Ghent and Padua where I focused on the study of the reward process both from a behavioral and psychobiological perspective. I hold a master and bachelor degree in psychology from the Univeristy of Padua.
Bio from: Assessing Risk of Extreme Events & Knowledge Extraction for RAG Systems
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