Congratulations to Chih-Yi Lu (呂芷儀) for winning the Best Paper Award at the 2024 TEGA Conference (台灣智慧電動車及綠能科技研討會)

Congratulations to Chih-Yi Lu (呂芷儀), doctoral student in the E3 group, for winning the Best Paper Award at the 2024 Taiwan E-Intelligent Vehicle & Green Energy Technology Conference (台灣智慧電動車及綠能科技研討會) — the TEGA annual meeting held November 6–7, 2024 at National Chung Hsing University in Taichung, under the theme "Green-Powered Transport, Innovative Business Opportunities" (綠電運輸 創新商機).

The Winning Research

Chih-Yi presented her work on CL-SUNSET, which integrates contrastive representation learning into the SUNSET deep-learning framework for very short-term solar power forecasting. Accurate minutes-ahead photovoltaic forecasts are a linchpin of green-powered transport: the more confidently a grid operator can predict solar output, the more aggressively EV charging and battery-swap infrastructure can lean on renewable generation. Her results showed that adding a contrastive learning stage improves forecasting performance in both RMSE and R² — with the largest gains under the cloudy, non-sunny conditions that make solar forecasting hardest. The research line has since developed into a manuscript on contrastive representation learning for robust cross-site photovoltaic forecasting.

A Conference the Lab Keeps Coming Back To

The TEGA conference series — organized with partners including the National Science and Technology Council and Taiwan's e-vehicle industry alliances — has been good ground for the E3 group. Prof. Hsieh received the Outstanding Academic Advisor Award at the first edition in 2021, and the group took home both the Best Paper Award and a second advisor award at the 2022 meeting. Chih-Yi's win continues the streak into a new generation of E3 researchers.

Learn more about Chih-Yi's research on her member page.