Nuttapat Jittratorn | Renewable Energy Technologies | Editorial Board Member

Mr. Nuttapat Jittratorn | Renewable Energy Technologies | Editorial Board Member

National Cheng Kung University | Taiwan

Mr. Nuttapat Jittratorn is a Ph.D. candidate at National Cheng Kung University specializing in energy forecasting, artificial intelligence, and image-based predictive modeling. His research focuses on advanced machine learning frameworks for wind and photovoltaic (PV) power forecasting, contributing to improved accuracy in short-term and ultra-short-term energy predictions. He has authored multiple peer-reviewed publications in high-impact journals, including Q1-ranked outlets, with growing citation impact. His work involves international collaborations and conference contributions (IEEE, IET), addressing challenges in renewable energy integration and smart grid management, thereby supporting sustainable energy systems and enhancing reliability in modern power networks.

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Featured Publications

A deterministic and probabilistic framework based on corrected wind speed to improve short-term wind power forecasting accuracy.

– International Journal of Electrical Power & Energy Systems. (2025). Cited By: 7

A hybrid method for hour-ahead PV output forecast with historical data clustering.

– In 2022 IET International Conference on Engineering Technologies and Applications (IET-ICETA). (2018). Cited By:  5

Deterministic multi-energy load forecasting for integrated energy management system using a random search transformer network.

– In Proceedings of the 2025 IEEE International Conference on Environment and Electrical Engineering and 2025 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe) (pp. 1–6). IEEE. (2025) Cited By: 1

Ultrashort-term PV power forecasting based on weather classification and dynamic cloud tracking.

– In Proceedings of the 2025 IEEE Industry Applications Society Annual Meeting (IAS) (pp. 1–8). IEEE.. (2020). Cited By: 1