A southern, middle, and northern Norwegian offshore wind energy resources analysis by a transfer learning method for Energy Internet

Hao Chen, Yngve Birkelund, Benjamin Ricaud, Qixia Zhang

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Abstract

As renewable energy sources offshore wind energy develop quickly, countries like Norway with long coastlines are exploring their potential. However, the diverse wind resources across different regions of Norway present challenges for study for effective utilization of offshore wind energy. This study proposes a novel method that utilizes transfer learning techniques to analyse the resource differences between these areas for optimum energy generation. The suggested approach is tested using real-world wind data from Norway's southern, middle, and northern regions. The results show that transfer learning successfully bridges resource discrimination, boosting wind resource prediction precision in the target domains. The work can contribute to optimizing offshore wind energy utilization in Norway by addressing the resource disparities and forecasting between the different regions.

Original languageEnglish
Article number012011
JournalJournal of physics: Conference series
Volume2655
Issue number1
DOIs
Publication statusPublished - 2023
Externally publishedYes
Event2nd International Conference on Energy Internet and Power Systems, ICEIPS 2023 - Chengdu, China
Duration: 4 Aug 20236 Aug 2023
Conference number: 2

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