Article

Researchers led by Xie, Tian, and Gu have developed a new framework for integrating offshore wind farms in Eastern China to enhance grid flexibility and renewable energy penetration. This model transforms wind farms from isolated power sources into collaborative aggregators that stabilize grid operations through data sharing and coordinated dispatch strategies.

The approach utilizes advanced control algorithms and machine learning for real-time forecasting, optimizing energy dispatch to maintain grid stability while reducing reliance on fossil fuels. Coupling wind farms with energy storage systems aims to mitigate supply fluctuations, potentially reducing energy curtailment by 30%.

The study also suggests market reforms to incentivize participation in grid services. The model's principles are applicable to other regions with offshore wind potential, supporting international climate targets by promoting higher renewable energy shares and reducing carbon emissions significantly. Future research may extend this integration to hybrid offshore platforms.