Jing Gao

Title: Jing Gao - Innovator in Wind Power Prediction

Introduction

Jing Gao is a notable inventor based in Liaoning, China. He has made significant contributions to the field of renewable energy, particularly in the area of wind power prediction. His innovative methods aim to enhance the efficiency and reliability of wind energy generation.

Latest Patents

Jing Gao holds a patent for a "Method and system for predicting a day-ahead wind power of wind farms." This patent describes a comprehensive approach that includes constructing a raw data set based on correlations between predicted daily wind power, numerical weather forecasts, and historical data. The method employs k-means clustering to categorize data and utilizes robust auxiliary classifier generative adversarial networks to generate labeled scenes. Ultimately, it determines the predicted daily wind power based on historical data and weather features, providing results at multiple set times.

Career Highlights

Throughout his career, Jing Gao has worked with prominent organizations such as the Economic and Technological Research Institute of State Grid Liaoning Electric Power Co., Ltd. and the State Grid Corporation of China. His work in these institutions has allowed him to apply his innovative ideas in practical settings, contributing to advancements in energy technology.

Collaborations

Jing Gao has collaborated with several professionals in his field, including Xiao Pan and Mingli Zhang. These partnerships have fostered a collaborative environment that encourages the exchange of ideas and enhances the development of innovative solutions in wind power prediction.

Conclusion

Jing Gao's contributions to the field of wind power prediction exemplify the importance of innovation in renewable energy. His patented methods and collaborative efforts continue to pave the way for advancements in this critical area of technology.