Research on Distributed New Energy Automatic Control Based on Multi source Heterogeneous Data

In order to solve the problem of poor level and low efficiency of automatic regulation of distributed new energy caused by the diversity, heterogeneity, and processing difficulty of data in traditional methods, a distributed new energy automatic regulation method based on multi-source heterogeneous data is proposed. Firstly, through data reading and preprocessing, comprehensive analysis and attribute classification of multisource heterogeneous data are carried out; Subsequently, a data model is established using machine learning algorithms to achieve data association and fusion; Finally, a distributed new energy automatic regulation method based on fused data was designed and implemented. The experimental results show that this method can significantly improve the accuracy and real-time performance of energy regulation, effectively cope with the volatility and uncertainty of new energy generation, and achieve optimized operation of the energy system. Through continuous optimization methods, it is expected to further improve the overall performance and reliability of energy regulation methods.