Optimization Design of Data Compression and Transmission Optimization Algorithm for Facial Energy Internet

This study focuses on addressing the challenges of renewable energy data management in the energy internet and proposes an optimized design for data compression and transmission optimization algorithms. We have designed a data compression algorithm for the energy internet based on its data characteristics. By compressing renewable energy data, we have reduced transmission bandwidth and costs. Through performance evaluation of different compression algorithms and transmission optimization algorithms, we found that different algorithms exhibit differentiated performance in the energy internet. Based on actual needs and constraints, we can choose the most suitable algorithm. Finally, the experimental results indicate that latency is the most critical indicator in real-time data transmission, and it is necessary to minimize the latency of data transmission as much as possible. Through data analysis, it can be found that the algorithm proposed in this article performs well in this area, finding shorter transmission paths and reducing transmission latency, achieving a minimum delay of about 17 milliseconds. Future work can further improve algorithm performance, expand application areas, consider more data types and sources, in order to further improve the efficiency and reliability of data management and transmission.