Multi-objective Performance Optimization of Energy Internet Using Improved NSGA-II

In this paper, we propose an improved NSGA-II algorithm to optimize the operation performance of Energy Internet. We designed the corresponding gene structure and related parameters according to the Energy Internet operation demands. Then, to increase the proportion of feasible gene samples, we designed a data sequence compensation function and adopted random compensating with different probability thresholds, which can further increase the performance compared to all samples compensating. Through this means, we obtained the optimal result with better operation indices, which verified the advanced performance of this improved algorithm. In the further research, we will try more system optimal indexes and obtain better results based on the progress of the newest NSGA-like algorithms.