Optimization configuration of flexible interconnection device DG based on improved E-C-Kmeans and GA under SOP support

The increasing popularity of flexible interconnected devices has made them a crucial component of distributed power systems. At present, the effective integration and optimized configuration of distributed power sources remain a key focus in power system research. To address this, the study introduces improvements to both the feature selection weighted K-means clustering algorithm and the genetic algorithm, applying them to data preprocessing and configuration optimization. Based on these, an integrated optimization configuration model is proposed. The experimental results demonstrated that the improved clustering algorithm achieved the highest accuracy of 96 %. Under varying wind speeds and light intensities, its minimum sum of squared clustering errors reached 8 and 10, respectively. The improved genetic algorithm generated up to 190 optimal individuals, with a highest accuracy of 91.2 % and a minimum computation time of 6.2 s. Simulation testing further showed that, under support from back-to-back voltage source converters, the decision-making layer achieved a maximum comprehensive income of 1.547 million yuan, an environmental impact of only 41.7 %. The scheduling layer reached the lowest operational cost of 1.627 million yuan. In conclusion, the proposed approach demonstrates significant improvements in distributed power utilization and system operating efficiency.