Analysis of Power Grid Operation Characteristics with Distributed Generation Access Based on Data Mining

With the increasingly problems of environmental pollution and energy shortage, new energy power generation technology has been developed rapidly. The scale of grid-connected new energy generation in the distribution network is increasing, and its influence on the grid is becoming more and more significant, which also brings challenges to the system scheduling. Based on the historical data, after preprocessing a large number of data, the improved K-means clustering algorithm based on GSA elbow criterion is proposed to extract and mine the features of power data. On this basis, the output characteristics of new energy and regional load characteristics are analyzed. Secondly, the impact of distributed new energy on the peak-valley difference of load and the impact of new energy with different permeability on the system reserve are studied. Finally, the impact on the typical operation characteristics of regional power grid is analyzed.