Research on the Impact of Wind Power Access on Distribution Network Load Characteristics Based on K-means Clustering Algorithm

This study examines the effect of wind power availability on the distribution system load behaviors using the K-means clustering algorithm to process the load data following the integration of wind power. First, this article presents the concept of the K-means clustering algorithm and then carries out the preprocessing of the data and the analysis of the clusters using real distribution network load data. The findings of the research are that the volatility of the distribution network load curve increases sharply with the ratio of wind power access, and the voltage quality and the system stability are also affected to some extent. This research verified the feasibility of the K-means clustering algorithm to categorize the load data and to derive characteristics, explored the characteristics of the load under various wind power access modes, and disclosed the relationship between the wind power access and the characteristics of the distribution network load. The conclusions obtained through this research not only promote the theory regarding how the connection of wind power has an effect upon distribution networks but also offer date support and decision making aid to the optimization of the operations of the grid and dispatch in real-world projects, and indicate the way to improve the adaptability and stability of the distribution networks through new concepts and technical means.