A Typical Output Mode Analysis Method for Distributed Renewable Generation Based on K-Means

With the development of a green and low-carbon economy, distributed renewable generation (DRG) is growing rapidly, with obvious advantages and disadvantages. DRG has characteristics such as volatility, randomness, and uncontrollability, which may have an impact and adverse impact on the safe operation of the power grid. If it can accurately predict and grasp its power generation law, it has significant significance for improving the safe operation of the power grid. This article innovatively proposes a K-means based DRG typical output mode analysis method. The method first collects the DRG output of two regions over a long period of time, uses isolated forest algorithm to normalize and fuse the collected data, and uses K-MEANS method to cluster the processed data. Finally, 16 representative output modes of these regions are obtained, These models can be used to guide the output prediction and analysis of corresponding types of weather days. The example analysis shows that this method is generally effective and has good robustness, and can be used to guide the analysis of DRG output patterns in similar regions.