Pattern simulation and analysis of generalized load profile coupling with active load and renewable energy power. (May 2020) - Li, Jinghua; Zhu, Mengshu; Liang, Junjie
Highlights: The generalized load patterns considering the coupling of the active load and renewable energy are investigated. Three linkage models of the active load and renewable energy are constructed. Based on the proposed linkage model, the generalized load data is generated. DBSCAN clustering algorithm is applied to extract typical generalized load pattern. The sensitivity analysis of influent factors on the generalized load is done. Abstract: Due to the coupling of renewable energy (RE) generation and demand response, the load pattern changed greatly. The coupled loads are called generalized loads (GL). The simulation and analysis of GL pattern are necessary for the planning and operation of the future smart grid. However, because the influence factors of the GL model are very complex, there is no mathematical analytical model that accurately describes the linkage response between the active load and RE. In this paper, a mathematical model for formulating GL profile pattern is proposed. First, three linkage models of active load and renewable energy are constructed, including transferable load, interruptible load, and uncontrollable load. Based on three models, three kinds of active loads are generated. Second, the primary GL data is formed by adding base loads and active loads. However, the primary GL patterns are chaos and unrecognized. For solving this problem, Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering algorithm is applied to extract typical GL pattern. Then, the features of extracted GL patterns are analyzed. Furthermore, the sensitivity analysis of influent factors on GL is done, including the influences of RE permeability, active load ratio, and composition ration of the active load. The results show that the pattern of GL, which is influenced by RE and active load, is very different from the traditional load. The study of GL pattern is essential and can provide a reference for the prediction, planning, and operation of the smart grid.