Clustering and decision tree based analysis of typical operation
In this paper, a clustering and decision tree-based scheme is proposed for the analysis of the typical operation modes of power systems. Specifically, the k-means++
After the system operation is preprocessed, the typical operation modes analysis is conducted with the following three stages: Firstly, the k-means + + clustering algorithm is used to classify the system operation data into different groups, which represent the typical operation modes.
The extraction of typical operating modes is of great importance for the analysis of power system operation, which could present the main characteristics of the power system and provide deep insights into system planning for system operators, .
The real operation data of the power system has strong periodicity and strong correlation. In the corresponding comparative analysis of the data, the power system operation data set is preprocessed by the combination of normalization, time-series singular spectrum analysis, and principal component analysis (PCA) technique.
Abstract The high renewable penetration will cause the power system operation mode (PSOM) to change frequently. At present, the selection of PSOM mainly depends on the experience of relevant staff....
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