Research on Advanced Power System Analysis and Control Based on Big Data Technology

Abstract

The continuous development of big data technology has brought many new ideas and challenges to power system analysis and control. With the development of distributed power sources, energy storage, monitoring, and protection devices, the traditional distribution network has gradually evolved into much Active distribution networks with control ability. At present, the power quality of the power system is a hot issue in power system research. There are many types of power quality disturbances, mainly including single type and compound type disturbances. The thesis first uses Matlab to model and simulate the power quality disturbance signal and then obtains a complex number matrix through S transform, then calculates its modulus, and extracts the corresponding characteristic parameters to form the characteristic vector. Secondly, the thesis uses a simple and efficient decision tree to correctly classify and identify power quality disturbance signals. Finally, the thesis’s simulation analysis results show that this research method combining S transform and decision tree has high recognition accuracy and strong anti-noise ability, which is a very suitable method.