Song Shuyong

Diagnosis model of low voltage generation based on large data

Voltage is one of the measurement standard of power quality. The issue of low voltage in distribution network seriously affect the social economic development and peoples life. Consequently, it would optimize low voltage investment program, clear direction of low voltage investment and provide decision support for the management of low voltage. Canopy- Kmeans is one of the widely used classical partition clustering algorithm. Support vector machine is a kind of sorting algorithms that could take full advantage of limited learning sample to acquire generalization. Both Canopy-Kmeans and Support Vector Machine have better behavior and precision rate. However, the runtime and RAM would be the bottleneck in the case of large amount of data. The application of data mining algorithm based on big data is particularly important. This paper take advantage of distributed Kmeans and SVM algorithm to realize diagnosis model of cause of low voltage based on big data platform of Hadoop. Experiments have shown that this method has a higher accuracy and reliability compared to traditional Kmeans and SVM algorithm.

Study on tuning method of low excitation limit curve of Generator

The low excitation limit curve of generator which is tuned correctly can helps to ensure the normal operation of generator, because the generator and power system will be separated if the voltage of auxiliary power is too low, loss of field protection is in operation or static stability of generator is not enough. This paper describes a tuning method of low excitation limit curve of Generator. Experiment proved that the method is practical and effective.

Research on grid-connected and economy of distributed wind power generation

This paper introduced several types of distributed wind turbines, discussed the impact on grid-connected and put forward the measures. Combined with the wind data in Shanghai area, economy of the currently used widely distributed wind power generator was calculation. The results show that, the distributed wind power generator had better stability and economy, suitable for application in the surrounding areas of the city.