전압 모니터링과 확률적 분석에 기반한 순간전압강하 평가 연구

Abstract

This thesis presents a method to evaluate the long-term tendency of voltage sag occurrence, one of the most important power quality problems. Voltage sag assessment basically includes a statistical analysis method based on voltage monitoring and a simulation evaluation method using system data. Along with the development of precision measurement equipment, power quality monitoring systems are widely installed and operated. Therefore, voltage sag assessment is possible based on these monitoring systems. However, in order to obtain a reliable evaluation result, it is necessary to acquire data for a long period of time, and there is a limitation that a relatively large cost is required to evaluate many points in the system. On the other hand, the simulation method based on past fault occurrence data can quickly assess the expected voltage sag frequency at sensitive load points if necessary data is provided. Also, the simulation method can evaluate voltage sag performance for planned systems and cases where actual monitoring is impossible. However, the simulation-based assessment is only possible to evaluate voltage sags caused by faults in the system and it is difficult to reflect voltage sags due to other causes. This thesis proposes a new evaluation method that performs voltage sag assessment based on both voltage monitoring and simulation. The method overcomes the limitations of existing assessment approaches. In the long term, the voltage sag assessment based on monitoring is expected to effectively evaluate system voltage sag performance. However, in the case of insufficient monitoring data and period, the reliability of voltage sag assessment could be low. Therefore, a novel method to correct low reliable results in voltage sag assessment is proposed through the stochastic analysis and simulation-based assessment. In addition, a assessment method to consider system operating conditions is introduced in the simulation-based assessment. In most of the existing simulation-based assessment, it is performed by assuming the annual average system operation condition or by considering only the maintenance scheduling of generators. However, since Korea has four different seasons, load conditions, fault rates and operating conditions change significantly throughout the year. The system operation plan and the transmission and distribution system maintenance plan are determined according to the forecasting of power demand. For reliable evaluation, it is necessary to reflect such changes in simulation-based assessment.