| Title |
Search of Stable Operation through Statistical Analysis of PMU Generated Big Data of Substation |
| Authors |
이경민(Kyung-Min Lee) ; 박철원(Chul-Won Park) |
| DOI |
https://doi.org/10.5370/KIEE.2021.70.12.2070 |
| Keywords |
Big data; PMU; Power quality; R Programming; RESs; Stable operation; Statistical techniques; S/S |
| Abstract |
In order to monitor, analyze, and control RESs operated in connection with the power system in real-time, the installation and distribution of PMUs are expanding. Accordingly, there is a need for a method that can effectively use the large-capacity big data generated by the PMU. In Gangwon-do, more than 3GW of RES is expected to be connected by 2025. In this paper, in order to cope with the volatility of RESs and to improve reliability of power system in Gangwon-do, the effect on the power system is effectively investigated through the PMU-generated big data of S/S connected with RESs. First, big data is collected using the PMU and F/R installed in the S/S. The instantaneous voltage change rate is calculated, and statistical techniques such as boxplot, kernel density, correlation index, and harmonic average are implemented using R programming, which is specialized for large data statistics and analysis. Finally, the power quality is analyzed through the implemented technique. So, it is thought to be helpful in research on the stable operation of RESs linked systems |