논문 해외 국제전문학술지(SCI급) Probabilistic Power Flow Analysis of Bulk Power System for Practical Grid Planning Application
- 학술지 구분 국제전문학술지(SCI급)
- 게재년월 2019-04
- 저자명 S. Song, C. Han, S. Jung, M. Yoon, G. Jang
- 학술지명 IEEE Access
- 발행처명 IEEE Xplore
- 발행국가 해외
- 논문언어 외국어
- 전체저자수 5
홈페이지논문 초록 (Abstract)
The sizes of PV power plants have grown in such a way that their effects on the power system can no longer be neglected. In order to address these issues, grid operators are forced to expand grid connection points, and a power flow analysis considering uncertain renewable generation is required. Thus, a modified probabilistic power flow (PPF) analysis for practical grid planning is suggested in this paper. The regularity and randomness of PV power are modeled by a Monte Carlo-based probabilistic model combining both k-means clustering and the kernel density estimation method. The certain cluster group is selected so as to reflect the severe PV generation scenario, and the chi-square test to represent the n th conservative network planning was suggested. In order to provide the power flow result more effectively, a mapping function of graphic representation based on a significant grid code violation is provided in an automatic PPF tool written by Python scripts. Following this procedure yields a reasonable network design for various renewable energy penetration levels.