A Vine-Copula Based Voltage State Assessment with Wind Power Integration

• Main Authors: Xiaolu Chen, Ji Han, Tingting Zheng, Ping Zhang, Simo Duan, Shihong Miao
• Format: Article
• Language: English
• Published: MDPI AG 2019-05-01
• Series: Energies
• Subjects: voltage state assessment; large-scale wind power integration; vine-copula; probabilistic load flow; east Inner Mongolia power system
• Online Access: https://www.mdpi.com/1996-1073/12/10/2019

With the increasing rate of wind power installed capacity, voltage state assessment with large-scale wind power integration is of great significance. In this paper, a vine-copula based voltage state assessment method with large-scale wind power integration is proposed. Firstly, the nonparametric kernel density estimation is used to fit the wind speed distribution, and vine-copula is used to construct the wind speed joint distribution model of multiple regions. In order to obtain voltage distribution characteristics, probabilistic load flow based on the semi-invariant method and wind speed independent transformation based on the Rosenblatt transformation are described. On this basis, a voltage state assessment index is established for the more comprehensive evaluation of voltage characteristics, and a voltage state assessment procedure is proposed. Taking actual wind speed as an example, the case study of the IEEE 24-node power system and the east Inner Mongolia power system for voltage state assessment with large-scale wind power integration are studied. The simulation results verify the effectiveness of the proposed voltage state assessment method.