An Analytical Method for Calculating Probability Density Distribution of HVDC System Reliability Index

Traditional high voltage direct current transmission (HVDC) system uses expectation-based indices to represent the system average reliability level. However, only limited information can be learned from such indices. It is necessary to present the results of reliability evaluation from the perspective of the probability distribution. Based on the idea of the minimum cut set, this paper presents an analytical method to calculate the probability density distribution of the HVDC system reliability index. First, assuming that the minimum cut set events obey Poisson distribution, the approximate analytical expression of the HVDC system reliability index is derived. Then, a large number of HVDC system reliability index samples are obtained through the analytical expression. Combined with the nonparametric kernel density estimation technique, the probability density distribution curve of the HVDC system reliability index is obtained. The proposed analytical method can not only efficiently calculate the probability density distribution of the HVDC system reliability index, but also provide useful information for HVDC system planning and operation. Finally, the correctness and effectiveness of the proposed method are verified on Yunnan-Guangdong HVDC Transmission Demonstration Project.