Short-Term Reliability Assessment of UHVdc Systems Based on State Aggregation With SMP

The short-term reliability of the ultra-high-voltage dc (UHVdc) systems has enormous influence on the security of the whole power system. The frequency and duration (F&D) algorithm based on the Markov process (MP) will reduce the accuracy of the short-term reliability indices, due to the exponentially distributed parameters and the strict premises for the state aggregation and combination. In this paper, the short-term aggregation algorithm based on the semi-MP (SMP) is improved. The aggregated transfer rates are obtained by the definition of the semi-Markov kernel elements and the invariability of the transfer probabilities before and after aggregation. The algorithm is applied to the series structure system, which is common in UHVdc. The aggregated kernel matrix and instantaneous transfer probability matrix are derived from those before aggregation directly. A new method is proposed to describe the combined transfer rates by matrices combination and deleting the nonexistent states and transitions, which requires less calculation effort. The Erlang and Weibull distributions are first used to fit the bell-shaped probability density functions (PDFs) of the repair times of the equipments in the UHVdc. The numerical examples show that, compared with the SMP algorithm, the traditional F&D algorithm overestimates the instantaneous equivalent outage hours of the UHVdc. The error is originated from that the F&D algorithm regards the aggregated system as a MP while it is non-Markovian. To show the effectiveness of the bell-shaped repair time, the Erlang and Weibull distributions are compared with the exponential one by the reliability indices. The differences are result from the different PDFs of these distributions.