采用瞬时概率的运行可靠性短期评估

提出运行可靠性短期评估的概念和算法，基于元件实时可靠性模型研究运行状态对系统可靠性的影响，基于马尔柯夫过程的瞬时状态概率进行系统状态预测和评估，研究系统在当前运行状态下的短期可靠性水平。通过分析与算例表明，系统短期与长期的可靠性存在不同，基于瞬时概率进行评估才能表征系统短期的可靠性水平。进一步综合考虑系统状态的可能性与严重性，定义了指标精度。按照概率大小进行系统状态选择，按照指标精度进行状态截止，并研究了状态截止精度随预测时间的变化关系，表明短期评估只需选择少量系统状态就能满足较高的评估精度，具备在线应用的前景，通过算例IEEE-RTS进行了验证。

Short-term Operational Reliability Evaluation By Using Time Dependent State Probability

An algorithm is proposed to study the online short-term reliability of power system under the real-time operating condition. The influence of the variable operating state on system's reliability is studied based on component's real-time reliability model. Markov process is applied to obtain the time dependent state probabilities of components. The short-term reliability is analyzed based on the time dependent state probability. The analysis and the evaluation results of IEEE-RTS indicate that there are significant differences between the short-term and long-term reliability indices. The short-term reliability evaluation should therefore be based on the time dependent state probability. The index accuracy is defined considering the probability and severity of each system scheme. The system schemes are selected in descending probability order. The stopping rule for the state selection is the index accuracy. The relationship between scheme selection accuracy and the forecasting time is also studied. The results show that only a small number of system schemes are required to achieve the high accuracy of the short-term reliability index. Hence, evaluation can be performed in the online environment. The proposed algorithm is applied to the IEEE-RTS.