The probabilistic distribution of cascading outages is one of the main measures to describe the propagation of cascading outages, and to evaluate the risk of the large scale outages of the power system. Historical outage data has always been used for power system reliability evaluation, and by combined with the branching process model, it is used for cascading outage analysis for a regional power grid. Based on the 14-year utility historical outage data from a regional power grid in China, several known probabilistic models are tested and compared, and a Borel-Tanner branching process model is proposed to estimate the probabilities of cascading line outages. Statistical error analysis is performed to study the effectiveness of applying the Borel-Tanner model to practical grid risk management. Results indicate that the empirical distribution of the total number of line outages is approximated well by the Borel-Tanner model. For the same confidential level, the estimation of the probability distribution of the larger cascades by the Borel-Tanner branching process model requires significantly fewer recorded outage data than empirical estimation by a factor of 10-1.%连锁故障规模的概率分布描述了电网连锁故障的传播特点，是衡量电网发生大规模停电故障概率的有效方法之一。针对历史故障统计数据进行计算，是传统电力系统可靠性评估方法之一。将其与分支过程模型结合，用于区域电网的连锁故障分析。采用某区域电网14年历史故障数据为样本数据，针对多种概率模型进行比较分析，提出采用波雷-坦尔分支过程模型计算该区域电网连锁故障规模的概率分布，并采用误差分析研究了波雷-坦尔模型应用于实际电网风险管理的有效性和可能性。结果表明，波雷-坦尔模型能够很好地估计线路故障规模的概率分布。在相同置信度要求下，基于波雷-坦尔模型估计故障概率分布所需样本数据比直接根据实际故障数据计算所得概率分布所需样本数据降低一个数量级。
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