External weather conditions have significant effects on the operation of composite power systems. Stochastic renewable generations, random loads, dynamic thermal ratings, and failure probabilities of outdoor power devices are all influenced by diverse meteorological factors. To integrate the probabilistic impacts of multiple meteorological factors and their resulting uncertainties, a new nested sampling framework for probabilistic operational reliability evaluation of composite power systems is proposed. As one critical step of the framework, a general modeling method to fit the probability distribution of each meteorological factor at each time point by historical weather records is presented in details, and several specific distributions are introduced for the first time to refine the accuracy of probabilistic weather representation. In subsequent tests, the actual failure records and corresponding meteorological data are used to validate the performance of the proposed framework. Several existing methods, considering but not fully considering meteorological effects, are adopted for comparisons to verify the effectiveness of the proposed method in the test case. As one benefit of the proposed framework, uncertainty importance measures of all involved random variables are available and discussed as well.
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Chen et al. (2019) studied this question.
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