Power System Sensitivity Identification—Inherent System Properties and Data Quality

The increasing amount of data recorded during power system operations and recently developed data-driven methods make online sensitivity identification (SI) a possibility. However, due to the inherent properties of power systems - nonlinearity, time variance, and collinearity - the effective data that carry the sensitivity information are insufficient. Consequently, the online SI information collected with existing methods may result in unexpected estimates. In this paper, a sufficient effective data condition that guarantees the success of online SI is proposed. The inherent properties of power systems and their impacts on this condition are then investigated. A series of metrics to qualify online whether the data meet the condition is put forward to assess the online SI results. A method is also proposed to select the effective data to improve the online computational efficiency. Finally, the findings and methods are validated in an eight-generator 36-node bus system with operations data recorded from actual power systems.