An automated strategy for the processing and analysis of distribution automation data

Recent installations of distribution automation technology have made it possible to monitor a number of locations in the distribution system on a continuous long-term basis. Unfortunately, due to the resulting volume of distribution automation data, it is difficult and time-consuming for humans to analyze these data effectively. The authors describe automated strategies for the analysis of these data that will lead to more effective uses of this information for improving upon operating, planning, and design practices. To do this, a novel approach for automating the management of distribution data was designed, and a prototype was implemented. The resulting program, TAME, uses a combination of procedural and knowledge-based programming techniques to sift through the real-time data with the purpose of identifying patterns or trends which characterize the performance of the distribution system. Examples pertaining to volt/Var control and alarm processing are employed to illustrate the benefits of automated data processing and analysis