Synergizing PMU Data From Multiple Locations in Indian Power Grid-Case Study

Abstract

Synchrophasor technology improves power grid visibility by installing phasor measurement units (PMUs) over a wide area in the power system. Big data received from PMUs contains important information about grid behavior. This information is useful in monitoring the safety and security of the grid. An extensive state-of-the-art review of big data analytics and its prime applications in power systems are expressed in this paper. It presents, a general background in data analysis techniques such as exploratory data analysis, statistical data analysis, and unsupervised data mining techniques like clustering. Two 400 kV transmission line tripping events are analyzed from the data recorded by the PMUs installed in the western part of the Indian grid i.e., Maharashtra State Electricity Transmission Company Limited (MSETCL) grid. The box plots, Correlogram, and the formation of clusters carried out for the PMU data recorded under ambient and disturbance events. This provides insights on how effective big data helps to make the right decision at right time for effective management of the power grid under normal and contingency conditions.

Keywords

• Phasor measurement unit (PMU)
• box plot
• connectivity index
• correlation technique
• Dunn index
• Hierarchical clustering