Efficient Smart Grid Data Updating and Diagnostics for Transformer Loading Management

This paper develops a business process to maintain a clean Smart Grid data. Such data involves Geographic Infor-mation System (GIS) network data and Supervisory Control and Data Acquisition (SCADA) time-series data. For accurate distri-bution transformer optimization, GIS data gap must be managed. Updating and diagnostics of such data must be optimized due to limited metering devices. This paper develop portable tools and design data ecosystem separate from Smart Grid environment for efficient and non-disruptive GIS diagnostics. It takes 33 minutes to build from scratch a fresh network model with customer loads from GIS, Customer and SCADA data. Compared to 42 hours of Smart Grid network model promotion, 98.7% reduction of time in new data build-up for updated diagnostics. Reportorial submission to energy regulatory, efficient system operations, and effective planning relies on GIS accuracy and realtime SCADA availability.