The Distribution Management System (DMS) is a key smart grid technology; and complete, up-to-date network asset information is mandatory in order to develop and maintain the accurate network model on which the DMS is based. The utility’s enterprise geographic information system (GIS) database stores and maintains this network asset data and can manage the workflow for updating this vital information.
In evaluating its readiness for Smart Grid implementation, the utility needs to assess the completeness, accuracy and backlog of the data contained in its GIS. One utility determined that inaccurate data accounted for a 50 percent deviation between DMS-modeled load flow and observed load flow. This discrepancy made it clear to the utility that its DMS is unusable to predict voltage reduction gains and volt/VAR optimization – the very operational functions the utility targeted in its smart grid strategy.
Many errors in the GIS data can be attributed to a complex or duplicative graphic work design (GWD) process, from initiation, through design, review, lockdown, posting and as-built updating. A GIS-based GWD works within the GIS database and eliminates re-digitization of designs; takes advantage of network connectivity for QA/QC checks to improve data accuracy and completeness; and significantly reduces backlog and speeds network updates. This approach not only streamlines the design process but also yields more accurate asset information that supports network modeling, maintenance and vital planning and decision making processes.
A quantitative comparison of the time involved in the typical workflow of a small design project, completed by means of manual sketching and also with GIS-based and CAD-based methodologies, shows the time savings related to the GIS-based GWD are accountable and significant. The same productivity advantages were seen when comparing typical workflows involved in a large design project.
GIS-based design provides faster update of the network model, making it more appropriate for supporting DMS functionality – the heart of an effective smart grid strategy.