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GITA 1998


SCADA and Real-Time Systems
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Integrating DMS and GIS The Time Has Come

Tony Sileo
Director of Product Development GeoData Solutions, Inc.
8620 Wolff Court Suite 250
Westminster, Colorado 80030
tony@igeodata-gis.com
http://geodata-gis.com


Introduction
This paper fmt provides an overview of the key features and requirements of a Distribution Management System (DMS). It then explores the advantages of a DMS that is tightly integrated with a Geographic Information System (GIS). Next, the paper presents a database architecture that combines the benefits of long transaction GIS databases with the efilciency and scalability of conventional short transaction databases. Finally, the paper shares key results and conclusions fi-om a proof-of- concept laboratory and discusses progress since its completion and plans for the future.

Features of a DMS
A Distribution Management System provides control, troubleshooting and analysis of an electric power distribution network. Performing these fimctions well requires reliable, eff]cient interfaces with many other utility information systems. A successful DMS must include a fast, well-organized, intuitive user interface as well as fimdamental network modeling and analysis capabilities. Finally, the DMS must be available 24 hours a day, 7 days a week, and it must maintain acceptable performance under the highest load conditions. See (Briody 1997) for an excellent overview of DMS functionality.)

Interface with Other Information Systems
A full-featuredDMS will include well-defined interfaces for exchanging data and interacting with some or all of the utility information systems listed in this section. In general, an open database architecture with well-defined application programming interfaces will provide the most adaptable, extensible approach to systems integration. For each system, the description includes key data items and indicates whether those items are inputs or outputs of the DMS. Ideally, all data should be pushed to its destination(s) from the system that creates the data (the source). This is the most efficient approach and avoids time lags and wasted resources introduced by polling processes that have to watch for new data and pull it from the source to the destination.

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