DocumentCode :
3219444
Title :
Integrating advanced metering data into the enterprise
Author :
King, Chris
Author_Institution :
eMeter Corporation, USA
fYear :
2009
fDate :
15-18 March 2009
Firstpage :
1
Lastpage :
1
Abstract :
This presentation addresses the challenges associated with integrating advanced metering data into the utility enterprise. These challenges go well beyond simple developing and implementing interfaces that connect the systems that collect advanced meter data to the systems that use the data in business processes, such as billing and outage management. The first step in a useful and successful integration is the basic functions of data collection, data storage, and data delivery in a predictable, timely, and reliable manner. To support these functions, the integration platform must address the inevitable weaknesses associated with any data collection technology as well as the day to day issues that arise in processing and managing such data. For instance, the integration must include a robust data synchronization engine to ensure that the integration software knows the basics - expected data types and sources by meter and service delivery point - as well as more advanced information, such as schedules for delivering billing determinants to the CIS system. As another example, the integration platform must include the tools to detect and resolve data exceptions that arise in the data stream or disrupt the flow of data. Finally, the integration platform must account for and accommodate the limitations of the enterprise systems receiving the data. The outage management system may not be able to handle large data volumes triggered by wide-scale outages, so the integration platform must be able to pre-process, or filter, the outage data to deliver only the most important data. These and related issues will be covered in the presentation.
Keywords :
Artificial neural networks; Clustering algorithms; Job shop scheduling; Load forecasting; Power generation; Power system modeling; Power system planning; Power system security; Predictive models; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Systems Conference and Exposition, 2009. PSCE '09. IEEE/PES
Conference_Location :
Seattle, WA, USA
Print_ISBN :
978-1-4244-3810-5
Electronic_ISBN :
978-1-4244-3811-2
Type :
conf
DOI :
10.1109/PSCE.2009.4840244
Filename :
4840244
Link To Document :
بازگشت