Title :
On the impact of SmartGrid metering infrastructure on load forecasting
Author :
Alizadeh, Mahnoosh ; Scaglione, Anna ; Wang, Zhifang
Author_Institution :
Sch. of Electr. & Comput. Eng., Univ. of California, Davis, CA, USA
fDate :
Sept. 29 2010-Oct. 1 2010
Abstract :
Accurate real-time load forecasting is essential for the reliable and efficient operation of a power system. Assuming that the number of electrical vehicles will increase substantially in the near future, the load profiles of the system will become too volatile and unpredictable for the current forecasting techniques. We propose to utilize the accurate reporting of the emerging Advanced Metering Infrastructure (AMI) to track the incoming PHEV load requests and their statistics. We propose a model for the PHEV loads statistics and an optimization of the generation dispatch that uses the full statistical information. This model offers an example of the potential impact of the smart metering infrastructure currently being deployed.
Keywords :
hybrid electric vehicles; load forecasting; power generation dispatch; power meters; smart power grids; PHEV load requests; PHEV loads statistics; SmartGrid metering infrastructure; advanced metering infrastructure; generation dispatch; load forecasting; power system reliability; smart metering infrastructure; Biological system modeling; Data models; Load modeling; Mathematical model; Predictive models; Random variables; Time series analysis;
Conference_Titel :
Communication, Control, and Computing (Allerton), 2010 48th Annual Allerton Conference on
Conference_Location :
Allerton, IL
Print_ISBN :
978-1-4244-8215-3
DOI :
10.1109/ALLERTON.2010.5707109