Blueprinting a Smart Grid Automated Demand Response System for Data Mining Research and Education by Rasmus U. Pedersen

Next generation data mining platforms will include energy management in smart grids and telematics. Wireless sensor networks, smart grid infrastructure, and smart grid aware household appliances are important IT platforms addressing environmental sustainability. We propose a research and educational platform blueprint for next generation data mining within smart grid and possibly telematics research. We use mostly Java-based tools and include a running demonstration of using Lego Mindstorms to receive and act on smart grid pricing information. Furthermore, the data mining platform Rapid Miner is used to demonstrate how embedded usage statistics data can be classified with a popular classification algorithm.

Tuesday, December 13, 2011 - 12:30 to 13:00

As the importance of eco-sustainable growth becomes increasingly important, scientific research communities support the initiatives of governments and organizations worldwide. Next generation data mining platforms will include energy management in smart grids and telematics. Wireless sensor networks, smart grid infrastructure, and smart grid aware household appliances are important IT platforms addressing environmental sustainability. The data mining community is well positioned to provide embedded intelligence to the smart grid. We propose a research and educational platform blueprint for next generation data mining within smart grid and possibly telematics research. We use mostly Java-based tools and include a running demonstration of using Lego Mindstorms to receive and act on smart grid pricing information in relation to a US-based open automatic demand response (Open ADR1) standard REST web service event. Furthermore, the data mining platform Rapid Miner is used to demonstrate how embedded usage statistics data can be classified with a popular classification algorithm.

Work carried out in collaboration with Katharina Morik, TU Dortmund, Artificial Intelligence Group.

The page was last edited by: Communications // 12/06/2011