Abstract
In this paper, a big data visualization platform is designed to discover the hidden useful knowledge for smart grid (SG) operation, control and situation awareness. The spawn of smart sensors at both grid side and customer side can provide large volume of heterogeneous data that collect information in all time spectrums. Extracting useful knowledge from this big-data poll is still challenging. In this paper, the Apache Spark, an open source cluster computing framework, is used to process the big-data to effectively discover the hidden knowledge. A high-speed communication architecture utilizing the Open System Interconnection (OSI) model is designed to transmit the data to a visualization platform. This visualization platform uses Google Earth, a global geographic information system (GIS) to link the geological information with the SG knowledge and visualize the information in user defined fashion. The University of Denver's campus grid is used as a SG test bench and several demonstrations are presented for the proposed platform.
| Original language | American English |
|---|---|
| Number of pages | 6 |
| DOIs | |
| State | Published - 2016 |
| Event | 2016 North American Power Symposium (NAPS) - Denver, Colorado Duration: 18 Sep 2016 → 20 Sep 2016 |
Conference
| Conference | 2016 North American Power Symposium (NAPS) |
|---|---|
| City | Denver, Colorado |
| Period | 18/09/16 → 20/09/16 |
NREL Publication Number
- NREL/CP-5D00-67825
Keywords
- Apache Spark
- big data
- geographic information system
- knowledge discovery
- parallel computation
- smart sensor