Semantic Information Modeling for Emerging Applications in Smart Grid
Smart Grid modernizes power grid by integrating digital and information technologies. Millions of smart meters, intelligent appliances and communication infrastructures are under deployment allowing advanced IT applications to be developed to secure and manage power grid operations. Demand response (DR) is one such emerging application to optimize electricity demand by curtailing/shifting power load when peak load occurs. Existing DR approaches are mostly based on static plans such as pricing policies and load shedding schedules. However, improvements to power management applications rely on data emanating from existing and new information sources with the growth of Smart Grid information space. In particular, dynamic DR algorithms depend on information from smart meters that report interval-based power consumption measurement, HVAC systems that monitor buildings heat and humidity, and even weather forecast services. In order for emerging Smart Grid applications to take advantage of the diverse data influx, extensible information integration is required. In this paper, we develop an integrated Smart Grid information model using Semantic Web techniques and present case studies of using semantic information for dynamic DR. We show the semantic model facilitates information integration and knowledge representation for developing the next generation Smart Grid applications.
- Research Organization:
- City of Los Angeles Department
- Sponsoring Organization:
- USDOE Office of Electricity (OE)
- DOE Contract Number:
- OE0000192
- OSTI ID:
- 1332534
- Report Number(s):
- DOE-USC-00192-102
- Resource Relation:
- Conference: International Conference on Information Technology: New Generations Las Vegas, NV, USA April 16 - 18, 2012
- Country of Publication:
- United States
- Language:
- English
Similar Records
Secure Interoperable Open Smart Grid Demonstration Project
On Using Cloud Platforms in a Software Architecture for Smart Energy Grids