Abstract—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 protect and optimize 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
emanated from existing and new information sources with the grow
of Smart Grid information space. In particular, dynamic DR algorithms
may 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.
%0 Conference Paper
%1 Zhou:itng:2012
%A Zhou, Qunzhi
%A Natarajan, Sreedhar
%A Simmhan, Yogesh
%A Prasanna, Viktor
%B International Conference on Information Technology : New Generations
(ITNG)
%D 2012
%K grid, information integration, peer reviewed semantic, smart usc,
%P 775--782
%R 10.1109/ITNG.2012.150
%T Semantic Information Modeling for Emerging Applications in Smart
Grid
%U http://dx.doi.org/10.1109/ITNG.2012.150
%X Abstract—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 protect and optimize 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
emanated from existing and new information sources with the grow
of Smart Grid information space. In particular, dynamic DR algorithms
may 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.
@inproceedings{Zhou:itng:2012,
abstract = {Abstract—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 protect and optimize 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
emanated from existing and new information sources with the grow
of Smart Grid information space. In particular, dynamic DR algorithms
may 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.},
added-at = {2014-08-13T04:08:36.000+0200},
author = {Zhou, Qunzhi and Natarajan, Sreedhar and Simmhan, Yogesh and Prasanna, Viktor},
biburl = {https://www.bibsonomy.org/bibtex/2a7f504a727f72d45eb7fff84fb78476c/simmhan},
booktitle = {International Conference on Information Technology : New Generations
(ITNG)},
doi = {10.1109/ITNG.2012.150},
interhash = {f6a922db9044312ec08d12b7f17cd335},
intrahash = {a7f504a727f72d45eb7fff84fb78476c},
keywords = {grid, information integration, peer reviewed semantic, smart usc,},
owner = {Simmhan},
pages = {775--782},
timestamp = {2014-08-13T04:08:36.000+0200},
title = {Semantic Information Modeling for Emerging Applications in Smart
Grid},
url = {http://dx.doi.org/10.1109/ITNG.2012.150},
year = 2012
}