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tor descriptions and use the ontology to find out, how
to treat them during evaluating a schedule, how to
convert indicators or how to map them to each other.
5 CONCLUSIONS AND FURTHER
WORK
It is to be expected that future architectures for smart
grids will call for the ability of DER to frequently at-
tach themselves to different groups depending on the
situation at hand. Unlike VPPs, such groups will be
drawn together rather by market forces. This transi-
tion to volatile groups of independent DER will be
gradual. Due to universal applicability to central,
decentral and distributed scheduling approaches, our
method should be able to serve the needs during the
whole transition process as the ontology approach is
independent of specific smart grid architectures.
Research has just started out. Up to now we
have gained a clear understanding of how the inte-
gration of distributed knowledge about individual en-
vironmental performance into a centralized (and in
the long run decentralized) energy management con-
trol scheme might be done. A meta-model of search
spaces that is based on geometric subspace descrip-
tions, provides an ideal connecting point for the in-
tegration of environmental information about alterna-
tives by simply extending the mathematical model of
a schedule to additional dimensions for EPIs. In this
way, necessary information is directly incorporated
into the meta-model of the load schedules and there-
with into the schedules themselves.
At the same time, correct interpretation of the EPI
values may be ensured with the help of a extended
EPI ontology. Our next steps will be the extension of
the OEPI ontology as discussed and the definition of
a standard set of EPIs for the sketched scenarios be-
fore we will start implementing a planned simulation
environment to test our approach.
ACKNOWLEDGEMENTS
This work was funded by the European research
project OEPI (Solutions for Managing Organizations
Environmental Performance Indicators, 748735).
REFERENCES
Blank, M., Gerwinn, S., Krause, O., and Lehnhoff, S.
(2011). Support vector machines for an efficient rep-
resentation of voltage band constraints. In Innovative
Smart Grid Technologies. IEEE PES.
Bontas, E. P.; Mochol, M. (2005). Towards a reuse-oriented
methodology for ontology engineering. In 7th Inter-
national Conference on Terminology and Knowledge
Engineering, Copenhagen, Denmark. Shaker Verlag,
Aachen.
Bremer, J., Rapp, B., and Sonnenschein, M. (2010). Sup-
port vector based encoding of distributed energy re-
sources feasible load spaces. In IEEE PES Confer-
ence on Innovative Smart Grid Technologies Europe,
Chalmers Lindholmen, Gothenburg, Sweden.
Bremer, J., Rapp, B., and Sonnenschein, M. (2011a). En-
coding distributed search spaces for virtual power
plants. In IEEE Symposium Series in Computational
Intelligence 2011 (SSCI 2011), Paris, France.
Bremer, J., Rapp, B., and Sonnenschein, M. (2011b). In-
cluding Environmental Performance Indicators into
Kernel based Search Space Representations. Infor-
mation Technologies in Environmental Engineering
(ITEE 2011).
Dada, A., Staake, T., and Fleisch, E. (2010). Reducing envi-
ronmental impact in procurement by integrating mate-
rial parameters in information systems: The example
of apple sourcing. AMCIS 2010 Proceedings.
H
ˇ
reb
´
ı
ˇ
cek, J., Misa
ˇ
rov
´
a, P., and Hyr
ˇ
slov
´
a, J. (2007). Envi-
ronmental Key Performance Indicators and Corporate
Reporting. In Environmental Accounting and Sustain-
able Development Indicators (EA-SDI 2007), pages
978–980. Universita Jana Evangelisty Purkyn
ˇ
e.
IEC 61850-7-420:2009 (2009). Communication networks
and systems for power utility automation - Part 7-420:
Basic communication structure - Distributed energy
resources logical nodes. IEC, Geneva, Switzerland.
Lukovic, S., Kaitovic, I., Mura, M., and Bondi, U. (2010).
Virtual power plant as a bridge between distributed en-
ergy resources and smart grid. Hawaii International
Conference on System Sciences, 0:1–8.
Meyerholt, D., Marx G
´
omez, J., Dada, A., Bremer, J., and
Rapp, B. (2010). Bringing sustainability to the daily
business: The oepi project. Proceedings of the Work-
shop ”Environmental Information Systems and Ser-
vices - Infrastructures and Platforms.
Rapp, B., Solsbach, A., Mahmoud, T., Memari, A., and Bre-
mer, J. (2011). It-for-green: Next generation cemis for
environmental, energy and resource management. In
Pillmann, W., Schade, S., and Smits, P., editors, En-
viroInfo 2011 - Innovations in Sharing Environmental
Observation and Information, Proceedings of the 25th
EnviroInfo Conference ’Environmental Informatics’,
pages 573 – 581. Shaker Verlag. ISBN 978-3-8440-
0451-9.
Teuteberg, F. and G
´
omez, J. M. (2010). Green comput-
ing & sustainability - status quo und herausforderun-
gen f
¨
ur buis der n
¨
achsten generation. Praxis der
Wirtschaftsinformatik, 47(274):6–17.
Thomas, B. (2007). Mini-Blockheizkraftwerke: Grundla-
gen, Ger
¨
atetechnik, Betriebsdaten. Vogel Buchverlag.
Uslar, Mathias; Schmedes, T. L. A. L. T. W. L. A. H.-J.
(2005). Interaction of ems related systems by using
the cim standard. In Proceedings of the ITEE 2005
Magdeburg, pages 596–610. Shaker Verlag, Aachen.
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