MIRABEL DW: Managing Complex Energy Data in a Smart Grid

  • Laurynas Siksnys
  • Christian Thomsen
  • Torben Bach Pedersen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7448)

Abstract

In the MIRABEL project, a data management system for a smart grid is developed to enable smarter scheduling of energy consumption such that, e.g., charging of car batteries is done during night when there is an overcapacity of green energy from windmills etc. Energy can then be requested by means of flex-offers which define flexibility with respect to time, amount, and/or price. In this paper, we describe MIRABEL DW, a data warehouse (DW) for the management of the large amounts of complex energy data in MIRABEL. We present a unified schema that can manage data both at the level of the entire electricity network and at the level of individual nodes, such as a single consumer node. The schema has a number of complexities compared to typical DW schemas. These include facts about facts and composed non-atomic facts and unified handling of different kinds of flex-offers and time series. We also discuss alternative data modeling strategies and present typical queries from the energy domain and a performance study.

Keywords

Time Series Smart Grid Data Warehouse Dimension Table Legal Entity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Bauer, A., Hümmer, W., Lehner, W.: An Alternative Relational OLAP Modeling Approach. In: Kambayashi, Y., Mohania, M., Tjoa, A.M. (eds.) DaWaK 2000. LNCS, vol. 1874, pp. 189–198. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  2. 2.
    Boehm, M., et al.: Data Management in the M Smart Grid System. In: Proc. of EDBT/ICDT Workshops (2012)Google Scholar
  3. 3.
    Böhlen, M.H., Gamper, J., Jensen, C.S.: Multi-dimensional Aggregation for Temporal Data. In: Ioannidis, Y., Scholl, M.H., Schmidt, J.W., Matthes, F., Hatzopoulos, M., Böhm, K., Kemper, A., Grust, T., Böhm, C. (eds.) EDBT 2006. LNCS, vol. 3896, pp. 257–275. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  4. 4.
    European Network of Transmission System Operators for Electricity. The Harmonised Electricity Market Role Model, version 2011-01 (June 12, 2012), http://www.ebix.org/Documents/role_model_v2011_01.pdf
  5. 5.
    Introduction to Business Requirements and Information Models (June 12, 2012), http://www.ebix.org/documents/Introduction%20to%20ebIX%20Models%200.0.D.pdf
  6. 6.
    IEC61970-301 Ed. 2, Energy management system application program interface (EMS-API) - Part 301: Common information model (CIM) base, International Electrotechnical Commission (2009)Google Scholar
  7. 7.
    Jensen, C.S., Pedersen, T.B., Thomsen, C.: Multidimensional Databases and Data Warehousing. Morgan & Claypool (2010)Google Scholar
  8. 8.
    Konsman, M.J., Rumph, F.J.: MIRABEL Deliverable 2.3: Final data model, specification of request and negotiation messages and contracts (June 12, 2012), http://www.db.inf.tu-dresden.de/miracle/files/deliverables/M18/D2.3_final.pdf
  9. 9.
    Malinowski, E., Zimányi, E.: Advanced Data Warehouse Design From Conventional to Spatial and Temporal Applications. Springer (2009)Google Scholar
  10. 10.
    www.meregio.de/en/ (June 12, 2012)
  11. 11.
    www.mirabel-project.eu/ (June 12, 2012)
  12. 12.
    postgresql.org (June 12, 2012)
  13. 13.
    Song, I.-Y., et al.: An Analysis of Many-to-Many Relationships Between Fact and Dimension Tables in Dimensional Modeling. In: Proc. of DMDW (2001)Google Scholar
  14. 14.
    Šikšnys, L., Khalefa, M.E., Pedersen, T.B.: Aggregating and Disaggregating Flexibility Objects. In: Ailamaki, A., Bowers, S. (eds.) SSDBM 2012. LNCS, vol. 7338, pp. 379–396. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  15. 15.
    Zubcoff, J., Pardillo, J., Trujillo, J.: A UML profile for the conceptual modelling of data-mining with time-series in data warehouses. Information and Software Technology 51(6), 977–992 (2008)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Laurynas Siksnys
    • 1
  • Christian Thomsen
    • 1
  • Torben Bach Pedersen
    • 1
  1. 1.Department of Computer ScienceAalborg UniversityDenmark

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