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Towards an Integrated Development and Sustainability Evaluation of Energy Scenarios Assisted by Automated Information Exchange

  • Jan Sören Schwarz
  • Tobias Witt
  • Astrid Nieße
  • Jutta Geldermann
  • Sebastian LehnhoffEmail author
  • Michael Sonnenschein
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 921)

Abstract

Today, decision making in politics and businesses should aim for sustainable development, and one field of action is the transformation of energy systems. To reshape energy systems towards renewable energy resources, it has to be decided today on how to accomplish the transition. Energy scenarios are widely used to guide decision making in this context. While considerable effort has been put into developing energy scenarios, researchers have pointed out three requirements for energy scenarios that are not fulfilled satisfactorily yet: The development and evaluation of energy scenarios should (1) incorporate the concept of sustainability, (2) provide decision support in a transparent way, and (3) be replicable for other researchers. To meet these requirements, we combine different methodological approaches: story-and-simulation (SAS) scenarios, multi-criteria decision making (MCDM), information modeling, and co-simulation. We show how the combination of these methods can lead to an integrated approach for development and sustainability evaluation of energy scenarios assisted by automated information exchange. We concretize this approach with a sustainability evaluation process (SEP) model and an information model. We highlight, which artifacts are developed during the SEP and how the information model can help to automate the information exchange in this process. The objectives are to facilitate a sustainable development of the energy sector and to make the development and decision support processes of energy scenarios more transparent.

Keywords

Co-simulation Energy scenarios Information model Multi-criteria decision making (MCDM) Ontology Scenario planning Story-and-simulation (SAS) Sustainability evaluation 

Notes

Acknowledgements

The research project ‘NEDS – Nachhaltige Energieversorgung Niedersachsen’ acknowledges the support of the Lower Saxony Ministry of Science and Culture through the ‘Niedersächsisches Vorab’ grant program (grant ZN3043).

References

  1. 1.
    Alcamo, J.: The SAS approach: combining qualitative and quantitative knowledge in environmental scenarios. In: Alcamo, J. (ed.) Environmental Futures: The Practice of Environmental Scenario Analysis, Developments in Integrated Environmental Assessment, vol. 2, pp. 123–150. Elsevier, Amsterdam and Boston (2008).  https://doi.org/10.1016/S1574-101X(08)00406-7CrossRefGoogle Scholar
  2. 2.
    Bastian, J., Clauß, C., Wolf, S., Schneider, P.: Master for co-simulation using FMI. In: Proceedings of the 8th International Modelica Conference, pp. 115–120 (2011).  https://doi.org/10.3384/ecp11063115
  3. 3.
    Belton, V., Stewart, T.J.: Multiple Criteria Decision Analysis: An Integrated Approach, 2nd edn. Kluwer Academic Publishers, Boston (2003)Google Scholar
  4. 4.
    Blank, M., et al.: Process for simulation-based sustainability evaluation of smart grid future scenarios, version 1.0 (2016). http://neds-niedersachsen.de/uploads/tx_tkpublikationen/Whitepaper-SEP-V1.pdf. Accessed 17 Aug 2017
  5. 5.
    BMWi: Federal Ministry of Economics and Technology. Energiekonzept für eine umweltschonende, zuverlässige und bezahlbare Energieversorgung (2010). https://www.bmwi.de/Redaktion/DE/Downloads/E/energiekonzept-2010.pdf. Accessed 17 Aug 2017. (in German)
  6. 6.
    Brans, J.P., Vincke, P.: Note–a preference ranking organisation method: (the PROMETHEE method for multiple criteria decision-making). Manag. Sci. 31(6), 647–656 (1985).  https://doi.org/10.1287/mnsc.31.6.647CrossRefzbMATHGoogle Scholar
  7. 7.
    Brundtland, G.H.: Our Common Future. Oxford Paperbacks. Oxford University Press, Oxford (1987)Google Scholar
  8. 8.
    Castro, A.G., et al.: The use of concept maps during knowledge elicitation in ontology development processes-the nutrigenomics use case. BMC Bioinform. 7, 267 (2006).  https://doi.org/10.1186/1471-2105-7-267CrossRefGoogle Scholar
  9. 9.
    Daraio, C., Lenzerini, M., Leporelli, C., Naggar, P., Bonaccorsi, A., Bartolucci, A.: The advantages of an Ontology-Based Data Management approach: openness, interoperability and data quality. Scientometrics 108(1), 441–455 (2016).  https://doi.org/10.1007/s11192-016-1913-6CrossRefGoogle Scholar
  10. 10.
    Deutscher Bundestag: German Bundestag. Gesetz über die Elektrizitäts- und Gasverordnung (Energiewirtschaftsgesetz): EnWG (2005). http://www.gesetze-im-internet.de/enwg_2005/BJNR197010005.html. Accessed 17 Aug 2017. (in German)
  11. 11.
    Elkington, J.: Cannibals with Forks: The Triple Bottom Line of 21st Century Business. Capstone, Oxford (2002). Reprint ednGoogle Scholar
  12. 12.
    European Commission: Communication from the European Commission: A policy framework for climate and energy in the period from 2020 to 2030 (2014). http://eur-lex.europa.eu/legal-content/EN/ALL/?uri=CELEX:52014DC0015. Accessed 17 Aug 2017
  13. 13.
    Fensel, D.: Ontologies: A Silver Bullet for Knowledge Management and Electronic-Commerce. Springer, Berlin (2004).  https://doi.org/10.1007/978-3-662-09083-1CrossRefzbMATHGoogle Scholar
  14. 14.
    Gausemeier, J., Fink, A., Schlake, O.: Scenario management: an approach to develop future potentials. Technol. Forecast. Soc. Change 59, 111–130 (1998).  https://doi.org/10.1016/S0040-1625(97)00166-2CrossRefGoogle Scholar
  15. 15.
    Grunwald, A., Dieckhoff, C., Fischedick, M., Höffler, F., Mayer, C., Weimer-Jehle, W.: Consulting with energy scenarios: requirements for scientific policy advice. In: acatech/Leopoldina/Akademienunion (eds.) Series on Science-Based Policy Advice (2016)Google Scholar
  16. 16.
    Hughes, N., Strachan, N.: Methodological review of UK and international low carbon scenarios. Energy Policy 38(10), 6056–6065 (2010).  https://doi.org/10.1016/j.enpol.2010.05.061CrossRefGoogle Scholar
  17. 17.
    International Energy Agency (IEA): World Energy Outlook 2016: Executive Summary (2016)Google Scholar
  18. 18.
    Keles, D., Möst, D., Fichtner, W.: The development of the German energy market until 2030—A critical survey of selected scenarios. Energy Policy 39(2), 812–825 (2011).  https://doi.org/10.1016/j.enpol.2010.10.055CrossRefGoogle Scholar
  19. 19.
    Kontchakov, R., Rodríguez-Muro, M., Zakharyaschev, M.: Ontology-based data access with databases: a short course. In: Rudolph, S., Gottlob, G., Horrocks, I., van Harmelen, F. (eds.) Reasoning Web 2013. LNCS, vol. 8067, pp. 194–229. Springer, Heidelberg (2013).  https://doi.org/10.1007/978-3-642-39784-4_5CrossRefGoogle Scholar
  20. 20.
    Kowalski, K., Stagl, S., Madlener, R., Omann, I.: Sustainable energy futures: methodological challenges in combining scenarios and participatory multi-criteria analysis. Eur. J. Oper. Res. 197(3), 1063–1074 (2009).  https://doi.org/10.1016/j.ejor.2007.12.049CrossRefGoogle Scholar
  21. 21.
    Kronenberg, T., et al.: Energieszenarien für Deutschland: Stand der Literatur und methodische Auswertung. In: Bruhns, H. (ed.) Energiewende - Aspekte, Optionen, Herausforderungen, pp. 132–168. Deutsche Physikalische Gesellschaft - Arbeitskreis Energie, Berlin (2012). (in German)Google Scholar
  22. 22.
    Lee, Y.T.: Information modeling: from design to implementation. In: Proceedings of the Second World Manufacturing Congress, pp. 315–321 (1999)Google Scholar
  23. 23.
    Lehnhoff, S., et al.: Exchangeability of power flow simulators in smart grid co-simulations with mosaik. In: 2015 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, MSCPES, pp. 1–6, April 2015.  https://doi.org/10.1109/MSCPES.2015.7115410
  24. 24.
    Oberschmidt, J., Geldermann, J., Ludwig, J., Schmehl, M.: Modified PROMETHEE approach for assessing energy technologies. Int. J. Energy Sect. Manag. 4(2), 183–212 (2010).  https://doi.org/10.1108/17506221011058696CrossRefGoogle Scholar
  25. 25.
    Rehtanz, C., Guillaud, X.: Real-time and co-simulations for the development of power system monitoring, control and protection. In: 2016 Power Systems Computation Conference, PSCC, pp. 1–20, June 2016.  https://doi.org/10.1109/PSCC.2016.7541030
  26. 26.
    Robinson, S.: Simulation: The Practice of Model Development and Use. Wiley, Hoboken (2004)Google Scholar
  27. 27.
    Schlögl, F., Rohjans, S., Lehnhoff, S., Velasquez, J., Steinbrink, C., Palensky, P.: Towards a classification scheme for co-simulation approaches in energy systems. In: International Symposium on Smart Electric Distribution Systems and Technologies, pp. 2–7. IEEE/IES (2015).  https://doi.org/10.1109/SEDST.2015.7315262
  28. 28.
    Schwarz, J.S., Witt, T., Nieße, A., Geldermann, J., Lehnhoff, S., Sonnenschein, M.: Towards an integrated sustainability evaluation of energy scenarios with automated information exchange. In: Proceedings of the 6th International Conference on Smart Cities and Green ICT Systems, pp. 188–199. ScitePress (2017).  https://doi.org/10.5220/0006302101880199
  29. 29.
    Simon-Cuevas, A., Ceccaroni, L., Rosete-Suarez, A., Suarez-Rodriguez, A.: A formal modeling method applied to environmental-knowledge engineering. In: International Conference on Complex, Intelligent and Software Intensive Systems (2009).  https://doi.org/10.1109/CISIS.2009.55
  30. 30.
    Singh, R.K., Murty, H.R., Gupta, S.K., Dikshit, A.K.: An overview of sustainability assessment methodologies. Ecol. Indic. 15(1), 281–299 (2012)CrossRefGoogle Scholar
  31. 31.
    Steinhilber, S.: Exploring options for the harmonisation of renewable energy support policies in the EU using multi-criteria decision analysis. Dissertation, Karlsruher Institut für Technologie (2015)Google Scholar
  32. 32.
    Stewart, T.J., French, S., Rios, J.: Integrating multicriteria decision analysis and scenario planning - review and extension. Omega 41(4), 679–688 (2013).  https://doi.org/10.1016/j.omega.2012.09.003CrossRefGoogle Scholar
  33. 33.
    Uslar, M., Specht, M., Rohjans, S., Trefke, J., Vasquez González, J.M.: The Common Information Model CIM. Springer, Heidelberg (2012).  https://doi.org/10.1007/978-3-642-25215-0CrossRefGoogle Scholar
  34. 34.
    van der Heijden, K.: Scenarios: The Art of Strategic Conversation. Wiley, Chichester, England and New York (1996)Google Scholar
  35. 35.
    Vysniauskas, E., Nemuraite, L., Paradauskas, B.: Hybrid method for storing and querying ontologies in databases. Elektronika ir Elektrotechnika 115(9), 67–72 (2011).  https://doi.org/10.5755/j01.eee.115.9.752CrossRefGoogle Scholar
  36. 36.
    Wang, J.J., Jing, Y.Y., Zhang, C.F., Zhao, J.H.: Review on multi-criteria decision analysis aid in sustainable energy decision-making. Renew. Sustain. Energy Rev. 13(9), 2263–2278 (2009).  https://doi.org/10.1016/j.rser.2009.06.021CrossRefGoogle Scholar
  37. 37.
    Weimer-Jehle, W., et al.: Context scenarios and their usage for the construction of socio-technical energy scenarios. Energy 111, 956–970 (2016).  https://doi.org/10.1016/j.energy.2016.05.073CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Computing ScienceUniversity of OldenburgOldenburgGermany
  2. 2.Chair of Production and LogisticsUniversity of GoettingenGoettingenGermany
  3. 3.OFFIS - Institute for Information TechnologyOldenburgGermany

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