IDEAS home Printed from https://ideas.repec.org/a/spr/binfse/v6y2014i1p25-31.html
   My bibliography  Save this article

Energy Informatics

Author

Listed:
  • Christoph Goebel
  • Hans-Arno Jacobsen
  • Victor Razo
  • Christoph Doblander
  • Jose Rivera
  • Jens Ilg
  • Christoph Flath
  • Hartmut Schmeck
  • Christof Weinhardt
  • Daniel Pathmaperuma
  • Hans-Jürgen Appelrath
  • Michael Sonnenschein
  • Sebastian Lehnhoff
  • Oliver Kramer
  • Thorsten Staake
  • Elgar Fleisch
  • Dirk Neumann
  • Jens Strüker
  • Koray Erek
  • Rüdiger Zarnekow
  • Holger Ziekow
  • Jörg Lässig

Abstract

Due to the increasing importance of producing and consuming energy more sustainably, Energy Informatics (EI) has evolved into a thriving research area within the CS/IS community. The article attempts to characterize this young and dynamic field of research by describing current EI research topics and methods and provides an outlook of how the field might evolve in the future. It is shown that two general research questions have received the most attention so far and are likely to dominate the EI research agenda in the coming years: How to leverage information and communication technology (ICT) to (1) improve energy efficiency, and (2) to integrate decentralized renewable energy sources into the power grid. Selected EI streams are reviewed, highlighting how the respective research questions are broken down into specific research projects and how EI researchers have made contributions based on their individual academic background. Copyright Springer Fachmedien Wiesbaden 2014

Suggested Citation

  • Christoph Goebel & Hans-Arno Jacobsen & Victor Razo & Christoph Doblander & Jose Rivera & Jens Ilg & Christoph Flath & Hartmut Schmeck & Christof Weinhardt & Daniel Pathmaperuma & Hans-Jürgen Appelrat, 2014. "Energy Informatics," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 6(1), pages 25-31, February.
    • Handle: RePEc:spr:binfse:v:6:y:2014:i:1:p:25-31
    DOI: 10.1007/s12599-013-0304-2
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s12599-013-0304-2
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s12599-013-0304-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Hans-Jürgen Appelrath & Orestis Terzidis & Christof Weinhardt, 2012. "Internet of Energy," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 4(1), pages 1-2, February.
    2. Gottwalt, Sebastian & Ketter, Wolfgang & Block, Carsten & Collins, John & Weinhardt, Christof, 2011. "Demand side management—A simulation of household behavior under variable prices," Energy Policy, Elsevier, vol. 39(12), pages 8163-8174.
    3. Bodenstein, Christian & Schryen, Guido & Neumann, Dirk, 2012. "Energy-aware workload management models for operation cost reduction in data centers," European Journal of Operational Research, Elsevier, vol. 222(1), pages 157-167.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Feuerriegel, Stefan & Bodenbenner, Philipp & Neumann, Dirk, 2016. "Value and granularity of ICT and smart meter data in demand response systems," Energy Economics, Elsevier, vol. 54(C), pages 1-10.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Feuerriegel, Stefan & Neumann, Dirk, 2014. "Measuring the financial impact of demand response for electricity retailers," Energy Policy, Elsevier, vol. 65(C), pages 359-368.
    2. Y, Kiguchi & Y, Heo & M, Weeks & R, Choudhary, 2019. "Predicting intra-day load profiles under time-of-use tariffs using smart meter data," Energy, Elsevier, vol. 173(C), pages 959-970.
    3. Fridgen, Gilbert & Kahlen, Micha & Ketter, Wolfgang & Rieger, Alexander & Thimmel, Markus, 2018. "One rate does not fit all: An empirical analysis of electricity tariffs for residential microgrids," Applied Energy, Elsevier, vol. 210(C), pages 800-814.
    4. Freier, Julia & von Loessl, Victor, 2022. "Dynamic electricity tariffs: Designing reasonable pricing schemes for private households," Energy Economics, Elsevier, vol. 112(C).
    5. Gilbraith, Nathaniel & Powers, Susan E., 2013. "Residential demand response reduces air pollutant emissions on peak electricity demand days in New York City," Energy Policy, Elsevier, vol. 59(C), pages 459-469.
    6. Shinichi Taniguchi, 2020. "Examining the causality structures of electricity interchange and variable renewable energy: a comparison between Japan and Denmark," Asia-Pacific Journal of Regional Science, Springer, vol. 4(1), pages 159-191, February.
    7. Chen Wang & Kaile Zhou & Lanlan Li & Shanlin Yang, 2018. "Multi-agent simulation-based residential electricity pricing schemes design and user selection decision-making," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 90(3), pages 1309-1327, February.
    8. Andruszkiewicz, Jerzy & Lorenc, Józef & Weychan, Agnieszka, 2020. "Seasonal variability of price elasticity of demand of households using zonal tariffs and its impact on hourly load of the power system," Energy, Elsevier, vol. 196(C).
    9. Ensslen, Axel & Ringler, Philipp & Dörr, Lasse & Jochem, Patrick & Zimmermann, Florian & Fichtner, Wolf, 2018. "Incentivizing smart charging: Modeling charging tariffs for electric vehicles in German and French electricity markets," MPRA Paper 91543, University Library of Munich, Germany, revised 17 Feb 2018.
    10. Wang, Yong & Li, Lin, 2015. "Time-of-use electricity pricing for industrial customers: A survey of U.S. utilities," Applied Energy, Elsevier, vol. 149(C), pages 89-103.
    11. Mauser, Ingo & Müller, Jan & Allerding, Florian & Schmeck, Hartmut, 2016. "Adaptive building energy management with multiple commodities and flexible evolutionary optimization," Renewable Energy, Elsevier, vol. 87(P2), pages 911-921.
    12. Chattopadhyay, Kabitri & Kies, Alexander & Lorenz, Elke & von Bremen, Lüder & Heinemann, Detlev, 2017. "The impact of different PV module configurations on storage and additional balancing needs for a fully renewable European power system," Renewable Energy, Elsevier, vol. 113(C), pages 176-189.
    13. Woo, C.K. & Sreedharan, P. & Hargreaves, J. & Kahrl, F. & Wang, J. & Horowitz, I., 2014. "A review of electricity product differentiation," Applied Energy, Elsevier, vol. 114(C), pages 262-272.
    14. Lucas Roth & Jens Lowitzsch & Özgür Yildiz, 2021. "An Empirical Study of How Household Energy Consumption Is Affected by Co-Owning Different Technological Means to Produce Renewable Energy and the Production Purpose," Energies, MDPI, vol. 14(13), pages 1-38, July.
    15. Martínez Ceseña, Eduardo A. & Good, Nicholas & Mancarella, Pierluigi, 2015. "Electrical network capacity support from demand side response: Techno-economic assessment of potential business cases for small commercial and residential end-users," Energy Policy, Elsevier, vol. 82(C), pages 222-232.
    16. Torriti, Jacopo, 2012. "Demand Side Management for the European Supergrid: Occupancy variances of European single-person households," Energy Policy, Elsevier, vol. 44(C), pages 199-206.
    17. Venizelou, Venizelos & Philippou, Nikolas & Hadjipanayi, Maria & Makrides, George & Efthymiou, Venizelos & Georghiou, George E., 2018. "Development of a novel time-of-use tariff algorithm for residential prosumer price-based demand side management," Energy, Elsevier, vol. 142(C), pages 633-646.
    18. El-Baz, Wessam & Tzscheutschler, Peter, 2015. "Short-term smart learning electrical load prediction algorithm for home energy management systems," Applied Energy, Elsevier, vol. 147(C), pages 10-19.
    19. Ketter, W. & Collins, J. & de Weerdt, M.M., 2016. "The 2016 Power Trading Agent Competition," ERIM Report Series Research in Management ERS-2016-002-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    20. Stoll, Pia & Brandt, Nils & Nordström, Lars, 2014. "Including dynamic CO2 intensity with demand response," Energy Policy, Elsevier, vol. 65(C), pages 490-500.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:binfse:v:6:y:2014:i:1:p:25-31. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.