Skip to main content

Effects of Constraints in Residential Demand-Side-Management Algorithms—A Simulation-Based Study

Part of the Operations Research Proceedings book series (ORP)

Abstract

Due to various challenges such as climatic changes or implementation of renewable energy generation, improvements in regulating energy grids are required. Demand-Side-Management (DSM) contributes to this progress by managing, shifting and controlling loads. However, many DSM algorithms make assumptions regarding load characteristics which do not consider real world conditions. Prior studies find a total of five constraints but so far no investigation shows the effects of these constraints on DSM algorithms. Hence, this research analyses the effects of several constraints of DSM algorithms by conducting a simulation. As a result, we can conclude that the constraints have an effect on the results. For example, the savings dropped about 7% when considering multiple constraints. The handling and the outcomes depend on several factors and might vary. As a logical conclusion, we postulate that these constraints should be considered in DSM algorithms.

Keywords

  • Demand-Side-Management(-Algorithms)
  • Constraints
  • Residential Context
  • Simulation

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-319-89920-6_35
  • Chapter length: 7 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   169.00
Price excludes VAT (USA)
  • ISBN: 978-3-319-89920-6
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   219.99
Price excludes VAT (USA)
Fig. 1
Fig. 2

References

  1. Al-Sumaiti, A. S., Ahmed, M. H., & Salama, M. M. A. (2014). Smart home activities: A literature review. Electric Power Components and Systems, 42(3–4), 294–305.

    CrossRef  Google Scholar 

  2. Balijepalli, V. M., Pradhan, V., Khaparde, S., & Shereef, R. (2011). Review of demand response under smart grid paradigm. Innovative Smart Grid Technologies.

    Google Scholar 

  3. Barbato, A., & Capone, A. (2014). Optimization models and methods for demand-side management of residential users: A survey. Energies, 7(9), 5787–5824.

    CrossRef  Google Scholar 

  4. Behrens, D., Gerwig, C., Knackstedt, R., & Lessing, H. (2014). Selbstregulierende Verbraucher im smart grid: Design einere Infrastruktur mit Hilfe eines Multi-Agenten-Systems. Proceedings of the Multikonferenz Wirtschaftsinformatik 2014.

    Google Scholar 

  5. Behrens, D., Schoormann, T., & Knackstedt, R. (2016). In Heinrich, C. & Pinzger, M. (Eds.), Datensets für Demand-Side-Management Literatur-Review-Basierte Analyse und Forschungsagenda., Lecture notes in informatics.

    Google Scholar 

  6. Behrens, D., Schoormann, T., & Knackstedt, R. (2017). Towards a taxonomy of constraints in demand-side-management-methods for a resedential context. Lecture Notes in Business Information Processing (LNBIP), 288, 283–295.

    CrossRef  Google Scholar 

  7. Feuerriegel, S., Bodenbenner, P., & Neumann, D. (2016). Value and granularity of ICT and smart meter data in demand response systems. Energy Economics, 54, 1–10.

    CrossRef  Google Scholar 

  8. Gellings, C. W., & Chamberlin, J. H. (1993). Demand-Side Management: Concepts and Methods (2nd ed.). GA: Prentice Hall.

    Google Scholar 

  9. Schoormann, T., Behrens, D., Kolek, E., & Knackstedt, R. (2016). Sustainability in business models - a literature-review-based design-science-oriented research agenda. Proceedings of the European Conference on Information Systems.

    Google Scholar 

  10. Sianaki, O. A., Hussain, O., & Tabesh, A. R. (2010). A knapsack problem approach for achieving efficient energy consumption in smart grid for endusers’ life style. 2010 IEEE Conference on Innovative Technologies for an Efficient and Reliable Electricity Supply (pp. 159–164).

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Dennis Behrens .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this paper

Verify currency and authenticity via CrossMark

Cite this paper

Behrens, D., Rüther, C., Schoormann, T., Hachmeister, T., Ambrosi, K., Knackstedt, R. (2018). Effects of Constraints in Residential Demand-Side-Management Algorithms—A Simulation-Based Study. In: Kliewer, N., Ehmke, J., Borndörfer, R. (eds) Operations Research Proceedings 2017. Operations Research Proceedings. Springer, Cham. https://doi.org/10.1007/978-3-319-89920-6_35

Download citation