Nothing Special   »   [go: up one dir, main page]

Skip to main content

Towards an Energy Internet: A Game-Theoretic Approach to Price-Directed Energy Utilization

  • Conference paper
Energy-Efficient Computing and Networking (E-Energy 2010)

Abstract

The growing interest towards internet-inspired research for power transmission and distribution invariably encounters the barrier of energy storage. Limitations of energy storage can be offset, to a degree, by reliable forecasting of granular demand leading to judicious scheduling involved and incentivized by appropriate pricing signals. The anticipation of energy demand and future system state is of great benefit in scheduling capacities offsetting storage limitations. In this paper, a game is formulated that shows the effect of the synergy between anticipation and price elasticity to achieve lower Peak-to-Average Ratios and minimize waste of energy. The results demonstrate that the final demand signal can be smoother and energy efficiency increased.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Moslehi, K., Kumar, R.B.A., Shurtleff, D., Laufenberg, M., Bose, A., Hirsch, P.: Framework for a Self-Healing Power Grid. In: IEEE Power Engineering Society General Meeting, pp. 3027–3034. IEEE Press, New York (2005)

    Google Scholar 

  2. Mamlook, R., Badran, O., Abdulhadi, E.: A fuzzy inference model for short-term load forecasting. Energy Policy 37, 1239–1248 (2009)

    Article  Google Scholar 

  3. Yalcinoz, T., Eminoglu, U.: Short term and medium term power distribution load forecasting by neural networks. Energy Convers. and Manag. 46, 1393–1405 (2005)

    Article  Google Scholar 

  4. Gabriel, M., Gunville, M.: The Digital Landscape: Energy moves to the Internet, Instrumentation. Control and Autom. in the Power Ind. 45, 3–9 (2004)

    Google Scholar 

  5. Mohagheghi, S., Harley, R., Venayagamoorthy, G.: Making the power grid more intelligent. In: 2007 iRep. Symposium, pp. 1–10. IEEE, Piscataway (2007)

    Google Scholar 

  6. Jiang, Z.: Computational Intelligence Techniques for a Smart Electric grid of the Future. In: Yu, W., He, H., Zhang, N. (eds.) ISNN 2009. LNCS, vol. 5551, pp. 1191–1201. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  7. Tsoukalas, L.H., Gao, R.: Inventing an Energy Internet: The Role of Anticipation in Human-Centered Energy Distribution and Utilization. In: SICE Annual Conference, pp. 399–403. Society of Instrument and Control Engineers, Tokyo (2008)

    Google Scholar 

  8. Gao, R., Tsoukalas, L.H.: Implementing Virtual Buffer for Electric Power Grids. In: Shi, Y., van Albada, G.D., Dongarra, J., Sloot, P.M.A., et al. (eds.) ICCS 2007. LNCS, vol. 4487, pp. 1083–1089. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  9. Consortium for Intelligent Management of Electric Power Grid (CIMEG), http://www.cimeg.com

  10. Tsoukalas, L.H., Gao, R.: From Smart Grids to an Energy Internet: Assumptions, Architectures and Requirements. In: DRPT 2008, pp. 94–98. IEEE, Piscataway (2008)

    Google Scholar 

  11. Thaler, M., Grabec, I., Poredos, A.: Prediction of Energy Consumption and Risk of excess Demand in a Distribution System. Phys. A: Stat. Mech. and its Appl. 355, 46–53 (2005)

    Article  MathSciNet  Google Scholar 

  12. Skoulidas, C., Vournas, C., Papavasilopoulos, G.: Adaptive Game Modeling of Deregulated Power Markets. IEEE Power Eng. Review, 42–45 (2002)

    Google Scholar 

  13. Skoulidas, C., Vournas, C., Papavasilopoulos, G.: An Adaptive Game for Pay-as-Bid and Uniform Pricing Power Pools Comparison. In: 3rd MedPower Conference, pp. 1–6. National Technical University of Athens, Athens (2002)

    Google Scholar 

  14. Lijesen, M.G.: The real-time price elasticity of electricity. Energy Econ. 29, 249–258 (2007)

    Article  Google Scholar 

  15. ISO New England, http://www.iso-ne.com

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering

About this paper

Cite this paper

Alamaniotis, M., Gao, R., Tsoukalas, L.H. (2011). Towards an Energy Internet: A Game-Theoretic Approach to Price-Directed Energy Utilization. In: Hatziargyriou, N., Dimeas, A., Tomtsi, T., Weidlich, A. (eds) Energy-Efficient Computing and Networking. E-Energy 2010. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 54. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19322-4_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-19322-4_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19321-7

  • Online ISBN: 978-3-642-19322-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics