Skip to main content
SpringerLink
Log in

Agent-Based Modelling of Cost Efficient and Stable Transmission Grid Expansion Planning

  • Conference paper
  • First Online:
Highlights of Practical Applications of Scalable Multi-Agent Systems. The PAAMS Collection (PAAMS 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 616))

  • 769 Accesses

Abstract

Due to politically defined goals to raise the share of renewable energy, the landscape of electricity production has changed in recent years. Normally, a decision to invest in new generation capacity by generation companies is often based on profit maximization criteria. Criteria considering the costs resulting from the required expansion or construction of new transmission capacity are only playing a minor role, if any. This paper introduces an integrated model based on a multi-agent system to simulate the investment and decision behavior of the relevant entities in the liberalized energy market and their impact on social welfare. The interaction between the modelled market entities is based on a non-cooperative game theoretic approach. Its functionality is demonstrated within a small application example.

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

Access this chapter

Log in via an institution
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 EPUB and 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

Notes

  1. 1.

    The formula is based on [16].

References

  1. Botterud, A., Mahalik, M.R., Veselka, T.D., Heon-Su, R., Ki-Won, S.: Multi-agent simulation of generation expansion in electricity markets. In: Power Engineering Society General Meeting 2007, pp. 1–8. IEEE (2007)

    Google Scholar 

  2. Kays, J.: Agent-based simulation environment for improving the planning of distribution grids. Sierke Verlag, Göttingen (2014)

    Google Scholar 

  3. Kays, J., Seack, A., Rehtanz, C.: Agent-based modelling of regenerative energy sources for an efficient distribution power system design. In: Cigré Bologna 2011, pp. 1–9 (2011)

    Google Scholar 

  4. Wu, F.F., Zheng, F.L., Wen, F.S.: Transmission investment and expansion planning in a restructured electricity market. Energy 31(6–7), 954–966 (2006)

    Article  Google Scholar 

  5. Sauma, E.E., Oren, S.S.: Proactive planning and valuation of transmission investments in restructured electricity markets. J. Regul. Econ. 30(3), 261–290 (2006)

    Article  Google Scholar 

  6. Sauma, E.E., Oren, S.S.: Economic criteria for planning transmission investment in restructured electricity markets. IEEE Trans. Power Syst. 22(4), 1394–1405 (2007)

    Article  Google Scholar 

  7. Pozo, D., Contreras, J., Sauma, E.: If you build it, he will come: anticipative power transmission planning. Energy Econ. 36, 135–146 (2013)

    Article  Google Scholar 

  8. Motamedi, A., Zareipour, H., Buygi, M.O., Rosehart, W.D.: A transmission planning framework considering future generation expansions in electricity markets. IEEE Trans. Power Syst. 25(4), 1987–1995 (2010)

    Article  Google Scholar 

  9. Yen, J., Yan, Y., Contreras, J., Ma, P.-C., Wu, F.F.: Multi-agent approach to the planning of power transmission expansion. Decis. Support Syst. 28, 279–290 (2000)

    Article  Google Scholar 

  10. German Energy Agency (dena): dena Grid Study II - Integration of Renewable Energy Sources in the German Power Supply System from 2015–2020 with an Outlook to 2025. Berlin (2010)

    Google Scholar 

  11. Java Agent Development Framework (JADE) (2015). http://jade.tilab.com/, Accessed 05 Nov 2015

  12. Sun, J., Tesfatsion, L.: DC optimal power flow formulation and solution using QuadProgJ. In: ISU Economics of Education Working Paper No. 06014, pp. 1–62, 1 March 2010 (2010)

    Google Scholar 

  13. Tesfatsion, L.: DCOPFJ Package: A Java DC-OPF Solver (Leigh Tesfatsion) (2015). http://www2.econ.iastate.edu/tesfatsi/DCOPFJHome.htm, Accessed 05 Nov 2015

  14. Sun, J., Tesfatsion, L.: DC-OPF Formulation with Price-Sensitive Demand Bids (2008)

    Google Scholar 

  15. Kirschen, D., Strbac, G.: Fundamentals of Power System Economics. Wiley, Chichester (2004)

    Book  Google Scholar 

  16. Swami, R.: Social welfare maximization in deregulated power system. Int. J. Power Syst. Oper. Energy Manage. 1(4), 4–8 (2012)

    MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Energy Systems, Energy Efficiency and Energy Economics (ie3), Technical University Dortmund, Dortmund, Germany

    Johannes Hiry, Jonas von Haebler, Ulf Häger & Christian Rehtanz

  2. Grupo de Investigación en Sistemas Energéticos (GISE), Universidad Nacional de Asunción, Asunción, Paraguay

    Gerardo Blanco & Aldo Martinez

Authors
  1. Johannes Hiry
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jonas von Haebler
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ulf Häger
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Christian Rehtanz
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Gerardo Blanco
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Aldo Martinez
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Johannes Hiry .

Editor information

Editors and Affiliations

  1. Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, Madrid, Spain

    Javier Bajo

  2. Universidad de Sevilla, Sevilla, Spain

    María José Escalona

  3. Faculté des Sciences, Université de Sherbrooke, Sherbrooke, Canada

    Sylvain Giroux

  4. University of Poznan, Poznan, Poland

    Patrycja Hoffa-Dąbrowska

  5. Universidad Politécnica de Valencia, Valencia, Spain

    Vicente Julián

  6. Department of Informatics, Universidade do Minho, Braga, Portugal

    Paulo Novais

  7. Fluminense Federal University, Rio de Janeiro, Brazil

    Nayat Sánchez-Pi

  8. Inst. Comp. Sci. & Bus. Info. Sys. (ICB), University of Duisburg-Essen, Essen, Nordrhein-Westfalen, Germany

    Rainer Unland

  9. Departamento de Informática e Estatístic, Universidade Federal de Santa Catarina, Florianópolis S.C.,, Brazil

    Ricardo Azambuja-Silveira

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Hiry, J., von Haebler, J., Häger, U., Rehtanz, C., Blanco, G., Martinez, A. (2016). Agent-Based Modelling of Cost Efficient and Stable Transmission Grid Expansion Planning. In: Bajo, J., et al. Highlights of Practical Applications of Scalable Multi-Agent Systems. The PAAMS Collection. PAAMS 2016. Communications in Computer and Information Science, vol 616. Springer, Cham. https://doi.org/10.1007/978-3-319-39387-2_30

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-39387-2_30

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-39386-5

  • Online ISBN: 978-3-319-39387-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation