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Modeling and analysis of a decentralized electricity market: An integrated simulation/optimization approach

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  • Sarıca, Kemal
  • Kumbaroğlu, Gürkan
  • Or, Ilhan

Abstract

In this study, a model is developed to investigate the implications of an hourly day-ahead competitive power market on generator profits, electricity prices, availability and supply security. An integrated simulation/optimization approach is employed integrating a multi-agent simulation model with two alternative optimization models. The simulation model represents interactions between power generator, system operator, power user and power transmitter agents while the network flow optimization model oversees and optimizes the electricity flows, dispatches generators based on two alternative approaches used in the modeling of the underlying transmission network: a linear minimum cost network flow model and a non-linear alternating current optimal power flow model. Supply, demand, transmission, capacity and other technological constraints are thereby enforced.

Suggested Citation

  • Sarıca, Kemal & Kumbaroğlu, Gürkan & Or, Ilhan, 2012. "Modeling and analysis of a decentralized electricity market: An integrated simulation/optimization approach," Energy, Elsevier, vol. 44(1), pages 830-852.
  • Handle: RePEc:eee:energy:v:44:y:2012:i:1:p:830-852
    DOI: 10.1016/j.energy.2012.05.009
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    1. Woo, Chi-Keung & Lloyd, Debra & Tishler, Asher, 2003. "Electricity market reform failures: UK, Norway, Alberta and California," Energy Policy, Elsevier, vol. 31(11), pages 1103-1115, September.
    2. Derek Bunn & Fernando Oliveira, 2003. "Evaluating Individual Market Power in Electricity Markets via Agent-Based Simulation," Annals of Operations Research, Springer, vol. 121(1), pages 57-77, July.
    3. James Nicolaisen & Valentin Petrov & Leigh Tesfatsion, 2000. "Market Power and Efficiency in a Computational Electricity Market with Discriminatory Double-Auction Pricing," Computational Economics 0004005, University Library of Munich, Germany.
    4. Al-Sunaidy, A. & Green, R., 2006. "Electricity deregulation in OECD (Organization for Economic Cooperation and Development) countries," Energy, Elsevier, vol. 31(6), pages 769-787.
    5. Alvaro Cartea & Marcelo Figueroa, 2005. "Pricing in Electricity Markets: A Mean Reverting Jump Diffusion Model with Seasonality," Applied Mathematical Finance, Taylor & Francis Journals, vol. 12(4), pages 313-335.
    6. von der Fehr, Nils-Henrik Morch & Harbord, David, 1993. "Spot Market Competition in the UK Electricity Industry," Economic Journal, Royal Economic Society, vol. 103(418), pages 531-546, May.
    7. Timothy N. Cason & Daniel Friedman, 1997. "Price Formation in Single Call Markets," Econometrica, Econometric Society, vol. 65(2), pages 311-346, March.
    8. Rajnish Kamat & Shmuel S. Oren, 2002. "Exotic Options for Interruptible Electricity Supply Contracts," Operations Research, INFORMS, vol. 50(5), pages 835-850, October.
    9. Huisman, Ronald & Mahieu, Ronald, 2003. "Regime jumps in electricity prices," Energy Economics, Elsevier, vol. 25(5), pages 425-434, September.
    10. Li, Gong & Shi, Jing & Qu, Xiuli, 2011. "Modeling methods for GenCo bidding strategy optimization in the liberalized electricity spot market–A state-of-the-art review," Energy, Elsevier, vol. 36(8), pages 4686-4700.
    11. Bunn, Derek W. & Martoccia, Maria, 2005. "Unilateral and collusive market power in the electricity pool of England and Wales," Energy Economics, Elsevier, vol. 27(2), pages 305-315, March.
    12. Guerci, E. & Ivaldi, S. & Pastore, S. & Cincotti, S., 2005. "Modeling and implementation of an artificial electricity market using agent-based technology," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(1), pages 69-76.
    13. Ventosa, Mariano & Baillo, Alvaro & Ramos, Andres & Rivier, Michel, 2005. "Electricity market modeling trends," Energy Policy, Elsevier, vol. 33(7), pages 897-913, May.
    14. Weidlich, Anke & Veit, Daniel, 2008. "A critical survey of agent-based wholesale electricity market models," Energy Economics, Elsevier, vol. 30(4), pages 1728-1759, July.
    15. Bower, John & Bunn, Derek, 2001. "Experimental analysis of the efficiency of uniform-price versus discriminatory auctions in the England and Wales electricity market," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 561-592, March.
    16. Derek W. Bunn and Fernando Oliveira, 2001. "An Application of Agent-based Simulation to the New Electricity Trading Arrangements of England and Wales," Computing in Economics and Finance 2001 93, Society for Computational Economics.
    17. Azadeh, A. & Skandari, M.R. & Maleki-Shoja, B., 2010. "An integrated ant colony optimization approach to compare strategies of clearing market in electricity markets: Agent-based simulation," Energy Policy, Elsevier, vol. 38(10), pages 6307-6319, October.
    18. John Bower & Derek W. Bunn, 2000. "Model-Based Comparisons of Pool and Bilateral Markets for Electricity," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 1-29.
    19. Dyner, Isaac & Larsen, Erik R., 2001. "From planning to strategy in the electricity industry," Energy Policy, Elsevier, vol. 29(13), pages 1145-1154, November.
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    6. Yao Liu & Jianmai Shi & Zhong Liu & Jincai Huang & Tianren Zhou, 2019. "Two-Layer Routing for High-Voltage Powerline Inspection by Cooperated Ground Vehicle and Drone," Energies, MDPI, vol. 12(7), pages 1-20, April.
    7. Zakeri, Behnam & Virasjoki, Vilma & Syri, Sanna & Connolly, David & Mathiesen, Brian V. & Welsch, Manuel, 2016. "Impact of Germany's energy transition on the Nordic power market – A market-based multi-region energy system model," Energy, Elsevier, vol. 115(P3), pages 1640-1662.
    8. Min, C.G. & Kim, M.K. & Park, J.K. & Yoon, Y.T., 2013. "Game-theory-based generation maintenance scheduling in electricity markets," Energy, Elsevier, vol. 55(C), pages 310-318.

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