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Journal of Regulatory Economics

, Volume 50, Issue 3, pp 290–327 | Cite as

Congestion management in power systems

Long-term modeling framework and large-scale application
  • Joachim Bertsch
  • Simeon Hagspiel
  • Lisa Just
Original Article

Abstract

In liberalized power systems, generation and transmission services are unbundled, but remain tightly interlinked. Congestion management in the transmission network is of crucial importance for the efficiency of these inter-linkages. Different regulatory designs have been suggested, analyzed and followed, such as uniform zonal pricing with redispatch or nodal pricing. However, the literature has either focused on the short-term efficiency of congestion management or specific issues of timing investments. In contrast, this paper presents a generalized and flexible economic modeling framework based on a decomposed inter-temporal equilibrium model including generation, transmission, as well as their inter-linkages. The model covers short-run operation and long-run investments and hence, allows to analyze short and long-term efficiency of different congestion management designs that vary with respect to the definition of market areas, the regulation and organization of TSOs, the way of managing congestion besides grid expansion, and the type of cross-border capacity allocation. We are able to identify and isolate implicit frictions and sources of inefficiencies in the different regulatory designs, and to provide a comparative analysis including a benchmark against a first-best welfare-optimal result. To demonstrate the applicability of our framework, we calibrate and numerically solve our model for a detailed representation of the Central Western European (CWE) region, consisting of 70 nodes and 174 power lines. Analyzing six different congestion management designs until 2030, we show that compared to the first-best benchmark, i.e., nodal pricing, inefficiencies of up to 4.6% arise. Inefficiencies are mainly driven by the approach of determining cross-border capacities as well as the coordination of transmission system operators’ activities.

Keywords

Power system economics Unbundling Congestion management Transmission pricing Inter-temporal equilibrium model 

JEL Classification

C61 C63 D47 E61 L50 Q40 

Notes

Acknowledgements

We thank Felix Höffler for helpful comments, as well as Tom Brown and Energynautics for their cooperation to realize the large-scale application. The project was funded by the German Federal Ministry for Economic Affairs and Energy based on ruling of the Deutsche Bundestag. The financial support through Grant No. 03ESP239 is gratefully acknowledged. Furthermore, J. Bertsch and S. Hagspiel acknowledge funding of the German research society DFG through Grant No. HO 5108/2-1. The responsibility for the content of this publication lies solely with the authors.

References

  1. ACER (2014, March). Report on the influence of existing bidding zones on electricity markets.Google Scholar
  2. Ackermann, T., Cherevatskiy, S., Brown, T., Eriksson, R., Samadi, A., Ghandhari, M., Sder, L., Lindenberger, D., Jägemann, C., Hagspiel, S., Cuk, V., Ribeiro, P.F., Cobben, S., Bindner, H., Isleifsson, F.R., & Mihet-Popa L. (2013, May). Smart modeling of optimal integration of high penetration of PV—smooth PV. Final Report.Google Scholar
  3. Andersson, G. (2011). Power system analysis. Zurich: Eidgenössische Technische Hochschule Zurich (ETH).Google Scholar
  4. Baldick, R., & Niu, H. (2005). Lessons learned: The Texas experience. In Griffin, J. M., & Puller, S. L. (Ed.), Electricity deregulation: Choices and challenges. Chicago: University of Chicago Press.Google Scholar
  5. Bazaraa, M. S., Sherali, H. D., & Shetty, C. M. (2006). Nonlinear programming—Theory and algorithms. Hoboken: Wiley.CrossRefGoogle Scholar
  6. Benders, J. F. (1962). Partitioning procedures for solving mixed-variables programming problems. Numerische Mathematik, 4, 238–252.CrossRefGoogle Scholar
  7. Bertsch, J., Brown, T., Hagspiel, S., & Just, L. (forthcoming). The relevance of grid expansion under zonal markets. The Energy Journal.Google Scholar
  8. Boyd, S., Xiao, L., Mutapcic, A., & Mattingley, J. (2008). Notes on decomposition methods.Google Scholar
  9. Brunekreeft, G., Neuhoff, K., & Newbery, D. (2005). Electricity transmission: An overview of the current debate. Utilities Policy, 13(2), 73–93.CrossRefGoogle Scholar
  10. Burstedde, B. (2012). Essays on the economic of congestion management—Theory and model-based analysis for Central Western Europe. Ph.D. thesis, Universität zu Köln.Google Scholar
  11. Capacity Allocating Service Company (2014, May). Documentation of the CWE FB MC solution—As basis for the formal approval-request.Google Scholar
  12. Caramanis, M. (1982). Investment decisions and long-term planning under electricity spot pricing. IEEE Transactions on Power Apparatus and Systems, PAS-101(12), 4640–4648.Google Scholar
  13. Chao, H.-P., Peck, S., Oren, S., & Wilson, R. (2000). Flow-based transmission rights and congestion management. The Electricity Journal, 13(8), 38–58.CrossRefGoogle Scholar
  14. Conejo, A. J., Castillo, E., Minguez, R., & Garcia-Bertrand, R. (2006). Decomposition techniques in mathematical programming—Engineering and science applications. Berlin: Springer.Google Scholar
  15. Daxhelet, O., & Smeers, Y. (2007). The EU regulation on cross-border trade of electricity: A two-stage equilibrium model. European Journal of Operations Research, 181, 1396–1412.CrossRefGoogle Scholar
  16. Ehrenmann, A., & Smeers, Y. (2005). Inefficiencies in European congestion management proposals. Utilities Policy, 13(2), 135–152.CrossRefGoogle Scholar
  17. European Commission (2013, March). Green Paper—A 2030 framework for climate and energy policies. COM(2013) 169 final.Google Scholar
  18. European Commission (2014, January). Impact assessment—A 2030 framework for climate and energy policies. SWD(2014) 15 final.Google Scholar
  19. Fürsch, M., Hagspiel, S., Jägemann, C., Nagl, S., Lindenberger, D., & Tröster, E. (2013). The role of grid extensions in a cost-effcient transformation of the European electricity system until 2050. Applied Energy, 104, 642–652.CrossRefGoogle Scholar
  20. Glachant, J.-M. (2010). The achievement of the EU electricity internal market through market coupling. EUI Working Papers, RSCAS 2010/87.Google Scholar
  21. Green, R. (2007). Nodal pricing of electricity: How much does it cost to get it wrong? Journal of Regulatory Economics, 31(2), 125–149.CrossRefGoogle Scholar
  22. Hagspiel, S., Jägemann, C., Lindenberger, D., Brown, T., Cherevatskiy, S., & Tröster, E. (2014). Cost-optimal power system extension under flow-based market coupling. Energy, 66, 654–666.CrossRefGoogle Scholar
  23. Höffler, F., & Wambach, A. (2013). Investment coordination in network industries: The case of electricity grid and electricity. Journal of Regulatory Economics, 44(3), 287–307.CrossRefGoogle Scholar
  24. Hogan, W. W. (1992). Contract networks for electric power transmission. Journal of Regulatory Economics, 4(2), 211–242.CrossRefGoogle Scholar
  25. Hogan, W., Rosellón, J., & Vogelsang, I. (2010). Toward a combined merchant-regulatory mechanism for electricity transmission expansion. Journal of Regulatory Economics, 38, 113–143.CrossRefGoogle Scholar
  26. Huppmann, D., & Egerer, J. (2014). National-strategic investment inEuropean power transmission capacity. DIW Discussion Papers, No. 1379.Google Scholar
  27. Jägemann, C., Fürsch, M., Hagspiel, S., & Nagl, S. (2013). Decarbonizing Europe’s power sector by 2050—Analyzing the implications of alternative decarbonization pathways. Energy Economics, 40, 622–636.CrossRefGoogle Scholar
  28. Joskow, P., & Tirole, J. (2005). Merchant transmission investment. The Journal of Industrial Economics, 53(2), 233–264.CrossRefGoogle Scholar
  29. Kunz, F. (2013). Improving congestion management: How to facilitate the integration of renewable generation in germany. The Energy Journal, 34(4), 55–78.CrossRefGoogle Scholar
  30. Kurzidem, M.J. (2010). Analysis of flow-based market coupling in oligopolistic power markets. Ph.D. thesis, ETH Zurich.Google Scholar
  31. Leuthold, F., Weigt, H., & von Hirschhausen, C. (2008). Efficient pricing for European electricity networks—The theory of nodal pricing applied to feeding-in wind in Germany. Utilities Policy, 16, 284–291.CrossRefGoogle Scholar
  32. Murty, K. G. (1983). Linear Programming. New York: Wiley.Google Scholar
  33. Neuhoff, K., Boyd, R., Grau, T., Barquin, J., Echabarren, F., Bialek, J., et al. (2013). Renewable electric energy integration: Quantifying the value of design of markets for international transmission capacity. Energy Economics, 40, 760–772.CrossRefGoogle Scholar
  34. Oggioni, G., & Smeers, Y. (2012). Degree of coordination in market coupling and counter-trading. The Energy Journal, 33(3), 39–90.CrossRefGoogle Scholar
  35. Oggioni, G., & Smeers, Y. (2013). Market failures of market coupling and counter-trading in europe: An illustrative model based discussion. Energy Economics, 35, 74–87.CrossRefGoogle Scholar
  36. Oggioni, G., Allevi, Y. S. E., & Schaible, S. (2012). A generalized nash equilibrium model of market coupling in the european power system. Networks & Spatial Economics, 12, 503–560.CrossRefGoogle Scholar
  37. Ozdemir, O., Munoz, F. D., Ho, J. L., & Hobbs, B. F. (2015). Economic analysis of transmission expansion planning with price-responsive demand and quadratic losses by successive lp. IEEE Transactions on Power Systems, PP(99), 1–12.Google Scholar
  38. Platts (2009, December). UDI World Electric Power Plants Data Base (WEPP).Google Scholar
  39. Richter, J. (2011). DIMENSION—a dispatch and investment model for European electricity markets. EWI WP 11/3.Google Scholar
  40. Rious, V., Dessante, P., & Perez, Y. (2009). Is combination of nodal pricing and average participation tariff the best solution to coordinate the location of power plants with lumpy transmission investment? EUI Working Papers, RSCAS 2009/14.Google Scholar
  41. Sauma, E. E., & Oren, S. S. (2006). Proactive planning and valuation of transmission investment in restructured electricity markets. Journal of Regulatory Economics, 30, 261–290.CrossRefGoogle Scholar
  42. Schweppe, F. C., Caramanis, M. C., Tabors, R. D., & Bohn, R. E. (1988). Spot pricing of electricity. Norwell, MA: Kluwer.CrossRefGoogle Scholar
  43. van der Weijde, A. H., & Hobbs, B. F. (2011). Locational-based coupling of electricity markets: Benefits from coordinating unit commitment and balancing markets. Journal of Regulatory Economics, 39, 223–251.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Department of EconomicsUniversity of CologneCologneGermany
  2. 2.ewi Energy Research and Scenarios gGmbHCologneGermany

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