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Financial Transmission Rights pp 191–210Cite as

Mechanisms for the Optimal Expansion of Electricity Transmission Networks

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Part of the book series: Lecture Notes in Energy ((LNEN,volume 7))

Abstract

Electricity transmission grid expansion and pricing have received increasing attention in recent years. Transmission networks provide the fundamental support upon which competitive electricity markets depend. Congestion of transmission networks might increase market power in certain regions, put entry barriers to potential competitors in the generation business, and in general reduce the span of competitive effects. A well functioning transmission network is a critical component of wholesale and retail markets for electricity.

This paper was previously published as: Rosellón J (2009) Mechanisms for the optimal expansion of electricity transmission networks. In: Evans J, Hunt LC (eds) International handbook on the economics of energy. Edward Elgar Publishing, UK.

Support from Conacyt (p. 60334) and from Pieran-Colegio-de-México is gratefully acknowledged.

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Notes

  1. 1.

    Problems related with coordination and capacity to the transmission network partly caused power outages in the northeast of the US during 2003, which affected more than 20 million consumers and six control areas (Ontario, Quebec, Midwest, PJM, New England, and New York), and shut down 61,000 MW of generation capacity. Similar recent events in other parts of the world such as UK, Italy, Sweden, Brazil, Argentina, Chile New Zealand, and Germany (incidence of E.ON Netz that blacked out large chunks of Europe in 2006) also awakened the interest in the factors that ensure reliability of transmission grids.

  2. 2.

    Vogelsang (2006).

  3. 3.

    Loop flow is the characteristic of electricity that takes it through all available routes (path of least resistance) to get from one point to another. For instance, if a second line becomes available that is identical to a first line, the electricity that had been flowing over the first line will “divide” itself so that half of it will remain flowing through the first line and the other half will flow over the second (see Brennan et al. 1996).

  4. 4.

    Joskow and Tirole (2000), and Léautier (2001).

  5. 5.

    Wilson (2002).

  6. 6.

    Léautier (2001),

  7. 7.

    Wilson (2002).

  8. 8.

    In practice, the ISO model has been used in Argentina, and Australia. System operation is carried out by the ISO and transmission ownership is carried out by another independent company, the Gridco. ISOs also exist in California, New England, New York, Pennsylvania-New Jersey-Maryland (PJM), and the Texas. ISO practical experiences and proposals have been centralized. The Transo model has been typically used in practice in the UK, Spain and the Scandinavian countries.

  9. 9.

    Hogan (2002b).

  10. 10.

    Vogelsang (2006).

  11. 11.

    A third alternative method for transmission expansion seeks to derive optimal transmission expansion from the power-market structure of electricity generation, and considers conjectures made by each generator on other generators’ marginal costs due to the expansion (Wolak 2000). This method uses a real-option analysis to derive the net present value of both transmission and generation projects through the calculation of their joint probability. Transmission expansion only yields benefits until it is large enough compared to a given generation market structure. Likewise, many small upgrades are preferable to large greenfield project.

  12. 12.

    Vogelsang (2006) makes a division between Bayesian and non-Bayesian mechanism for transmission expansion. The Bayesian approach derives from the merger of the principal agent theory and the optimal pricing approach, and implies a theoretical framework supported by the Revelation Principle but that does not in general translate into rules that regulators can apply directly. According to the canonical model of regulation, under asymmetric information the need for prices to provide incentives arises when transfers from the regulator are not possible (Laffont 1994). Non-Bayesian mechanisms arise from more practical reasons so as to improve inadequacies associated to rate-of-return regulation. Then PBR regulation, including price-caps and yardsticks, were developed as non-Bayesian instruments to promote cost-minimization. However, the application of PBR to network industries has been scarce, mainly due the lumpy and long-term nature of networks, such as the electricity grid.

  13. 13.

    Léautier (2000), Grande and Wangensteen (2000), Vogelsang (2001), and Joskow and Tirole (2005).

  14. 14.

    Littlechild (2003).

  15. 15.

    Littlechild and Skerk (2004a, b).

  16. 16.

    Gans and King (1999), Léautier (2000), Grande and Wangensteen (2000), Joskow and Tirole (2002).

  17. 17.

    Crew et al. (1995).

  18. 18.

    Brown et al. (1991).

  19. 19.

    Vogelsang (1999).

  20. 20.

    Baldick et al. (2007), provide practical guidelines for allocation among consumers of the costs of transmission expansion.

  21. 21.

    See Vogelsang 1999, pp. 28–31.

  22. 22.

    See Ramírez and Rosellón (2002).

  23. 23.

    Hogan (2002a)

  24. 24.

    See Hogan et al. (2010) for a redefinition of transmission outputs in terms of point-to-point FTRs.

  25. 25.

    An application of the Vogelsang (2001) PBR model is carried out in Rosellón (2007) for the electricity transmission system in Mexico, under stable demand growth for electricity. Three scenarios are studied: (a) a single Transco providing transmission services nationally and that applies postage-stamp tariffs; (b) several regional companies that separately operate in each of the areas of the national transmission system, and that charge different prices; and (c) a single Transco owns all the regional systems in the nation but that charges different prices in each region. Achieved capacity and network increases are highest under the first scenario, while higher profits are implied by the second approach. These results are found to critically depend on two basic effects; namely, the “economies-of-scale effect” and the “discriminatory effect”. The economies-of-scale effect produces greater capacity and network expansion whereas the discriminatory effect increases profit.

  26. 26.

    Sappington and Sibley (1988), and Gans and King (1999).

  27. 27.

    The typical power-flow model framework is that of a centralized ISO that maximizes social welfare subject to transmission-loss and flow-feasibility constraints in a spot market. In practice, this model has been applied in Argentina, Australia, and several regions in the United States (Pennsylvania-Maryland-New Jersey (PJM), New York, Texas, California). The economic dispatch model can also be understood within a static competitive equilibrium model. The producing entity is an ISO that provides transmission services, receives and delivers power, and coordinates the spot market. Meanwhile, consumers inject power into the grid at some nodes and remove power out at other points. See Hogan (2002b).

  28. 28.

    FTRs give their holders a share of the congestion surpluses collected by the ISO under a binding constraint. The quantity of FTRs is normally fixed ex ante and allocated to holders. This reflects the capacity of the network. The difference between allocated FTRs and actual transmission capacity provides congestion revenues for the ISO. FTRs are defined in terms of the difference in nodal prices. See Joskow and Tirole (2002).

  29. 29.

    Flowgate rights are defined in terms of the constraints implied from limits in the selling of capacity (Hogan 2000).

  30. 30.

    Pope (2002).

  31. 31.

    A set of FTRs is simultaneously feasible if the associated set of net loads satisfies the energy balance and transmission capacity constraints, as well as the power flow equations.

  32. 32.

    Other LTFTR allocation practical mechanisms are provided by Harvey (2002), and Gribik et al. (2002).

  33. 33.

    Revenue adequacy is the financial counterpart of the physical concept of availability of transmission capacity. FTRs meet the revenue-adequacy condition when they are also simultaneously feasible (Hogan 1992).

  34. 34.

    Littlechild (2003).

  35. 35.

    Joskow and Tirole (2005).

  36. 36.

    Joskow and Tirole (2000), Léautier (2001), and Gilbert et al. (2002).

  37. 37.

    Hogan (2002a), and Kristiansen and Rosellón (2006).

  38. 38.

    Hogan (2003).

  39. 39.

    Hogan (2002b).

  40. 40.

    Hogan (1999, 2000).

  41. 41.

    Bushnell and Stoft (1997).

  42. 42.

    Hogan (2002a), and Kristiansen and Rosellón (2006).

  43. 43.

    A general solution method utilizing Kuhn-Tucker conditions would check which of the constraints are binding. One way to identify the binding inequality constraints is the active set method. Kristiansen and Rosellón (2006) solve the problem in detail with simulations for different network topologies, including a radial line and three-node networks.

  44. 44.

    See also Brunekreeft et al. (2005).

  45. 45.

    This would be an alternative approach to the previously seen model in Vogelsang (2006). A main difference would be that the combined merchant-regulatory approach mainly focuses in generalizing the price-cap constraints for electricity transmission (as in Vogelsang 2006) within a power flow model. Likewise, this combined model aims to redefine the output of transmission in terms of PTP transactions (or incremental FTRs) as well as to seriously tackle the “heroic” assumption of smooth well-behaved transmission cost functions of the models in Vogelsang 2001, 2006, and Tanaka 2007.

  46. 46.

    Of course, this includes (RPI-X) adjustments together with cost-of-service tariff reviews at the end of each regulatory lag.

  47. 47.

    The Kristiansen and Rosellón (2006) model is an example of a concrete merchant mechanism designed for small line increments in meshed transmission networks.

  48. 48.

    Under Laspeyres weights – and assuming that cross-derivatives have the same sign – if goods are complements and if prices are initially above to marginal costs, prices will intertemporally converge to marginal costs. When goods are substitutes, this effect is only obtained if the cross effects are smaller than the direct effects. If prices are below marginal costs the opposite results are obtained.

  49. 49.

    As in Rosellón and Weigt (2011).

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Authors and Affiliations

  1. División de Economía, Centro de Investigación y Docencia Económicas (CIDE), Carretera México-Toluca 3655, Mexico, D.F, 01210, Mexico

    Juan Rosellón

  2. German Institute for Economic Research (DIW Berlin), Mohrenstrasse 58, Berlin, 10117, Germany

    Juan Rosellón

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  1. Juan Rosellón
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  1. Económicas (CIDE), Department of Economics, Centro de Investigación y Docencia, Carretera Mexico-Toluca 3655, Mexico, 06400, Mexico

    Juan Rosellón

  2. Åsegårdsvegen 65, Ålesund, 6017, Norway

    Tarjei Kristiansen

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Rosellón, J. (2013). Mechanisms for the Optimal Expansion of Electricity Transmission Networks. In: Rosellón, J., Kristiansen, T. (eds) Financial Transmission Rights. Lecture Notes in Energy, vol 7. Springer, London. https://doi.org/10.1007/978-1-4471-4787-9_7

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