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Does risk aversion affect transmission and generation planning? A Western North America case study

Author

Listed:
  • Francisco D. Munoz

    (Facultad de Ingeniería y Ciencias, Universidad Adolfo Ibáñez, Peñalolén, Santiago, Chile)

  • Adriaan Hendrik van der Weijde

    (School of Engineering, The University of Edinburgh, Edinburgh)

  • Benjamin F. Hobbs

    (Whiting School of Engineering, Johns Hopkins University, Baltimore, USA.)

  • Jean-Paul Watson

    (Department of Discrete Math and Optimization, Sandia National Laboratories, Albuquerque, USA.)

Abstract

We investigate the effects of risk aversion on optimal transmission and generation expansion planning in a competitive and complete market. To do so, we formulate a stochastic model that minimizes a weighted average of expected transmission and generation costs and their conditional value at risk (CVaR). We show that the solution of this optimization problem is equivalent to the solution of a perfectly competitive risk-averse Stackelberg equilibrium, in which a risk-averse transmission planner maximizes welfare after which risk-averse generators maximize profits. This model is then applied to a 240-bus representation of the Western Electricity Coordinating Council, in which we examine the impact of risk aversion on levels and spatial patterns of generation and transmission investment. Although the impact of risk aversion remains small at an aggregate level, state-level impacts on generation and transmission investment can be significant, which emphasizes the importance of explicit consideration of risk aversion in planning models.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Francisco D. Munoz & Adriaan Hendrik van der Weijde & Benjamin F. Hobbs & Jean-Paul Watson, 2016. "Does risk aversion affect transmission and generation planning? A Western North America case study," Working Papers EPRG 1621, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    • Handle: RePEc:enp:wpaper:eprg1621
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    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

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