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Mathematical Programming

, Volume 140, Issue 2, pp 239–266 | Cite as

A model and approach to the challenge posed by optimal power systems planning

  • Richard P. O’NeillEmail author
  • Eric A. Krall
  • Kory W. Hedman
  • Shmuel S. Oren
Full Length Paper Series B

Abstract

Currently, there is a need to plan and analyze the electric power transmission system in greater detail and over larger geographic areas. Existing models approach the problem from different perspectives. Each model addresses different aspects of and has different approximations to the optimal planning process. In order to scope out the huge challenge of optimal transmission planning, this paper presents a new modeling approach for inter-regional planning and investment in a competitive environment. This modeling approach incorporates the detailed generator, topology and operational aspects found in production cost planning models into a larger framework that can find optimal sets of transmission expansion projects. The framework proposed here can be used in an auction to award investment contracts or as a part of a more general policy analysis. The solution yields the set of transmission projects that have the highest expected benefits, while also representing generic generation expansions under the same objective. The model is a two-stage, mixed-integer, multi-period, N-1-reliable model with investment, unit commitment, and transmission switching. The combination of combinatorial, stochastic and operational elements means this model may be computationally intractable without judicious modelling aggregations or approximations to reduce its size and complexity. Nevertheless we show via a dual problem that analysing the economics and sensitivity of the solution is computationally more straightforward.

Keywords

Duality Integer programming Stochastic programming  Generation unit commitment Investment Power system economics 

Mathematics Subject Classification

90B15 Network models, stochastic 90C11 Mixed integer programming 90C90 Applications of mathematical programming 91B32 Resource and cost allocation  91B26 Market models (auctions, bargaining, bidding, selling, etc.) 

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Copyright information

© Springer-Verlag Berlin Heidelberg and Mathematical Optimization Society (Outside the USA) 2013

Authors and Affiliations

  • Richard P. O’Neill
    • 1
    Email author
  • Eric A. Krall
    • 1
  • Kory W. Hedman
    • 2
  • Shmuel S. Oren
    • 3
  1. 1.Federal Energy Regulatory CommissionWashingtonUSA
  2. 2.Arizona State UniversityTempeUSA
  3. 3.University of California-BerkeleyBerkeleyUSA

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