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

Richard P. O'Neill, Eric A. Krall, Kory Hedman, Shmuel S. Oren

Research output: Contribution to journalArticlepeer-review

27 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)239-266
Number of pages28
JournalMathematical Programming
Volume140
Issue number2
DOIs
StatePublished - Sep 1 2013

Keywords

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

ASJC Scopus subject areas

  • Software
  • Mathematics(all)

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