A chance constrained transmission network expansion planning method with consideration of load and wind farm uncertainties

H. Yu, C. Y. Chung, K. P. Wong, J. H. Zhang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

303 Citations (Scopus)

Abstract

This paper proposes a chance constrained formulation to tackle the uncertainties of load and wind turbine generator in transmission network expansion planning. A combined Monte Carlo simulation/analytical probabilistic power flow analysis method is first presented to obtain the probability density function of wind turbine generator output. The paper then shows the development of the chance constrained formulation with the inclusion of the wind turbine generator probability density function and probabilistic power flow in the formulation. The proposed formulation is more computationally efficient and can deal with uncertainties in transmission network expansion planning. The power of the new method is shown through the application of the formulation to two test systems.

Original languageEnglish
Pages (from-to)1568-1576
Number of pages9
JournalIEEE Transactions on Power Systems
Volume24
Issue number3
DOIs
Publication statusPublished - 2009

Keywords

  • Chance constrained programming
  • Probability
  • Transmission network planning
  • Wind turbine generator

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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