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Q. Fang, Identifiability Analysis of a Wind Generation Unit Model Using Global Sensitivity Analysis, 3rd March 2016.

  Abstract: This seminar presents a parameter identifiability method based on the Global Sensitivity Analysis (GSA), and its application in parameter estimation of a wind generation unit model. The GSA determines which model parameters will effect observations that are used in the parameter estimation procedure. Parameters with negligible impact on the observations are not identifiable. […]

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Q. Fang, A Global Optimization Framework for Parameter Estimation of a Wind Generation Unit Model, 26th November 2015.

  Abstract: This research purposes a global optimization method that could be applied in parameter estimation of wind generation unit model. When complex nonlinear models, like a wind generation unit model are used, the parameter estimation based on local optimization methods, such as nonlinear least squares method or Newton’s method, may not be able to […]

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Research Seminar 27th November, Miss Q. Fang – Parameter Identification of a Wind Generator Unit RMS Model Using Sparse Grid Optimization Algorithm

  Abstract: This paper presents a global sparse grid optimization algorithm applied in parameter identification of a wind generation Root Mean Square (RMS) phasor model. The details of vendor specific RMS models used in dynamic simulation software (e.g. PSSE) are not provided by manufacturers. Therefore, there is a need to develop a procedure which can […]

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