NDLI: Probabilistic wind power penetration of power system using nonlinear predictor-corrector primal-dual interior-point method

Content Provider	IEEE Xplore Digital Library
Author	Wei Zhou Yu Peng Hui Sun
Copyright Year	2008
Description	Author affiliation: Dept. of Electr. & Electron. Eng., Dalian Univ. of Technol., Dalian (Wei Zhou; Yu Peng; Hui Sun)
Abstract	In this paper an application of the nonlinear predictor-corrector primal-dual interior-point (IP) optimization method to wind power penetration is presented. The predictor- corrector primal-dual IP method improves the performance of the pure primal-dual IP algorithm by reducing the number of matrix factorizations to a necessary minimum. However, as wind power is stochastic and fluctuated with the variation of wind speed, the deterministic analysis approach is much more conservative for the power system containing wind farms. This paper proposes a probabilistic method to calculate the wind power penetration based on the nonlinear predictor-corrector primal-dual IP method. And the PQ model for double-fed wind power generator maintaining a constant power factor has been constructed and integrated into the presented method. The optimization results of a numerical example for IEEE 118-bus demonstrate that the proposed method is validated and fast compared with the pure primal-dual IP algorithm.
Starting Page	2548
Ending Page	2552
File Size	465147
Page Count	5
File Format	PDF
ISBN	9787900714138
DOI	10.1109/DRPT.2008.4523840
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-04-06
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	DRPT
Subject Keyword	Wind energy Power systems Optimization methods Power system modeling Stochastic systems Wind speed Power system analysis computing Wind farms Power generation Wind energy generation wind farm planning Grid integration interior-point method nonlinear programming optimization methods penetration power systems probability voltage stability wind energy
Content Type	Text
Resource Type	Article

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