O
Om P. Malik
Researcher at University of Calgary
Publications - 429
Citations - 11673
Om P. Malik is an academic researcher from University of Calgary. The author has contributed to research in topics: Electric power system & Control theory. The author has an hindex of 54, co-authored 416 publications receiving 10406 citations. Previous affiliations of Om P. Malik include Amirkabir University of Technology.
Papers
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Proceedings ArticleDOI
A review of wind power and wind speed forecasting methods with different time horizons
TL;DR: In this article, the main challenges and problems associated with wind power prediction are discussed, and an overview of comparative analysis of various available forecasting techniques is discussed as well as a major challenges and major challenges.
Journal ArticleDOI
Risk-based distributed generation placement
TL;DR: In this article, a multi-objective model for the placement of distributed generation (DG) units in the distribution networks in an uncertain environment is presented. And the true Pareto-optimal solutions are found with a multiobjective genetic algorithm and the final solution is found using a max-min approach.
Journal ArticleDOI
Power System Stabilizer Based on Adaptive Control Techniques
TL;DR: In this paper, a modified form of one of the more promising adaptive control algorithms for power systems is developed and described, and compared results of studies with adaptive stabilizer based on two alternate adaptive control algorithm and a conventional fixed parameter stabilizer show the improvement in response obtained with the adaptive algorithm.
Journal ArticleDOI
Wind Energy Conversion Using A Self-Excited Induction Generator
G. Raina,Om P. Malik +1 more
TL;DR: In this article, a wind energy conversion scheme using an induction machine driven by a variable speed wind turbine is described, where a single value capacitor and a thyristor controlled inductor are employed for energy conversion.
Journal ArticleDOI
High impedance fault detection based on wavelet transform and statistical pattern recognition
TL;DR: In this article, a novel method for high impedance fault (HIF) detection based on pattern recognition systems is presented, using this method, HIFs can be discriminated from insulator leakage current (ILC) and transients such as capacitor switching, load switching (high/low voltage), ground fault, inrush current and no load line switching.