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Andrew M. Knight

Researcher at University of Calgary

Publications -  186
Citations -  4741

Andrew M. Knight is an academic researcher from University of Calgary. The author has contributed to research in topics: Inverter & Induction motor. The author has an hindex of 34, co-authored 176 publications receiving 4229 citations. Previous affiliations of Andrew M. Knight include University of Technology, Sydney & University of Alberta.

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A review of power converter topologies for wind generators

TL;DR: In this paper, a comprehensive review of past and present converter topologies applicable to permanent magnet generators, induction generators, synchronous generators and doubly fed induction generators is presented and compared on the basis of topology, cost, efficiency, power consumption and control complexity.
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Design and Analysis of Brushless Doubly Fed Reluctance Machines

TL;DR: Analytical approaches to design a BDFRM with desirable qualities and the use of time-stepped finite-element analysis to validate the results of the design process are presented.
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Comparison of the Effects of Continuous and Discontinuous PWM Schemes on Power Losses of Voltage-Sourced Inverters for Induction Motor Drives

TL;DR: In this article, a comparison of inverter losses with sinusoidal pulsewidth modulation (PWM), space vector PWM and discontinuous PWM (DPWM) is presented, concluding that DPWM is the method of choice.
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Simple wind energy controller for an expanded operating range

TL;DR: In this paper, the authors proposed a power electronic converter, designed for efficiency, simplicity and ruggedness, for small-scale stand-alone wind energy systems, finding applications in locations where conventional generation is not practical.
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Risk-Constrained Bidding and Offering Strategy for a Merchant Compressed Air Energy Storage Plant

TL;DR: In this article, an information gap decision theory (IGDT)-based risk-constrained bidding/offering strategy for a merchant compressed air energy storage (CAES) plant that participates in the day-ahead energy markets considering price forecasting errors is proposed.