H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Engineering and Technology D-index 32 Citations 10,520 284 World Ranking 5043 National Ranking 215

Overview

What is he best known for?

The fields of study he is best known for:

  • Electrical engineering
  • Artificial intelligence
  • Statistics

Michael Negnevitsky spends much of his time researching Wind power, Electric power system, Control theory, Distributed generation and Reliability engineering. His Wind power research integrates issues from Electricity generation, Simulation, Electricity market and Renewable energy. His Electric power system research incorporates themes from Electricity, Demand response, Artificial neural network, Load management and Operations research.

His work carried out in the field of Control theory brings together such families of science as Permanent magnet synchronous generator, Variable speed wind turbine, Chopper and AC power. Expert system is closely connected to Sensitivity in his research, which is encompassed under the umbrella topic of AC power. His Distributed generation study integrates concerns from other disciplines, such as Mathematical optimization and Power loss.

His most cited work include:

  • Artificial Intelligence: A Guide to Intelligent Systems (1436 citations)
  • A Novel Control Strategy for a Variable-Speed Wind Turbine With a Permanent-Magnet Synchronous Generator (415 citations)
  • Very short-term wind forecasting for Tasmanian power generation (295 citations)

What are the main themes of his work throughout his whole career to date?

Michael Negnevitsky mainly investigates Electric power system, Control theory, Wind power, Control engineering and Renewable energy. His Electric power system research incorporates themes from Distributed generation, Electricity, Demand response, Reliability engineering and Expert system. His Control theory research focuses on subjects like Voltage, which are linked to Electronic engineering and Mathematical optimization.

His studies examine the connections between Wind power and genetics, as well as such issues in Fault, with regards to Inverter. His Control engineering study combines topics in areas such as Artificial neural network, Control and Energy. The Renewable energy study combines topics in areas such as Automotive engineering and Energy storage.

He most often published in these fields:

  • Electric power system (34.58%)
  • Control theory (22.90%)
  • Wind power (19.39%)

What were the highlights of his more recent work (between 2015-2021)?

  • Electric power system (34.58%)
  • Renewable energy (14.95%)
  • Automotive engineering (10.75%)

In recent papers he was focusing on the following fields of study:

Michael Negnevitsky mostly deals with Electric power system, Renewable energy, Automotive engineering, Control theory and Distributed generation. The concepts of his Electric power system study are interwoven with issues in Wind power, Reliability engineering, Frequency response, Automatic frequency control and Demand response. His Wind power study incorporates themes from Turbine, Simulation, Fault current limiter and Electricity market.

His Renewable energy research incorporates elements of Hybrid power, Smart grid, Low load and Energy storage. His studies deal with areas such as Permanent magnet synchronous generator, Model predictive control, Capacitor, AC power and Fault as well as Control theory. His study in Distributed generation is interdisciplinary in nature, drawing from both Electricity, Probabilistic logic, Mathematical optimization, Voltage and Monte Carlo method.

Between 2015 and 2021, his most popular works were:

  • Low voltage ride-through enhancement of DFIG-based wind turbine using {DC} link switchable resistive type fault current limiter (38 citations)
  • Energy Exchange Between Electric Vehicle Load and Wind Generating Utilities (35 citations)
  • Optimizing distributed generation parameters through economic feasibility assessment (32 citations)

In his most recent research, the most cited papers focused on:

  • Electrical engineering
  • Artificial intelligence
  • Statistics

His primary areas of investigation include Control theory, Energy storage, Fault, Renewable energy and Wind power. His research in Control theory intersects with topics in Probability density function, AC power and Model predictive control. His Fault research is multidisciplinary, incorporating elements of Induction generator and Fault current limiter, Electric power system.

Michael Negnevitsky has researched Electric power system in several fields, including Chopper and Converters. The various areas that Michael Negnevitsky examines in his Renewable energy study include Hybrid power and Mathematical optimization. His studies in Wind power integrate themes in fields like Linear programming and Electric vehicle.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Artificial Intelligence: A Guide to Intelligent Systems

Michael Negnevitsky.
(2001)

3944 Citations

A Novel Control Strategy for a Variable-Speed Wind Turbine With a Permanent-Magnet Synchronous Generator

M.E. Haque;M. Negnevitsky;K.M. Muttaqi.
IEEE Transactions on Industry Applications (2010)

786 Citations

Very short-term wind forecasting for Tasmanian power generation

C.W. Potter;M. Negnevitsky.
IEEE Transactions on Power Systems (2006)

463 Citations

Pool-Based Demand Response Exchange—Concept and Modeling

Duy Thanh Nguyen;Michael Negnevitsky;Martin de Groot.
IEEE Transactions on Power Systems (2011)

255 Citations

Distributed generation for minimization of power losses in distribution systems

M.A. Kashem;A.D.T. Le;M. Negnevitsky;G. Ledwich.
2006 IEEE Power Engineering Society General Meeting (2006)

232 Citations

A Neural-Fuzzy Classifier for Recognition of Power Quality Disturbances

Jiansheng Huang;M. Negnevitsky;D.T. Nguyen.
IEEE Power & Energy Magazine (2001)

173 Citations

A Novel Operation and Control Strategy for a Standalone Hybrid Renewable Power System

A. M. O. Haruni;M. Negnevitsky;M. E. Haque;A. Gargoom.
IEEE Transactions on Sustainable Energy (2013)

145 Citations

Control of a stand alone variable speed wind turbine with a permanent magnet synchronous generator

M.E. Haque;K.M. Muttaqi;M. Negnevitsky.
power and energy society general meeting (2008)

138 Citations

Short term wind power forecasting using hybrid intelligent systems

M. Negnevitsky;P. Johnson;S. Santoso.
2007 IEEE Power Engineering Society General Meeting (2007)

121 Citations

A Coordinated Voltage Control Approach for Coordination of OLTC, Voltage Regulator, and DG to Regulate Voltage in a Distribution Feeder

Kashem M. Muttaqi;An D. T. Le;Michael Negnevitsky;Gerard Ledwich.
IEEE Transactions on Industry Applications (2015)

109 Citations

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