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									       Electric Power Group

Electric Power Technical Interest Group
• ECE offers one of the country’s leading
  undergraduate and graduate academic programs in
  electric power engineering
• Broad range of activities relative to peers in power:
    • power systems
    • power electronics and controls
    • power apparatus (machines, semiconductors,
      high voltage equipment)
    • photovoltaics
Electric Power Group
Miroslav Begovic, Assoc. Professor
• Power system analysis, protection and emergency control
• Distributed energy resources: planning, interaction with distribution and transmission
• Sustainable energy systems
• Distribution network analysis

 Thomas G. Habetler, Professor
 • Current-based condition monitoring of electric machines
 • Control of electric machine drives
 • Power electronics
 • Design and protection of electric machines

 Ronald G. Harley, Duke Power Dist. Professor
 • Power system stability and control, including Flexible AC Systems (FACTS) devices
 • Power electronics, motor drives and electric vehicles
 • Neural networks applied to power electronics and electrical machines

    Jerome M. Meisel, Part-time Professor
    • Future Truck Team Advisor
    • Electric Vehicles
    • Power Electronics
Electric Power Group
   A.P. Sakis Meliopoulos, Professor
   • Power System Reliability and Risk Assessment
   • Power Systems Operations Planning
   • Electromagnetic Influence of Power Systems
   • Power Quality
   • Protective Relaying and Disturbance Analysis
   • Simulation, Animation and Visualization of Power System

   Hans B. Puttgen, Georgia Power Dist. Professor
   • Director of NEETRAC
   • Director of GT-Lorraine
   • ECE Associate Director of External Affairs
   • Power systems analysis and planning
   • Utility deregulation
   • Electric transportation vehicles and systems

    Ajeet Rohatgi, Georgia Power Dist. Professor
    •Director, University Center of Excellence for Photovoltaics Research and Education
    •Modeling and fabrication of low-cost high-efficiency silicon solar cells
    •Growth and characterization of low-temperature and high-performance dielectrics
    •Defects and carrier lifetime in semiconductors
    •Growth and optoelectronic properties of compound semiconductors
Electric Power Group

                Affiliated Faculty
   Christina B. Honsberg, Associate Professor
      •Design, development and characterization of novel commercially oriented solar cell
               structures using the buried contact technology
      •Identification, modeling and analysis of novel techniques to overcome traditional
      homojunction or two-stack tandem efficiency limits
      •Gallium Arsenide Solar Cells

   David G. Taylor, Professor
   • Nonlinear control systems
   • Electromechanical systems and devices
   • Modeling, simulation and control of assembly robots
   • Design and control of linear motion actuators and generators

    John F. Dorsey, Professor
         •Modeling and control of large-scale systems
       •Real time identification of parameters of power system models
       •On-line power system security assessment
       •Elimination of sustained oscillations in power systems
       •Effect on stability of nonutility generation
      Electric Power Group
          Areas of Educational and Research
              Activities in Electric Power

• Power system monitoring, analysis, protection,
  operation and control
• Distributed generation
• Power system simulation and visualization
• High voltage engineering and power system
• Electric machine control, condition monitoring, and
• Power Electronics
    Electric Power Group

      Research Centers

• $3M Consortium             • Materials
  Utilities                    1,000 sq. ft. Solar Cell
  Manufacturers                Fabrication Facility
  End Users
  Academia                   • Systems
• EV Research                  340 kW PV Array on GT
  200 HP Dynamometer           Olympic Natatorium Roof
  125 kW DC Test System
  EV Virtual Testbed
  EV Charger Power Quality
          Electric Power Group

                        Future Truck
• Student teams from 15 universities are challenged to re-
  engineer a conventional Ford Explorer into a lower-emissions
• Sponsored by the US DOE and Ford Motor Co.
       Electric Power Group
         Courses in Power Electronics and Machines
• ECE 3070 (3,0,3) – Introduction to Electromechanical Energy
   – Tier 2 course offered every semester
   – Prereq: ECE 2040, ECE 3025
• ECE 4803/6336 (3,0,3) – Electric Machinery Analysis
   – Taught concurrently as both undergrad and grad course.
   – Prereq: ECE3070, Offered summer of even years
• ECE 3881 (0,3,1) - Energy Conv & Mechatronics Lab
   – Laboratory portion of ECE3301
   – Offered every semester
   – Coreq: ECE3070
• ECE 6336 (3,0,3) – Dynamics and Control of Electric Machine Drives
   – Offered every spring
   – Prereq: ECE3070
     Electric Power Group
      Courses in Power Electronics and Machines

• ECE 4330 (2,2,3) – Power Electronics
   – Senior elective with lecture and lab
   – Offered every spring
   – Prereq: ECE 3040, ECE 3042
• ECE 6331 (3,0,3) – Power Electronic Circuits
   – Offered every fall
   – Prereq: ECE 4330
        Electric Power Group
       Research in Electric Machines and Power

• Rotating fault detection in induction machines.
• Neural network-based diagnostics using self organizing maps.
• Stator insulation fault detection using ANNs.
• Rotating fault detection in synchronous and brushless dc machines.
• Sensorless vibration detection in induction and synchronous machines.
• 25 kV power electronic sag supporter using a PWM-switched
  autotransformer .
       Electric Power Group

     Research in Electric Machines and Power Electronics

• Backpropagation neural networks for motor diagnostics (fault
• Sensorless speed measurement using slot harmonic detection and
  spectral estimation.
• Rotor temperature estimation based on rotor resistance thermal time
• Continuous on-line training of neural networks for motor control and
  power electronic applications.
• FPGA implementation of neural networks on motors.
• Turbogenerator identification and control using neural networks.

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