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Research Area: Energy Systems

Affiliated Faculty: Hopkins, Safiuddin, Sarjeant, Zirnheld

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W.J. Sarjeant, Jennifer Zirnheld: Energy Systems Institute

The Energy Systems Institute headed by Dr. Sarjeant is funded by U. S. Army, Sandia National Labs, and Office of Naval Research. Industrial collaborations include TPL, Inc., General Atomics – Electronic Systems, IInc., and AMBP Tech.
- U.S. Army
  - Mobility Power and Energy Management at the System Level
  - Power partitioning for advanced/ diverse mobility platforms
  - Flashover Robustness
  - Supports flashover or induced flashover on power utility grid insulators and electronic countermeasures systems (completed)
  - Low Energy Ignition/ Controlled Surface Fuzing
  - Part of a green/ electric munitions effort by Picatinny
- Sandia National Laboratory
  - High energy density ceramic capacitor program
  - To develop capacitors for high rep-rate, high power and pulsed power applications. Show below are some capacitors developed by the Institute.
- Office of Naval Research
  - New and novel dielectric materials program for higher energy, dense, pulsed power capacitors
  - Goal is to characterize new high dielectric constant materials
  - Material development with industry
- TPL, Inc.
  - Novel thin dielectric film assessment
  - Develop thin films with high energy density
  - 3-4 times better than current state-of-the-art
  - Applications include aircraft launch defibulators, electric guns and armor, and ECM systems
- GA-ESI
  - Evaluate new and novel technology for high energy density capacitors for commercial and military applications
- AMBP
  - Develop and characterize high-stability fluroniated polymer carbon films for capacitor use. A sample under testing is shown below.

Mohammed Safiuddin: Power Systems

Neural Network Pattern Recognition Schemes for Identification and Location of Faults in Thyristor Controlled Series-Compensated (TCSC) HV Power Transmission Lines
- This research project resulted in the development of an Artificial Neural Network protection system for classifying and locating faults in Thyristor-Controlled Series Compensated (TCSC) transmission lines. The scheme is based on Multi-layer Perceptron Neural Networks (MLPNN). The Levenberg-Marquardt (LM) training algorithm is employed. Three-phase power system currents and voltages at the relay location are used as inputs to MLPNN-based relay. Two neural networks are trained to address fault classification and location. Feasibility and reliability of the proposed scheme are investigated using fault data set of a typical 500 kV power system simulated in EMTP-ATP software package. Studied system is subjected to all possible faults at different operating conditions, including fault location, fault inception angle and fault resistance. Simulation results demonstrate the robustness and fault tolerant features of proposed protection system.
Evaluation of Performance of an Electrical Generator with a Superconductor Element as Rotor
- This research was conducted to evaluate energy conversion potential of an innovative electrical generator, employing a YBCO superconductor thin film disk rotor. Creating a rate of change of flux in a magnetic field using the “flux repulsion” property of superconductors, an electrical generator was realized. Using ANSYS simulation and a simplified experimental set up, the feasibility of the design concept of proposed device were evaluated for different magnetic field strengths and at different rotating speeds of the superconductor disk.
Dynamic Analysis of Fuel Cell/Microturbine Generation Scheme with Neural Network Control for Peak Power Shaver Applications
- Integrating distributed generation (DG) into the existing power system for peak power shaving has proven to be beneficial economically and technologically. It has been used in many applications but the dynamics associated within the peak power shaver (PPS) have not been studied before. The objective of this research was to study the dynamic behavior of a DG system consisting of a microturbine operating in parallel with a fuel cell when supplying an isolated load and sharing the load with the grid during peak periods. Addition of batteries for energy storage to reduce the response time of the system to adapt to rapid load variations was investigated. A fuel cell laboratory emulator using a DC generator was designed and implemented. Computer simulation results were verified with those from experimental models. A direct inverse control system using neural networks was developed and demonstrated through emulators.

Douglas Hopkins: Embedded Circuits

Dr. Hopkins teams up with other UB faculty to develop a new class of embedded circuits able to function in hostile, high-temperature environments. Where normal circuits are limited to 150 o C, advanced silicon carbide (SiC) power semiconductors now operate at 350 o C, making them useful for severe commercial and military applications.
Sophisticated materials characterization and model development provide predictive reliability modeling of several circuit configurations developed by Dr. Hopkins. The electro-physical topology provides a dense, high temperature, and air-cooled circuit.
By successfully mating a SiC device to a metalized composite, Dr. Hopkins and his collaborators are developing a circuit capable to endure repeated temperature shifts between -55 o C and +225 o C. The project is funded by the Naval Research Laboratory.