The research group focuses on modeling, simulation, analysis, design, control, and optimization of power and energy systems, including electric machinery and drive systems, power electronics, and power systems. Such work has applications in manufacturing, electric transportation, appliances, HVAC, industrial processes, renewable energy, power generation, transmission, distribution, and utilization, and special-purpose power systems. Work in electric machinery includes the development of advanced machine models, which include nonlinear and distributed effects, and appropriate formulations of these models for simulation. In power electronics, advanced averaging techniques, including hysteresis current control models and multifrequency models have been developed. In the renewable energy area, advances in modeling photovoltaic modules and control of inverters and distribution systems for high-penetration of renewables have been made. Finally, research in simulation and optimization, including market-based optimization and control, risk-based optimization, and simulation-based optimization, has been conducted.

Distributed Generation Reactive Power Control for Chance Constrained Distribution System Performance Optimization.

The research on which Sarmad Ibrahim is working for his Ph. D research is distributed generation reactive power control for chance constrained distribution system performance optimization. The main idea is to maximize the expected value of a figure of merit by controlling PV inverters, finding the optimal solution for both the voltage fluctuation problems and the maximum expected value of a figure of merit based on a linear optimization method. In this research, different reactive power output will be injected into specific locations each second during 15-min window. In conjunction with maximizing the expected value of a figure of merit algorithm, a new reactive power control is harnessed to reduce voltage fluctuations along the distribution feeder. The linear optimization program is iteratively used to choose the best control parameters in which the maximum expected value of a figure of merit will be obtained based on the mean (expected value of each PV phase) and variance that are computed from the forecasting method. MATLAB will be mainly used in this research.

Students

Sarmad Ibrahim

Musharrat Sabah, Graduate, Added 03/21/2022 on LCC

Publications:

M. Liu and A. M. Cramer, “Computing budget allocation in multi-objective evolutionary algorithms for stochastic problems,” Swarm and Evolutionary Computation, vol. 38, pp. 267–274, Feb. 2018.
M. Liu and A. M. Cramer, “Genetic algorithm with integrated computing budget allocation for stochastic optimization,” Int. J. Metaheuristics, vol. 5, no. 2, pp. 115–135, Nov. 2016.
Y. Q. Zhang and A. M. Cramer, “Unified model formulations for synchronous machine model with saturation and arbitrary rotor network representation,” IEEE Trans. Energy Conversion, accepted for publication.
M. Liu and A. M. Cramer, “Genetic algorithm with integrated computing budget allocation for stochastic optimization,” Int. J. Metaheuristics, accepted for publication.
H. Chen, A. M. Cramer, and X. Liu, “Average-value modeling of hysteresis current controlled three-phase inverters,” Electric Power Components and Systems, Electric Power Components and Systems, vol. 44, no. 6, pp. 693–700, 2016.
X. Liu, A. M. Cramer, and Y. Liao, “Reactive power control methods for photovoltaic inverters to mitigate short-term distribution system voltage magnitude fluctuations,” Electric Power Systems Research, vol. 127, pp. 213–220, Oct. 2015.
E. A. Paaso, Y. Liao, and A. M. Cramer, “Dual-layer voltage and var control approach with active participation from distributed generations,” Electric Power Components and Systems, vol. 43, no. 8–10, pp. 854–865, 2015.
E. A. Paaso, Y. Liao, and A. M. Cramer, “Formulation and solution of distribution system voltage and var control with distributed generation as a mixed integer non-linear programming problem,” Electric Power Systems Research, vol. 108, pp. 164–169, Mar. 2014.

Grants:

Market-based control of shipboard integrated engineering plants, ONR, PI, $503,400, funded, ONR Young Investigator award
A modular electrical power system architecture for small spacecraft, NASA Kentucky Space Grant (NASA), PI, $30,000, funded
Electric warship early design space methods incorporating dynamic energy storage, United States Naval Academy (ONR), PI, $44,100, funded
Electric power distribution system optimization in the presence of renewable distributed generation, Southeastern Center for Electrical Engineering Education, PI, $15,999, funded
A modular electrical power system architecture for small spacecraft, NASA Kentucky Space Grant (NASA), PI, $30,000, funded
Foundations for engineering education in distributed energy resources (FEEDER): A distributed technology training consortium, University of Central Florida (DOE), Co-I (PI: Larry Holloway), $535,001, funded
Market-based power allocation with energy storage, PC Krause and Associates (NASA), PI, $53,164, funded
NGIPS early design space assessment, ONR, PI, $54,060, funded
NGIPS early design space assessment, ONR, PI, $98,558, funded

Genetic algorithms in the presence of uncertainty with application to power electronics controller design

The project on which Mengmei Liu is working for her Ph. D. research is "Genetic algorithms in the presence of uncertainty with application to power electronics controller design." This project is examining methods of solving optimization problems under noisy environments using genetic algorithms and using statistical techniques to improve the efficiency and accuracy of the algorithm. In this project, multiple instances of a genetic algorithm will be executed in order to perform statistical analysis of the results of the algorithm. Additionally, computationally expensive fitness function evaluations may be distributed within the context of a single instance of the algorithm. MATLAB and C will be mainly used in this project.

Student:

Liu, Mengmei

Software:

MATLAB
C
Simulink
PI - Aaron M. Cramer, Assistant Professor
Electrical and Computer Engineering

Computational Methods

Genetic algorithm, including algorithms being developed within the project.

Publications

2013

1.S. Z. Aljoaba, A. M. Cramer, and B. L. Walcott, “Thermoelectrical modeling of wavelength effects on photovoltaic module performance – Part I: Model,” IEEE J. Photovoltaics, vol. 3, no. 3, pp. 1027–1033, Jul. 2013.
2.S. Z. Aljoaba, A. M. Cramer, S. A. Rawashdeh, and B. L. Walcott, “Thermoelectrical modeling of wavelength effects on photovoltaic module performance – Part II: Parameterization,” IEEE J. Photovoltaics, vol. 2, no. 3, pp. 1034–1037, Jul. 2013.

2012

1.A. M. Cramer, B. P. Loop, and D. C. Aliprantis, “Synchronous machine model with voltage-behind-reactance formulation of stator and field windings,” IEEE Trans. Energy Conversion, vol. 27, no. 2, pp. 391–402, Jun. 2012.

2011

1.A. M. Cramer, S. D. Sudhoff, and E. L. Zivi, “Performance metrics for electric warship integrated engineering plant battle damage response,” IEEE Trans. Aerospace and Electronic Systems, vol. 47, no. 1, pp. 634–646, Jan. 2011.
2.A. M. Cramer, S. D. Sudhoff, and E. L. Zivi, “Metric optimization-based design of systems subject to hostile disruptions,” IEEE Trans. Systems, Man, and Cybernetics, Part A: Systems and Humans, vol. 41, no. 5, pp. 989–1000, Sep. 2011.

Grants

Cramer, Aaron M SCEEE-14-003 Electric Power Distribution System Optimization in the Presence of Renewable Distributed Generation Southeastern Center for Electrical Engineering Ed 7/1/2014 - 6/30/2015 $15,999
Cramer, Aaron M N00189-14-P-1197 Electric Warship Early Design Space Methods Incorporating Dynamic Energy Storage Office of Naval Research 8/18/2014 - 8/17/2015 $44,100
Cramer, Aaron MNNX10AL96H NASA EPSCoR: A Modular Electrical Power System Architecture for Small Spacecraft National Aeronautics and Space Administration 1/1/2014 - 12/31/2014 SCOPE
Cramer, Aaron M N00014-12-1-0426 NGIPS Early Design Space Assessment $152,618 Office of Naval Research 3/1/2012 - 3/31/2014
Cramer, Aaron M PCK_UKY13CC80C_001 SBIR: Market-Based Power Allocation with Energy Storage $53,164 PC Krause and Associates Incorporated 7/18/2013 6/17/2015

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