projects available at unc charlotte - kit · or digsilent, or etap, or pscad, etc.) other skills...
Post on 25-Sep-2018
215 Views
Preview:
TRANSCRIPT
1
Projects available at UNC Charlotte
1. Project Title: Novel Peer to Peer (P2P) Energy Trading Applications using Advance Data Analytics . 2
2. Project Title: Development of emulated electromagnetic and mechanical inertia inside the
controller of a grid-tied PV inverter .............................................................................................................. 4
3. Project Title: Wideband Current Sensors for High Frequency Power Electronics Applications ........... 5
4. Predicting Impact of Thermal Energy Storage on German Power Market ........................................... 7
5. Project Title: Optimal Energy Dispatch for Demand Response of Residential PV-Battery Systems ..... 9
6. Project Title: Development of Nondestructive Techniques and Tools for In-Service Condition
Assessment of Timber Electrical Distribution Poles ................................................................................... 11
7. Project Title: Fault Detection for Solid State Circuit Breakers ............................................................ 13
8. Project Title: Evaluation of Instruments for Large-scale Metrology ................................................... 15
2
1. Project Title: Novel Peer to Peer (P2P) Energy Trading Applications using
Advance Data Analytics Energy Field Research Interest (please select from one of the options below)
1. Energy Markets and Analytics
2. Renewable Energy Devices and Integration
3. Power Grid Modernization
Abstract of the project In future the utilization of energy predictions systems
(incl. electricity price, renewable energy and load
forecasting models), distributed power generation and
consumption algorithms will be integrated into the
community based neighborhood energy infrastructure.
This will enable the distributed power procumers to
participate actively to the established / central power
markets and peer to peer energy markets. Thus
accurate and well-performing energy forecasting tools
are vital for the utilities, energy traders, power plant
operators and most importantly future procumer
market participants.
This project proposes to investigate the determining
the drivers of well-performing energy forecasting
applications such as further development of a multi-
model short-term electricity price forecasting,
renewable energy and energy demand forecasting
systems using advanced artificial intelligence and data
analytic techniques. Artificial neural networks (ANN),
statistical model and other artificial intelligence
methods will be tested and compared in terms of
performance. The model will include energy storage
units to optimize the power flow and trading. Therefore
in the final state an effective optimization algorithm will
be developed.
The models will be tested in a smart gird simulation
and power hardware-in the-loop (PHIL) environment in
the Duke Energy Smart Gird Laboratory.
Note: The first version of the electrical energy price
forecasting system was developed with a KIT
exchange student in the last term. First version of the
solar power forecasting is developed by the exchange
UNCC student who visited KIT last term. Therefore,
the next student will focus on further development of
existing algorithms but most importantly the main
target will be the development of optimization
3
algorithm and implementation of the peer to peer
neighborhood trading scenario to IEEE bus bar
systems in Simulink and RT lab (HIL) environment.
Tasks Literature research
Investigation of the US and Germany Power markets
Understanding and further improvement of existing
wind power, solar power and electricity price
forecasting algorithms using advance data analytics
and machine learning techniques.
Development of a basic electrical demand forecasting
model.
Development of optimization algorithm.
Implementation of the P2P energy trading scenarios in
Matlab/Simulink and RT Lab environments.
Testing the developed model in the Duke Energy
Smart Grid Lab.
Requirements Fundamental knowledge about the power markets
Basic knowledge about smart grids
Preliminary programing experience preferably in
Matlab and Python
Basic knowledge/ experience in optimization
Language Skills Fluency in German and English
Software Skills MATLAB / Simulink /Python
Other skills
Duration of the project up to six months (April – October)
Type of research project
Responsible Professor Drs. Umit Cali, Sukumar Kamalasadan
Supervisor/Mentor of the project
Supervisor`s Telephone Number 704-687-6038
Supervisor`s Email ucali@uncc.edu
Faculty, Institute or Company
Name
UNC Charlotte (partially in KIT)
4
2. Project Title: Development of emulated electromagnetic and mechanical
inertia inside the controller of a grid-tied PV inverter Energy Field Research Interest (please select from one of the options below)
Renewable Energy Devices and Integration
Abstract of the project A suite of localized, autonomous algorithms is to be
built on top of that emulated inertia of a solar
photovoltaic system, and will be steered by a mid-level
supervisory control layer. The grid forming and grid
support capability (such as voltage and frequency
support) of this design is to be demonstrated in
simulation, and in a scaled down lab experiment.
Interactions of experimental hardware with varied
distribution networks running on RTDS/Opal RT will be
carried out in hardware in the loop simulation runs.
Tasks Literature survey; distribution network simulation
model for control validation in Matlab; HIL formulation
and testing; writing reports/papers; making
presentations.
Requirements Must have B.S degree in Electrical Engineering with
concentration in power and energy.
Language Skills English
Software Skills Matlab, python, power analysis software (PowerWorld,
or DigSilent, or ETAP, or PSCAD, etc.)
Other skills Good communication skills
Duration of the project up to six months (April – October)
Type of research project Engineering study related to the power industry
Responsible Professor Dr. Badrul Chowdhury
Supervisor/Mentor of the project Dr. Chowdhury and his doctoral students
Supervisor`s Telephone Number 704-687-1960
Supervisor`s Email b.chowdhury@uncc.edu
Faculty, Institute or Company
Name
UNC-Charlotte
5
3. Project Title: Wideband Current Sensors for High Frequency Power
Electronics Applications Energy Field Research Interest (please select from one of the options below)
1. Power Conversion and Power Electronics
Abstract of the project The objective of this research is to investigate on
contactless integrated current sensing techniques
needed for next generation high frequency high
voltage power electronics systems. This project will
investigate on materials and implementation methods
that are responding to the magnetic field produced by
the carrying current in a printed circuit board trace.
This research will address the challenges of
measurements due to asymmetrical current
distribution and significantly non-uniform magnetic field
around the trace at frequencies beyond 1MHz. It is
expected that the student develops a detailed
simulation model for such solutions along with
hardware prototypes to verify the proposed methods.
Tasks It is expected that the student develops a detailed
simulation model for such solutions along with
hardware prototypes to verify the proposed methods.
Requirements Knowledge at least one of the following is required:
1. Familiarity of Multi-Physic simulation software
such as Comsol, HFSS, etc.
2. Knowledge of hardware experimentations and
basic power electronics circuits is essential.
3. Mixed-signal IC design or fabrication
Interested candidates are encouraged to contact Prof.
Babak Parkhideh (bparkhideh@uncc.edu) for an
interview. Please visit:
http://coefs.uncc.edu/bparkhid/research/ to know more
about our research projects
Language Skills Good
Software Skills Required, as mentioned in the requirements
Other skills Hardware-oriented person
6
Duration of the project up to six months (April – October)
Type of research project
Responsible Professor Dr. Babak Parkhideh
Supervisor/Mentor of the project Babak Parkhideh/
Shahriar Nibir, PhD Student, snibir@uncc.edu
Supervisor`s Telephone Number 704-687-1959
Supervisor`s Email bparkhideh@uncc.edu
Faculty, Institute or Company
Name
Electrical and Computer Engineering Department
Photovoltaic Integration Laboratory (PiL)
7
4. Predicting Impact of Thermal Energy Storage on German Power Market Energy Field Research Interest (please select from one of the options below)
Energy Storage and Energy Distribution
Abstract of the project Thermal energy storage is likely the most cost-
effective method to accommodate swings in output
from intermittent renewable energy power sources
(wind and solar) without curtailing or “spilling” that
power to other countries. Using data from the 2016
German Power compiled by the Fraunhofer Institute
for Solar Energy (https://www.energy-
charts.de/index.htm), an analysis will be carried out to
predict what the impact would be of adding various
amounts of the thermal energy storage at German coal
power plants. The goal will be to maximize the use in
Germany of power generated from renewable energy
sources while minimizing the operation of coal power
plants at part-load. The latter results in poorer thermal
efficiency and therefore higher CO2 emissions per
MWh. This project will require the creation of an
economic dispatch model for coal power plants. This
model will be used with the 2016 market data to
determine when it would have been more economic
for coal power plants to send energy to an energy
storage system rather than to sell power to the grid.
The model will also have to determine when the stored
energy should have been extracted in order to
minimize (or prevent) the operation of less efficient
and/or more expensive fossil power plants.
Tasks 1. Collection of data and background research on
thermal energy storage
2. Creation of economic dispatch model
3. Application of model to 2016 market data
4. Analysis of impact of adding varying amounts
of thermal energy storage
5. Reporting
Requirements A student from any engineering or physics-based
science program should be able to do this project.
The ability to create a computer program which can
process large amounts of data will be a key to success
in this project.
Language Skills English language skills will be required to interact with
the project advisors at UNCC
8
Software Skills The specific software platform to be used in this
analysis will be selected by the student.
Other skills An ability to independently carry out research will be
important to success. This includes the ability to dig
into available literature to find information which may
be necessary to carry out the analysis.
Duration of the project up to six months (April – October)
Type of research project Project for Mechanical Engineering Department
student
Responsible Professor Dr. Nenad Sarunac
Supervisor/Mentor of the project Nenad Sarunac / Jeffrey Phillips
Supervisor`s Telephone Number (704) 687-1089 / 704-595-2738
Supervisor`s Email nsarunac@uncc.edu / jphillip@epri.com
Faculty, Institute or Company
Name
Dr. Nenad Sarunac
EPIC Associate Professor of Mechanical Engineering
and Engineering Science
361 Duke Centennial Hall, UNCC, Charlotte, NC
28223
Dr. Jeffrey Phillips
Senior Program Manager, Electric Power Research
Institute, 1300 West WT Harris Blvd, Charlotte, NC
28262
9
5. Project Title: Optimal Energy Dispatch for Demand Response of Residential
PV-Battery Systems Energy Field Research Interest (please select from one of the options below)
3: Energy Storage and Energy Distribution
Abstract of the project The strategy of battery charging and discharging has a
great impact on the system performance such as
annualized cost, self-consumption, and peak shaving
for demand response. Previous studies usually
assume a simple control strategy. Under the simple
control strategy, the battery is charged whenever the
PV power generation is greater than the load
requirement and the battery is not full; the battery is
discharged whenever the PV power generation is less
than the load requirement and the state of charge of
battery is higher than the minimum. This simple control
strategy may not leads to the optimal solution with
respect to minimizing cost and maximizing grid
benefits. For example, it is desired to discharge the
battery during the peak hours instead of the off-peak
hours but this goal cannot be realized with the
conventional operation strategy. Thus, an optimal
dispatch strategy of the battery needs to account for 1)
the reduction of peak demand and thereby the
demand charge (if applicable) and 2) the increased
energy charge due to the roundtrip charge losses
battery. In this study, a model predictive control (MPC)
strategy will be developed to optimize the PV-battery
system operation for peak power reduction and cost.
The MPC strategy is based on the predicted electric
load consumption and the predicted PV power
generation, both depend on the weather forecasts.
This project will focus on the MPC strategy
development instead of the approaches for electric
load prediction and PV power prediction. Therefore,
the known load profiles will be used for the ideal load
prediction and the known weather profiles will be used
to derive the ideal PV power prediction.
Tasks Control algorithm development, implementation and
simulation. Documentation of research findings.
Requirements Preferable a Master student with interest and
background in PV-battery systems and controls
10
Language Skills Strong communication in English speaking and wiriting
Software Skills Proficient Matlab/Simulink
Other skills Knowledge of lithium-ion battery (preferred)
Duration of the project up to six months (April – October)
Type of research project Modeling and simulation
Responsible Professor Weimin Wang
Supervisor/Mentor of the project Weimin Wang
Supervisor`s Telephone Number 704-687-5066
Supervisor`s Email Weimin.wang@uncc.edu
Faculty, Institute or Company
Name
Weimin Wang, PhD
Faculty Engineering Technology Department
Associate - Energy Production and Infrastructure
Center
University of North Carolina - Charlotte
11
6. Project Title: Development of Nondestructive Techniques and Tools for In-
Service Condition Assessment of Timber Electrical Distribution Poles Energy Field Research Interest (please select from one of the options below)
Energy Storage and Energy Distribution
Abstract of the project The objective of this project is to explore low-cost and
rapid nondestructive evaluation (NDE) techniques for
condition assessment of timber electrical distribution
poles. The project proposed here builds on extensive
existing laboratory experimentation on full-scale
deteriorated timber poles and corresponding analytical
models to 1) develop prototypes of sensing hardware
and programmed embedded electronics for a routine
pole inspection tool; 2) perform field verification and
demonstration of the sensing hardware under a range
of operational conditions and environments; and 3)
analyze extensive laboratory and field test data to
facilitate the enhancement of the diagnostic
algorithms.
Tasks Project involves physical testing/data collection of
timber electrical distribution poles in the field and
potentially the laboratory. Signal processing
techniques and numerical models will be used to
correlate test data with the actual state of deterioration
in the poles to develop nondestructive assessment
techniques. Physical prototype systems for pole
condition assessment will also be designed,
fabricated, and programmed.
Requirements Must be able and willing to conduct laboratory and
field testing (must be in good physical condition and
willing to get dirty). Background in either structural
mechanics/dynamics, signal processing, or electrical
circuit design/fabrication/prototyping is necessary to be
able to offer contributions to the objective areas of this
project.
Language Skills Proficiency in English
Software Skills Familiarity with MATLAB; proficiency in C
programming language and familiarity with
microcontrollers is preferable
Other skills
Duration of the project April – October (6 Months)
Type of research project Applied Experimentation and Embedded Systems
Design/Development
Responsible Professor Matthew Whelan
12
Supervisor/Mentor of the project Matthew Whelan
Supervisor`s Telephone Number 704-687-1239
Supervisor`s Email M.Whelan.@uncc.edu
Faculty, Institute or Company
Name
University of North Carolina at Charlotte
13
7. Project Title: Fault Detection for Solid State Circuit Breakers
Energy Field Research Interest (please select from one of the options below)
Power Conversion and Power Electronics
Abstract of the project Solid-state circuit breakers (SSCB) is an emerging technology that could potentially change the way how power is distributed and managed in the buildings. One of EPIC’s affiliate members, Atom Power (www.atompower.com) has developed the world’s first truly solid-state circuit breaker for the commercial and industrial building markets. The Atom Switch has transitioned the circuit breaker from mechanical to digital in the intelligent, dynamic, and fastest circuit breaker ever. Instead interrupting current in milliseconds (ms) for traditional circuit breakers, the SSCB can stop the current in a few microsends (us). The ultrafast interruption speed also poses significant challenges in the fault detections and breaker coordination.
This project will investigate different fault detection and coordination methods for solid state circuit breakers, including high impedance fault, ground fault and arc fault. The project will also develop solid state breaker modeling for detection algorithm verification (in micro-sec range), and building system modeling in Opal-RT for breaker protection and impact study.
After completion of the project is of interest to create documentation of the algorithms, demonstrations and lab capabilities into a collaboration IEEE format paper to be presented. Student that select the project will be expected receive help from the mentors as well as from other graduate students working in power electronics group. The student will also have the chance to interact with the industry leaders directly on this emerging technology development.
Tasks 1. Identify SSCB fault detection and coordination
challenges.
2. Evaluate different fault detection and
coordination methods for solid state circuit
breakers, including high impedance fault,
ground fault and arc fault
3. Complete SSCB modeling and system
modeling for fault detection and impact study.
4. Support developing hardware prototype for
fault detection verification.
14
5. Summarize the findings in a presentation and
an IEEE format paper.
Requirements M.S. student in electrical engineering; familiarity with
principles of power electronics and power distribution,
familiarity with power electronic simulations.
Language Skills Strong oral and written communication skills.
Software Skills Matlab/Simulink or other power electronics simulation
software
Other skills Will prefer hands on experience but not required.
Duration of the project up to six months (April – October)
Type of research project Project for Electrical Engineering Department Student.
Responsible Professor Tiefu Zhao
Supervisor/Mentor of the project Tiefu Zhao (UNCC supervisor)
Ryan Kennedy, Denis Kouroussis (industry advisors)
Supervisor`s Telephone Number
704-687-0939
Supervisor`s Email Tiefu.Zhao@uncc.edu
Faculty, Institute or Company Name
Tiefu Zhao
Assistant Professor, Department of Electrical and
Computer Engineering
Associate, Energy Production and Infrastructure
Center (EPIC)
University of North Carolina at Charlotte
EPIC 1160, 8700 Phillips Rd, Charlotte, NC 28223
Tel: 704-687-0939
Email: Tiefu.Zhao@uncc.edu
15
8. Project Title: Evaluation of Instruments for Large-scale Metrology Energy Field Research Interest (please select from one of the options below)
Energy Equipment Manufacturing
Abstract of the project Equipment used for electricity generation at the utility
scale is physically large and expensive, and must be
manufactured with high precision in order to achieve
desired levels of efficiency and durability.
Components and equipment are typically much too
large and heavy to be able to move to dedicated
precision measurement instruments. Recent
advances in portable technologies for large-scale
metrology offer the opportunity for simultaneous
improvements in both productivity and quality in the
manufacture of this equipment. A wide range of
competing technologies have emerged to support
large-scale metrology, including laser trackers,
theodolites and total stations, laser radar, structured
light scanners, articulated-arm CMMs, etc. It is difficult
for manufacturing engineers to meaningfully compare
the various technologies to determine which is best
suited to a particular task or application. The goal of
the project is to design and conduct experiments
aimed at comparing the various technologies. A
reconfigurable artifact is currently being designed for
this purpose. It will be sized to be able to fit in the 3m
X 2m X 1.6m work volume of our large Leitz CMM,
which will provide a best estimate of the true value of
the dimensions and locations of various features.
Those same features will then be measured in various
environments and support conditions using different
instruments, and the results compared in terms of
accuracy, sensitivity to environmental conditions, time
and effort required, and other factors.
Tasks 1. Learn to operate multiple portable metrology
instruments.
2. Design and conduct measurement experiments.
3. Analyze data using appropriate software tools.
4. Summarize results and write report.
Requirements Mechanical Engineering student preferred. Strong
interest and experience in hands-on, experimental
16
work. Willingness to learn to operate new instruments
and software with minimal training.
Language Skills English required.
Software Skills Matlab, willingness to learn metrology software such
as Spatial Analyzer, GeoMagic, Polyworks, etc.
Other skills Interest in manufacturing
Duration of the project up to six months (April – October)
Type of research project Manufacturing technology, mechanical engineering.
Responsible Professor Edward Morse, John Ziegert
Supervisor/Mentor of the project Eward Morse, John Ziegert
Supervisor`s Telephone Number 704-687-8342, 704-687-8203
Supervisor`s Email emorse@uncc.edu, jziegert@uncc.edu
Faculty, Institute or Company
Name
Siemens Energy
top related