Projects available at UNC Charlotte

Transcription

1 Projects available at UNC Charlotte 1. Project Title: Novel Peer to Peer (P2P) Energy Trading Applications using Advance Data Analytics Project Title: Development of emulated electromagnetic and mechanical inertia inside the controller of a grid-tied PV inverter Project Title: Wideband Current Sensors for High Frequency Power Electronics Applications Predicting Impact of Thermal Energy Storage on German Power Market Project Title: Optimal Energy Dispatch for Demand Response of Residential PV-Battery Systems Project Title: Development of Nondestructive Techniques and Tools for In-Service Condition Assessment of Timber Electrical Distribution Poles Project Title: Fault Detection for Solid State Circuit Breakers Project Title: Evaluation of Instruments for Large-scale Metrology

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 multimodel 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 2

3 Tasks Requirements Language Skills Software Skills algorithm and implementation of the peer to peer neighborhood trading scenario to IEEE bus bar systems in Simulink and RT lab (HIL) environment. 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. Fundamental knowledge about the power markets Basic knowledge about smart grids Preliminary programing experience preferably in Matlab and Python Basic knowledge/ experience in optimization Fluency in German and English 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 Supervisor`s Faculty, Institute or Company Name ucali@uncc.edu UNC Charlotte (partially in KIT) 3

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 Tasks Requirements Language Skills Software Skills Other skills Duration of the project Type of research project Responsible Professor Supervisor/Mentor 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. Literature survey; distribution network simulation model for control validation in Matlab; HIL formulation and testing; writing reports/papers; making presentations. Must have B.S degree in Electrical Engineering with concentration in power and energy. English Matlab, python, power analysis software (PowerWorld, or DigSilent, or ETAP, or PSCAD, etc.) Good communication skills up to six months (April October) Engineering study related to the power industry Dr. Badrul Chowdhury Dr. Chowdhury and his doctoral students Supervisor`s Telephone Number Supervisor`s Faculty, Institute or Company Name b.chowdhury@uncc.edu UNC-Charlotte 4

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 Tasks Requirements 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. It is expected that the student develops a detailed simulation model for such solutions along with hardware prototypes to verify the proposed methods. 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: to know more about our research projects Language Skills Software Skills Other skills Good Required, as mentioned in the requirements Hardware-oriented person 5

6 Duration of the project up to six months (April October) Type of research project Responsible Professor Supervisor/Mentor of the project Dr. Babak Parkhideh Babak Parkhideh/ Supervisor`s Telephone Number Shahriar Nibir, PhD Student, Supervisor`s Faculty, Institute or Company Name Electrical and Computer Engineering Department Photovoltaic Integration Laboratory (PiL) 6

7 4. Predicting Impact of Thermal Energy Storage on German Power Market Energy Field Research Interest Energy Storage and Energy Distribution (please select from one of the options below) Abstract of the project Tasks Requirements Language Skills Thermal energy storage is likely the most costeffective 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 ( 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 CO 2 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. 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 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. English language skills will be required to interact with the project advisors at UNCC 7

8 Software Skills Other skills Duration of the project Type of research project Responsible Professor Supervisor/Mentor of the project The specific software platform to be used in this analysis will be selected by the student. 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. up to six months (April October) Project for Mechanical Engineering Department student Dr. Nenad Sarunac Nenad Sarunac / Jeffrey Phillips Supervisor`s Telephone Number (704) / Supervisor`s Faculty, Institute or Company Name nsarunac@uncc.edu / jphillip@epri.com Dr. Nenad Sarunac EPIC Associate Professor of Mechanical Engineering and Engineering Science 361 Duke Centennial Hall, UNCC, Charlotte, NC Dr. Jeffrey Phillips Senior Program Manager, Electric Power Research Institute, 1300 West WT Harris Blvd, Charlotte, NC

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 Tasks Requirements 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. Control algorithm development, implementation and simulation. Documentation of research findings. Preferable a Master student with interest and background in PV-battery systems and controls 9

10 Language Skills Software Skills Other skills Duration of the project Type of research project Responsible Professor Supervisor/Mentor of the project Strong communication in English speaking and wiriting Proficient Matlab/Simulink Knowledge of lithium-ion battery (preferred) up to six months (April October) Modeling and simulation Weimin Wang Weimin Wang Supervisor`s Telephone Number Supervisor`s Faculty, Institute or Company Name Weimin Wang, PhD Faculty Engineering Technology Department Associate - Energy Production and Infrastructure Center University of North Carolina - Charlotte 10

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) Abstract of the project Tasks Requirements Language Skills Software Skills Other skills Duration of the project Type of research project Responsible Professor Energy Storage and Energy Distribution 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. 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. 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. Proficiency in English Familiarity with MATLAB; proficiency in C programming language and familiarity with microcontrollers is preferable April October (6 Months) Applied Experimentation and Embedded Systems Design/Development Matthew Whelan 11

12 Supervisor/Mentor of the project Matthew Whelan Supervisor`s Telephone Number Supervisor`s Faculty, Institute or Company University of North Carolina at Charlotte Name 12

13 7. Project Title: Fault Detection for Solid State Circuit Breakers Energy Field Research Interest (please select from one of the options below) Abstract of the project Power Conversion and Power Electronics 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 ( 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 microsec range), and building system modeling in Opal-RT for breaker protection and impact study. Tasks 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. 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. 13

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 Supervisor`s Tiefu.Zhao@uncc.edu Faculty, Institute or Company Tiefu Zhao Name 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 Tel: Tiefu.Zhao@uncc.edu 14

15 8. Project Title: Evaluation of Instruments for Large-scale Metrology Energy Field Research Interest Energy Equipment Manufacturing (please select from one of the options below) Abstract of the project Tasks 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. 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 15

16 work. Willingness to learn to operate new instruments and software with minimal training. Language Skills Software Skills Other skills Duration of the project Type of research project Responsible Professor Supervisor/Mentor of the project English required. Matlab, willingness to learn metrology software such as Spatial Analyzer, GeoMagic, Polyworks, etc. Interest in manufacturing up to six months (April October) Manufacturing technology, mechanical engineering. Edward Morse, John Ziegert Eward Morse, John Ziegert Supervisor`s Telephone Number , Supervisor`s Faculty, Institute or Company Name Siemens Energy 16