Consortium of Hybrid Resilient Energy Systems (CHRES)
The CHRES program provides summer internship opportunities to undergraduates, doctoral students, and faculty from four Hispanic-Serving Institutions:
Universidad Ana G Méndez-Gurabo
Universidad de Puerto Rico-Mayaguez
University of Texas-El Paso
University of New Mexico-Albuquerque
The expected outcome of the research opportunities is to build a sustainable professional and academic pipeline of next generation engineers and scientists who are ready to take on the challenges of current and future energy systems.
At NETL, candidates don’t need experience; that’s what we’re here for! You will be assigned a mentor who will educate and guide you throughout your summer appointment. You will be part of a multi-cultural team who truly cares about you and your success. They are passionate about teaching the next generation of STEM professionals and increasing diversity and inclusion at NETL. You will have access to world class researchers and scientists; use one-of-a-kind equipment and facilities; collaborate with subject matter experts and professionals in your field; author/co-author papers, presentations, and other publication materials; attend/present at conferences and workshops.
CHRES Internship Opportunities
When: Application deadline: January 31, 2023 (Program Dates: June 5, 2023 to August 11, 2023) Where: National Energy Technology Laboratory in Morgantown, WV; Albany, OR; Pittsburgh, PA Financial Benefits: Stipend based on academic level; housing & travel allowance.
Be a full-time regular permanent faculty member at one of the four universities listed above with a research interest in NETL core R&D areas
Be at least 18 years of age at the time of appointment
Provide proof of coverage under a health insurance plan prior to the beginning of the internship
Sabbatical appointment candidates must include a statement describing the financial arrangements with their academic institution, including fringe benefits paid by the institution (state as a percentage of salary and itemize)
Experience with MATLAB-Simulink programming, thermodynamics, middleware interface, and/or dynamic controls is a plus. Please include on your resume and application.
NETL's Hybrid Performance (HYPER) facility is a one-of-a-kind facility built to evaluate dynamicoperations and to develop control strategies for solid oxide fuel cell / gas turbine (SOFC-GT) hybrids, with expanded reconfigurability and capability. To exploit the advantage of both numerical models and physical systems, as well as gapping the inaccessible technologies, a cyber-physical system (CPS) approach was implemented at the HYPER facility. A CPS fuel cell system was built and integrated with turbomachinery and other supporting components in real time, forming a pilot-scale SOFC-GT integrated system. NETL's HYPER team is seeking researchers for projects in the following areas:
Fuel Processing and Fuel Flexibility Mentors: Larry Shadle, Farida Harun
One particular research interest of the HYPER project is to explore the capability of this hybrid technology under a fuel flexible environment. A one-dimension reformer was built and implemented with the SOFC model in the dSPACE platform. This project will engage in a fuel flexibility modeling study to determine the impact of an array of secondary fuels on SOFC-GT cycle efficiency, and to identify key performance and cost drivers.
Fuel Cell Degradation Mentors: Jose Colon, Nana Zhou, David Tucker
Fuel cell stack degradation has a big impact on facility costs and operations. This project will use additional experimental data to optimize the HYPER project’s existing degradation model, with the expectation to test the control strategy (all the controllers simultaneously) on the HYPER facility. The project will also include characterizing of the system in a broad range of operating conditions while the cell is degrading.
System Analysis Mentors: Danylo Oryshchyn, Biao Zhang, Jose Colon
A novel cycle, composed of a solid oxide electrolyzer cell (SOEC), a solid oxide fuel cell (SOFC), an internal combustion engine (ICE), thermal management, and carbon capture technologies is proposed. This cycle aims to investigate the efficient and cost-effective production of hydrogen and electricity. System studies will be performed for cycle optimization to improve lifespan, efficiency, costs, and operability.
Mitigating Compressor Surge and Stall Mentors: Larry Shadle, David Tucker
Compressor surge and stall is one of the main operational challenges in SOFC-GT hybrid systems. The problem arises because of the added large volume between compressor and gas turbine and resultant changes to system fluid dynamics. This project will focus on examining several methods for detecting and mitigating compressor surge and stall during transient operation. The compressor stall and surge and its recovery will be characterized at different transient states in the SOFC-GT hybrid system. Acoustic measurements will be used to detect or confirm the onset of compressor stall and surge. An automated compressor surge recovery will be demonstrated using a cold air bypass strategy at nominal speed and for emergency shutdown.
Integration of Energy Storage into Hybrid Power Cycles Mentors: Farida Harun, David Tucker
The aim of this project is to evaluate the potential for energy storage in hybrid power cycles to enable more effective load following. This will build upon the analysis conducted previously that included both renewables and SOFC-GT hybrids. Energy storage concepts will be simulated and virtually integrated into hybrid cycles. They will be tested for their ability to provide flexibility and resiliency in power systems which have a high proportion of variable renewable power sources, such as wind and solar.
Performance Degradation and On-Line System Identification Mentors: David Tucker, Larry Shadle
It is clear from previous work that an adaptive control approach will be required for highly coupled advanced power systems as components degrade to maintain performance targets. As part of the HYPER project, single-input single-output controllers have been designed to regulate variables that directly affect component degradation in a hybrid system. The project goal is to improve performance and extend power system component lifespan using advanced controls and artificial intelligence. NETL researchers are developing an innovative continuous monitoring system to characterize drift from optimal performance by conducting on-line system identification. During this project, degradation of specific components will be characterized using the on-line system identification at nominal and off-design conditions.
Developing Cyber-Physical Reformer Mentors: Jose Colon, Farida Harun
NETL researchers have pioneered the cyber physical approach to enable rapid evaluation of a variety of operational configurations while maintaining the accuracy of process dynamics. A cyber-physical reformer incorporates real-time models, experimental hardware, and dynamic data transfer and control. Tests will be planned, conducted, and analyzed to verify dynamic models and evaluate the process limitations of extracting the heat from either auto-thermal reforming, heat exchange in turbine exhaust, or from the SOFC itself.
Automated Startup and Shutdown of SOFC-GT Hybrid System Mentors: David Tucker, Nana Zhou
One inherent complexity of the SOFC-GT hybrid system comes from wide discrepancies in the individual component response times, affecting the startup and shutdown of the hybrid system critical dynamic operations. For turbomachinery, this will involve avoiding compressor surge and stall. For the fuel cell system, it will require the thermal management and electrochemical light-off. This project will analyze previous system identification data and develop and demonstrate an automated dynamic control within the constraints of the supervisory control.
Load Following and Supervisory Control Mentors: David Tucker, Biao Zhang
The penetration of renewables requires other power plants to have a rapid load following. This project will investigate the SOFC-GT’s load following ability by operating the HYPER facility in response to Idaho National Lab’s grid simulator demand. A supervisory control scheme for load will be developed. The objective is to divide power generation between the fuel cell and the turbine during power demand changes, i.e., responding faster with the gas turbine and then adjusting the fuel cell load over time, while avoiding excessive temperature oscillation in the fuel cell. Temperature variation represents a constraint in the control problem.
Machine Learning and Digital Twin Mentors: Larry Shadle, David Tucker
Cyber-physical modeling provides a new modeling paradigm that has the potential to accelerate the design, deployment, and scale-up of advanced energy systems. Cyber-physical models can grow and change during the design and deployment process, and ultimately support development of the digital twin and the physical system of the embodied power plant. This project will use HYPER facility and operational data for machine learning and digital twin research.