Fall 2021 Seminars

Speaker: Sarika Khushalani Solanki

Date: January 10th, 2022

Time: 5:00 PM - 6:00 PM

Place: Zoom

Abstract: Introduce the graduate seminar series and welcome students.

Speaker Bio: Biography: Sarika Khushalani Solanki received B.E. and M.E. degrees from India in 1998 and 2000 respectively. She received Ph.D. in Electrical and Computer Engineering from Mississippi State University, USA in 2006. She is currently an Associate Professor in Lane Department of Computer Science and Electrical Engineering at West Virginia University, Morgantown, WV, since August 2009. Prior to that, she worked for Open Systems International Inc, Minneapolis, MN as a Senior Engineer for three years. She has served as reviewer in National Science Foundation and Department of Energy and is past president of IEEE Distribution Systems Analysis Subcommittee and IEEE Career Promotion and Workforce Development Subcommittee and is editor of Transactions in Smart Grid. She is a recipient of Honda Fellowship award and NSF Career Award. Her research interests are Smart Grid, Power Distribution System, computer applications in power system analysis and power system control.

Speaker: Martin Dunlap

Date: January 24th, 2022

Time: 5:00 PM - 6:00 PM

Place: Zoom

Abstract: He will introduce the services and resources available through the WVU Libraries. These library resources may be critical to your graduate research.

Speaker Bio: He joined WVU in 1998 and has spent 10+ years working in the swamps of Florida as an environmental consultant. Since then he has worked in libraries first in Cleveland, Ohio and then here at WVU in various capacities. He recently got promoted to be the Engineering Librarian at WVU.

Speaker: WVU IT

Date: NA

Time: NA

Place: At your desk

Abstract: There is an online plagiarism tutorial at https://wvu.qualtrics.com/jfe/form/SV_6W3rGjsAaEenYgd

Here are the steps:
View videos.
Take a self-test.
Repeat steps for each module.
Take the Plagiarism Avoidance Test.

How do you progress through this tutorial?
View videos or read material in a module. Take a self-test after reading and viewing materials in a module. This self-test is for practice and taking it will open the next module. Repeat steps for each module, five modules in all. After viewing / reading the material in each module and taking the self-tests, take the Plagiarism Avoidance Test.

Speaker: Kyri Baker

Date: Monday, February 28, 2022

Time: 5:30 PM

Place: Online via Zoom. Please register here to get the attendance instructions.

Abstract:Evolving energy systems are introducing heightened levels of uncertainty and stress on the electric grid; fluctuating renewable sources, dynamic pricing, and flexible loads are transforming traditional power grid operations. Grid overvoltages and instabilities are increasing due to high penetrations of intermittent distributed generation, but stochastic optimization and predictive control can help hedge against these undesirable conditions. In this talk, I discuss how buildings can help provide these services, simultaneously assisting the grid while improving comfort and cost savings for building occupants. Optimization techniques will be presented that combine model predictive control, machine learning, and fast convex relaxations that allow the algorithms to be implemented on limited-computing platforms. These methods incorporate look-ahead forecasts of load, weather, and renewable availability, determining optimal setpoints under uncertain conditions. Various demand response applications will be discussed.

Bio:Dr. Kyri Baker received her B.S., M.S., and Ph.D. in Electrical and Computer Engineering from Carnegie Mellon University in 2009, 2010, and 2014, respectively. From 2015 to 2017, she worked at the National Renewable Energy Laboratory. Since Fall 2017, she has been an Assistant Professor at the University of Colorado Boulder and is a Fellow of the Renewable and Sustainable Energy Institute (RASEI). She received the NSF CAREER award in 2021 and led a top performing team in the ARPA-E Grid Optimization competition. She also received an Outstanding Associate Editor award for IEEE Transactions on Smart Grid in 2021. Her research focuses on computationally efficient optimization and learning algorithms for energy systems ranging from building-level assets to transmission grids.

Speaker: Daniel Molzahn

Date: Monday, March 28, 2022

Time: 5:00 PM

Place: Online via Zoom. Please register here to get the attendance instructions.

Abstract: Many optimization problems relevant to the design and operation of electric power systems are inherently nonlinear due to the AC power flow equations that model the relationships between the voltages and the power flows in power grids. The nonlinearity of the power flow equations results in a variety of algorithmic and theoretical challenges, including non-convex feasible spaces for optimization problems containing these equations. This presentation describes four categories of methods for addressing these challenges: 1) local optimization, 2) approximation, 3) convex relaxation, and 4) convex restriction. Local optimization methods search for an operating point that is superior to all nearby points. The practical applicability of local optimization methods has been demonstrated via results from the US Department of Energy’s Grid Optimization Competition, which compared algorithms for solving large-scale security-constrained AC optimal power flow problems. Approximations, convex relaxations, and convex restrictions simplify the power flow equations to obtain more tractable convex representations that are useful in a variety of applications. This presentation describes recent research on these methods and discusses several relevant applications.

Speaker Bio: Daniel Molzahn is an Assistant Professor in the School of Electrical and Computer Engineering and a Fellow of the Strategic Energy Institute at the Georgia Institute of Technology. He also holds an appointment as a computational engineer in the Energy Systems Division at Argonne National Laboratory, where he was previously a member of the research staff. He was a Dow Postdoctoral Fellow in Sustainability at the University of Michigan and received the B.S., M.S., and Ph.D. degrees in electrical engineering and the Masters of Public Affairs degree from the University of Wisconsin–Madison, where he was a National Science Foundation Graduate Research Fellow. He received the IEEE Power and Energy Society’s 2021 Outstanding Young Engineer Award for contributions to the theory and practical application of nonlinear optimization algorithms for electric power systems.

Speaker: Shrirang Abhyankar

Date: Tuesday, March 29, 2022

Time: 5:00 PM

Place: Online via Zoom. Please register here to get the attendance instructions.

Abstract: This talk introduces the Exascale Grid Optimization (ExaGO) package, an open-source library for solving large-scale alternating current optimal power flow (ACOPF) based problems including stochastic effects, security constraints and multi- period constraints. ExaGO can run on parallel distributed memory platforms, including massively parallel hardware accelerators such as graphical processing units (GPUs). We present the details of the ExaGO library including its architecture, formulations, modeling details, and its performance for several optimization applications.

Speaker Bio: Shrirang Abhyankar is a senior scientist with the Electricity Infrastructure and Buildings division at Pacific Northwest National Laboratory (PNNL). Prior to PNNL, he was with Argonne National Laboratory (ANL) working with the Mathematics and Computer Science and Energy Systems Division. He received M.S. and Ph.D in Electrical Engineering from Illinois Institute of Technology, Chicago. Dr. Abhyankar has contributed to various open-source projects including GridPACK, HELICS, PETSc/TAO, and MATPOWER.

Speaker: Robert Kabera

Date: Monday, April 11, 2022

Time: 5:00 PM

Place: Online via Zoom. Please register here to get the attendance instructions.

Abstract: Our predictive grid failure analytics tool visualizes vulnerabilities on the electric grid, ahead of time. In short, we do this by combining weather forecasts, smart vegetation tracking and looking at historical reliability data. Unlike other companies that mainly focus only on vegetation or weather, our unique approach here is we also look closely at long-term historical analysis of past incidents, outage duration and connected kVA as they relate to vegetation density. The risk we predict - weeks in advance - include: 1) the affected spans on the grid, 2) the likelihood of a power outage, 3) the number of expected incidents, 4) the number of affected customers, 5) the power outage duration, 6) the expected customer call volume, and 7) the most at-risk vegetation to causing a power outage. Combined, this foresight can reduce up to 70% customer downtime during an extreme weather power outage event. Our insights offer the following short term and long-term benefits to electric utilities, cooperatives, municipalities, insurance companies and cities: 1) Right away, companies are equipped to be proactive when it comes to extreme weather events preparedness & response. 2) Resiliency in terms of long term planning & simulations.

Speaker Bio: Robert is currently Founder, President & COO of Sync Energy AI, an energy AI company that allows energy and insurance professionals to run complex simulations in a no-code analytics environment. They specialize in predicting climate-related risks to critical infrastructure. They excel at visualizing disruptions to the electric grid network, weeks in advance of incidents. Robert Kabera was named to the 2018 Global US Forbes Under 30 List in the Energy Sector. Robert has previously worked as a Process Engineer at Chevron and in the utility scale solar energy group of Siemens.

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