Title: Maintaining Reliability and Resiliency while Decarbonizing the Power Grid Abstract: The world has focused strongly, through the Paris Accords, on ridding the electricity generation mix of fossil fuels and replacing that with sustainable non-carbon resources. The emerging new generation mix, however, is changing the characteristics of the grid thus requiring the modification of the ways we […]
Click here for the poster. Topics that will be covered in the workshop: Overview of Photovoltaic and Wind Generations Converter Controls for Renewables Grid Connection Requirements Impact of Renewables on Fault Analysis and Protection Impact of Renewables on System Stability Training on Renewable Modelling in PSCAD AC Microgrids DC Microgrids Case Studies The list of […]
Title: On Plug-and-Play Regularization using Linear Denoisers. Degree Registered: PhD Guide: Prof Kunal Narayan Chaudhury Date: Jan 2, 2023. Time: 11:00 am. Venue: Online. MS Teams: https://tinyurl.com/bdz95wmw (meeting ID: 483 231 041 151; Passcode: QDF8WS) Abstract: The problem of inverting a given measurement model comes up in several computational imaging applications. For example, in CT […]
Department of Electrical Engineering, Indian Institute of Science and IEEE Signal Processing Society, Bangalore Chapter cordially invite you to a lecture on Advances in imaging and segmentation of thalamic nuclei with applications by Prof. Manoj Saranathan, Professor of Radiology at UMass Chan Medical School in Worcester, Massachusetts Date and time: January 2, 2023, 4 PM […]
Title: Emulator-based Microgrid studies vis a vis Some Indian Renewable interconnected Microgrids. Time: 10 am 6/1/23 Venue: EE MMCR Abstract: Mini / Micro Grid in Stand Alone or Grid integrated forms are coming up very fast in the conventional power system. Many a time, these are renewable sources integrated. Design considerations, Plant automation, Remote monitoring and O & M strategies […]
Department of Electrical Engineering, Indian Institute of Science and IEEE Signal Processing Society, Bangalore Chapter cordially invite you to a lecture on Proper Definition of Dirichlet Conditions and Convergence of Fourier Representations By Prof. Anubha Gupta Indraprastha Institute of Information Technology -Delhi Date and time: January 11, 2023, 5 PM Venue: Multimedia Classroom, Department of Electrical Engineering (EE), IISc. […]
Thesis Title: Pulse Width Modulation Techniques of Inverter Fed Split-Phase Machine Drive in Linear and Overmodulation Regions Degree registered: PhD Guide: Prof. Kaushik Basu Date and Time: 12th January 2023, 03:00 PM Place: MMCR EE, Meeting Link: Teams Meeting Link Multi-phase machines (MPMs) have more than three windings in their stator, rotor, or both. With the broader […]
Venue: MMCR, EE Time: 4pm, 20 January 2023 Abstract:Silicon Carbide MOSFETs (SiC MOSFETs) fall into wide band gap (WBG) power devices. These devices are commercially available in the voltage range of 600-3300V and compete with the state-of-the-art Si-insulated gate bipolar junction transistors (IGBTs). Superior material properties of SiC MOSFET lead to smaller die sizes. This […]
Title of Thesis: Experimental and Theoretical Investigations on High Voltage Polymeric Insulators. Research Supervisor: Subba Reddy B Date and Time: Tuesday 24th Jan 2023, 11am Venue: ON Line: Meeting link: Abstract High Voltage Ceramic and glass Insulators have been widely used by various transmission and distribution utilities for several decades across the globe. Recently composite or silicone […]
Advisors: Prof. Chandra Sekhar Seelamantula (EE) & Prof. Supratim Ray (CNS) Examiner: Prof. Vikram M. Gadre (EE), IIT Bombay Title of the thesis: Learning Filters, Filterbanks, Wavelets, and Multiscale Representations Date & Time: January 25, 2023; 11:00 AM onward (Coffee will be served during the defense) Venue: Multimedia Classroom (MMCR), Department of Electrical Engineering, IISc Abstract: […]
Speaker: Prof. P.S. Sastry, Dept of Electrical Engineering, Indian Institute of Science Abstract: Supervised learning of classifiers is widely used in many applications of AI/ML. The deep networks used in such applications today need a large training set. Creating a labelled data set where one can have high confidence in the labels is both expensive […]