Gayathri Krishnamoorthy

Gayathri Krishnamoorthy

Researcher II-Electrical Engineering


303-384-7783

Gayathri Krishnamoorthy is a researcher in the Transmission & Distribution Interactions Group within the Grid Planning and Analysis Center at NREL. She has 6+ years’ experience working on power distribution grid modeling, simulation, and analysis tools, and has an extensive background in developing various optimization models for distributed battery energy storage participation in regulation markets. In her spare time, Gayathri practices yoga, dance, and painting. She is also passionate about tech journalism and the brain science behind mindfulness practices.

Research Interests

Clean energy integration studies (large scale transmission and distribution cosimulation, DER impact assessment, long-duration battery energy storage design, ancillary services, regulation market, synthetic network model development)

Artificial intelligence for the power grid (identifying synergies in power grid model based optimization and data driven optimization using deep neural networks)

Education

Ph.D., Electrical Engineering and Computer Science, Washington State University

M.S., Electrical and Computer Engineering, Washington State University

B.E., Electronics and Communications Engineering, Anna University, India

Professional Experience

Graduate Research Assistant, Washington State University (2016–2022)

Outreach Coordinator, National GradSWE DEI (2021–2022)

Columnist at The Daily Evergreen, Washington State University (2020–2022)

Secretary at GradSWE, Washington State University (2020–2021)

DOE NSIP Intern, Pacific Northwest National Laboratory (2018, 2020)

Associations and Memberships

Member, Institute of Electrical and Electronics Engineer (IEEE)

Professional Member, Society of Women Engineers (SWE)

Featured Work

An Open-source Environment for Reinforcement Learning in Power Distribution Systems, IEEE Power & Energy Society (PESGM) (2022)

Reinforcement Learning for Battery Energy Storage Dispatch Augmented with Model-Based Optimizer, IEEE SmartGridComm (2021)

Iteratively-Coupled Co-Simulation Framework for Unbalanced Transmission-Distribution System, IEEE Milan PowerTech (2019)

Transmission–Distribution Cosimulation: Analytical Methods for Iterative Coupling, IEEE Systems Journal (2019)

Bilateral Electricity Market in a Distribution System Environment, IEEE Transactions on Smart Grid (2019)

Awards and Honors

Best Conference Paper Presentation at IEEE PESGM (2022)

3-minute Thesis Competition Winner, Washington State University (2020)

Graduate and Professional Student Association Scholarship (2019)

Best Student Paper Award at NAPS (2018)


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