The successful candidate will work towards the development of scalable, distributed state-estimation, forecasting, and system identification algorithms for power systems with high penetration of distributed energy sources. The candidate will also work towards development of power system and its sensor network optimization, system estimation and identification using data driven technologies, energy resource and load forecasting and disaggregation. He will be part of the Sensing and Predictive Analytics group under the Power Systems Engineering Center (PSEC) at NREL. PSEC supports the science and technology goals of the U.S. Department of Energy and NREL toward a sustainable energy future. The center works with the electricity industry to optimize strategies for effectively interconnecting renewable resources and emerging energy efficiency technologies in the existing electric power system. The center focuses on resolving grid integration barriers and providing improved control and management strategies for increased grid flexibility, consumer empowerment, and transportation electrification.
Required Education, Experience, and Skills
Relevant PhD . Or, relevant Master’s Degree and 3 or more years of experience . Or, relevant Bachelor’s Degree and 5 or more years of experience . Demonstrates broad understanding and wide application of engineering technical procedures, principles, theories and concepts in the field. General knowledge of other related disciplines. Demonstrates leadership in one or more areas of team, task or project lead responsibilities. Demonstrated experience in management of projects. Very good writing, interpersonal and communication skills.
Ideal candidates will have a background and expertise in one or more of the following topics:
- Measurement-based approach to model, predict and control large-scale power grid
- Machine learning
- Convex and nonconvex optimization
- Distributed solution methods for convex and/or nonconvex programs
- Familiarity with latest findings in state estimation and forecasting within the context of power systems and renewable generation
- Demonstrates broad understanding and wide application of principles, theories, and concepts in operations, controls, and optimization of power systems areas
- General knowledge of other related disciplines
- Knowledge of communication protocols used in power systems
- Proficiency in one or more of the following programming languages: Python, Julia, Java, C, C++, C#
- Proficiency in one or more of the following power system analysis tools: PSS/E and PSLF, DSA Tools, PSCAD, PowerWorld, Digsilent, EMTP, and RTDS
- Term Entry +
- Company NREL