NREL Postdoctoral Researcher - Hybrid Systems Controls and Optimization in Boulder, Colorado
Postdoctoral Researcher - Hybrid Systems Controls and Optimization
CO - Boulder
Postdoc (Fixed Term)
Hours Per Week
NREL is seeking a postdoctoral researcher to design and analyze hybrid power plants for the grid of the future. This will feature integration of technologies such as wind, solar, storage, and the grid.
The responsibilities of the researcher will be:
Develop novel optimization and control strategies for designing and operating hybrid systems.
Deploy large-scale strategies such as distributed optimization and controls to operate these plants in real-time or optimize over a large number of design variables.
Use a variety of simulation tools including WISDEM (Wind-Plant Integrated Systems Design and Engineering Model), SAM (System Advisory Model), and OpenDSS (an electric power distribution system simulator).
Work with a variety of customers including the US Department of Energy wind energy technology office.
Work collaboratively with other national laboratories, industry and the international community and execute wind energy related engineering projects worldwide.
Assist publishing results in technical journals/conference proceedings and present work at conferences, symposia, and sponsor review meetings and will also be expected to support the development of new work proposals, preparations, and reviews.
This researcher is expected to demonstrate a broad understanding and wide application of engineering principles, theories and concepts as well as general knowledge of wind energy related disciplines and applications and will have excellent writing, interpersonal and communication skills.
Must be a recent PhD graduate within the last three years.
The preferred candidate will have experience with hybrid energy system design and multi-disciplinary optimization; energy modeling tools used within the wind industry e.g. WISDEM, SAM, OpenDSS, and have experience with the FORTRAN, C++ and Python programming languages; comfortable working in high performance computing environments and will be familiar with distributed optimization and controls.
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