Requisition Id6414

Overview:

Oak Ridge National Laboratory is the largest US Department of Energy science and energy laboratory, conducting basic and applied research to deliver transformative solutions to compelling problems in energy and security.

We are seeking a Postdoctoral Research Associate who will support the Grid-interactive Controls (GIC) Group in the Electrification and Energy Infrastructure Division (EEID) within the Energy Science and Technology Directorate (ESTD) at Oak Ridge National Laboratory (ORNL) to perform R&D related to data-driven modeling and B2G co-simulation.

The GIC group leads the cross-disciplinary R&D to deliver innovative, multi-disciplinary grid-interactive control solutions to advancing the reliable, resilient, secure and affordable integration of demand-side flexibilities into the U.S. electric grid for providing various grid services essential to operational reliability and resilience.

This position will focus on the data-driven modeling and simulation of inverter-based resources (IBRs) and variable loads (VLs) both individually and in aggregation. It helps address the R&D challenges in deriving more accurate transient and dynamic distribution grid models to evaluate and support the solar grid integration. Selection will be based on qualifications, relevant experience, skills, and education. The successful candidate should be highly self-motivated and independent in conducting research under general guidance, and is expected to prepare manuscripts for scientific publication and present the work to clients and at conferences.

Major Duties/Responsibilities:

• Develop and validate data-driven black-box modeling methods for large distribution-connected IBRs


• Develop data-driven mechanical torque representation for direct-connected and inverter-driven motors associated with behind-the-meter (BTM) building loads under both normal and abnormal operations


• Develop and validate data-driven gray-box aggregated models to accurately characterize the dynamic response of a variety of residential/commercial building loas


• Integrate data-driven models into GridLAB-D for integrated distribution system transient and dynamic simulation

Basic Qualifications:

• A PhD in Electrical Engineering or a related field completed within the last 5 years


• Deep understanding of power electronics and control, electric machinery, and motor drive


• Strong expertise in machine learning, data science and statistics


• Extensive working experiences in C++, Fortran and Python coding

Preferred Qualifications:

• Expertise in single-/three-phase inverter models with grid-forming/grid-following and VSG controls


• Expertise in distribution system modeling and simulation


• Expertise in building load modeling and building-to-grid integration


• Experience in Modelica, GridLAB-D, MATLAB (Simulink, Simscape, system identification, etc.) and/or PSCAD


• Excellent written and oral communication skills


• Motivated self-starter with the ability to work independently and to participate creatively in collaborative teams across the laboratory


• Ability to function well in a fast-paced research environment, set priorities to accomplish multiple tasks within deadlines, and adapt to ever changing needs

Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before starting their appointment. The appointment length will be for up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and the availability of funding.

Moving can be overwhelming and expensive. UT-Battelle offers a generous relocation package to ease the transition process. Domestic and international relocation assistance is available for certain positions. If invited to interview, be sure to ask your Recruiter (Talent Acquisition Partner) for details.

For more information about our benefits, working here, and living here, visit the "About" tab atjobs.ornl.gov.

This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired.

We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted and the candidates submitted will not be considered for employment.

If you have trouble applying for a position, please email ORNLRecruiting@ornl.gov.

ORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply. UT-Battelle is an E-Verify employer.