Brookhaven National Laboratory Scientist Electrical Power Engineering in Upton, New York
Scientist Electrical Power Engineering
Job ID 2491 Date posted 03/10/2021
Brookhaven National Laboratory delivers discovery science and transformative technology to power and secure the nation's future. Primarily supported by the U.S. Department of Energy's (DOE) Office of Science, Brookhaven Lab is a multidisciplinary laboratory with seven Nobel Prize-winning discoveries, 37 R&D 100 Awards, and more than 70 years of pioneering research.
Brookhaven is operated and managed by Brookhaven Science Associates, which was founded by the Research Foundation for the State University of New York on behalf of Stony Brook University, and Battelle, a nonprofit applied science and technology organization.
The Interdisciplinary Science (IS) Department at Brookhaven National Laboratory (BNL) is seeking a Scientist with an Electrical Engineering and Data Analytics background and at least 3 years of experience to perform research in the areas of electric grid modernization and application of data analytics for grid planning and operation to improve grid reliability and resilience. The IS Department, in collaboration with others, is performing research in the areas of electric grid modernization and grid integration of renewable energy generation. The goal of our research is to contribute to the development of the next generation Smart Grid, including the application of innovative Smart Grid technologies that could enhance the performance, reliability and resilience of the distribution portion of the grid.This position is for a two-year appointment as a member of the BNL Scientific Staff assigned to the IS Department, reporting to the Renewables and Grid Analysis manager, Robert Lofaro.
Responsible for developing and performing independent new research projects related to the use of data analytics for enabling the next generation electric grid to realize the full potential of innovative new smart grid technologies, including smart sensors, to improve the performance, reliability and resilience of the grid.
Essential Duties and Responsibilities:
Develop and lead, with minimal supervision, sponsor funded research projects related to grid modernization.
Collaborate with other researchers in the IS department, as well as staff from other departments at BNL, including the Computer Science Initiative group to provide broad expertise for complex projects.
Conceptualize new grid research projects, develop and present project proposals to potential sponsors, and leading the performance of funded projects.
Technical activities will include modeling and analysis of electrical systems with integrated DER, application of data analytics and machine learning techniques to develop tools and techniques for enhanced grid planning and operation, review and analysis of operational data obtained from utility partners, and evaluation of innovative new technologies for applications to smart grids.
PhD in electrical engineering with focus on power systems and modeling and analysis of electrical networks.
Working knowledge of the electrical power grid, including both transmission and distribution system planning functions, operations, and restoration following outages, as well as the associated power grid energy markets and how they operate.
At least 3 years of experience in data analytics for application to planning and operation of the electric power grid to improve grid reliability and resilience.
Experience modeling electrical networks with integrated distributed energy resources (DER), such as solar, wind, grid-scale storage and load management functionality (e.g., demand-response)
Experience with one or more power system analytical software programs currently used in the power industry, such as PSCAD, SimPowerSystems, OpenDSS, CYME, PSSE , or hardware-in-loop (HIL) simulators such as RTDS and OPAL-RT
Demonstrated success or experience in developing and executing sponsor funded research programs, including concept development, proposal writing, budget preparation and project planning.
Preferred Knowledge, Skills and Abilities:
Candidates with existing sponsor relationships and funded grid research projects are preferred.Other Information:
The selected candidate will be placed at the appropriate level based on the depth and breadth of relevant knowledge and skills.
Brookhaven National Laboratory and the Energy and Photon Sciences Directorate are committed to your success. We offer a supportive work environment and the resources necessary for you to succeed.
At Brookhaven National Laboratory we believe that a comprehensive employee benefits program is an important and meaningful part of the compensation employees receive. Our benefits program includes, but is not limited to:
Medical, Dental, and Vision Care Plans
Flexible Spending Accounts
Paid Time-off and Leave Programs (vacation, holidays, sick leave, paid parental leave)
Lab-funded Retirement Plan
Flexible Work Arrangements
Tuition Assistance, Training and Professional Development Programs
Employee Fitness/Wellness & Recreation: Gym/Basketball Courts, Weight Room, Fitness Classes, Indoor Pool, Tennis Courts, Sports Clubs/Activities (Basketball, Ping Pong, Softball, Tennis)
Brookhaven National Laboratory (BNL) is an equal opportunity employer that values inclusion and diversity at our Lab.We are committed to ensuring that all qualified applicants receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, status as a veteran, disability or any other federal, state or local protected class.
BNL takes affirmative action in support of its policy and to advance in employment individuals who are minorities, women, protected veterans, and individuals with disabilities.We ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment.Please contact us to request accommodation.
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