Power System Optimization Research Intern

Hitachi

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profile Job Location:

Raleigh, WV - USA

profile Monthly Salary: Not Disclosed
Posted on: 11 hours ago
Vacancies: 1 Vacancy

Job Summary

Location:

Raleigh North Carolina United States

Job ID:

R0113868

Date Posted:

Company Name:

HITACHI ENERGY USA INC

Profession (Job Category):

Administration & Facilities

Job Schedule:

Full time

Remote:

No

Job Description:

Power System Optimization Research Intern

Hitachi Energy is a pioneering technology leader that is helping to increase access to affordable reliable sustainable and modern energy for all. We keep your lights on the factories running our hospitals and schools open. What we deliver is used almost universally with more than three quarters of the worlds population positively impacted by what we do. Founded on 100 years of engineering heritage and enriched by diversity we balance social environmental and economic values for a sustainable society. We employ more than 40000 people in more than 90 countries.

Responsibilities:

  • Perform literature survey and review to explore state-of-the-art topics that fall within the scope of power systems and distribution system optimization.
  • Simulate current and future distribution grid scenarios including emerging technologies (e.g. energy storage electro-mobility etc.)
  • Develop and implement models using linear programming (LP) nonlinear programming (NLP) mixed-integer linear programming (MILP) mixed-integer nonlinear programming (MINLP).
  • Develop novel and innovative solutions with particular emphasis on data analytics optimization machine learning probabilistic modeling and graph-based methods.
  • Develop proof-of-concept experiment/simulation setups for validating the proposed methodology using detailed case studies.
  • Collaborate with the research scientists within Hitachi Energy Research.
  • Prepare technical reports and presentations on work accomplished during internship and/or publications in peer-reviewed conference/journal.

Your Background:

  • Currently enrolled in the Ph.D. program in Electrical and Computer Engineering or Industrial Systems Engineering/Operations Research at an accredited university in the US. Excellent senior-year masters students with relevant experience are also welcome to apply.
  • Conceptual understanding of power system operations and market-based systems.
  • Working knowledge of power system concepts such as outage management state estimation power flow and/or optimal power flow.
  • Expertise in optimization techniques and tools (LP MILP NLP MINLP) and convex optimization.
  • Prior experience with distribution network modeling/power flow/DC-OPF/AC-OPF/state estimation is beneficial.
  • Familiar with power system automation.
  • Experience with Machine Learning Deep Neural Networks or Graph Neural Networks is a plus.
  • Comfortable with programming in either Python or C/C.
  • Excellent spoken and written communication skills in English.
  • Capable of carrying out independent work and able to communicate effectively in a team.

Equal Employment Opportunity (EEO)-Females/Minorities/Protected Veterans/Individuals with Disabilities

Protected veterans and qualified individuals with a disability may request a reasonable accommodation if you are unable or limited in your ability to use or access the Hitachi Energy career site as a result of your disability. You may request reasonable accommodations by completing a general inquiry form on our website. Please include your contact information and specific details about your required accommodation to support you during the job application process.

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Required Experience:

Intern

Location:Raleigh North Carolina United StatesJob ID: R0113868Date Posted:Company Name:HITACHI ENERGY USA INCProfession (Job Category):Administration & FacilitiesJob Schedule:Full timeRemote:NoJob Description:Power System Optimization Research InternHitachi Energy is a pioneering technology leader th...
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Key Skills

  • Robotics
  • Machine Learning
  • Python
  • AI
  • C/C++
  • Data Collection
  • Research Experience
  • Signal Processing
  • Natural Language Processing
  • Computer Vision
  • Deep Learning
  • Tensorflow

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