Power System Optimization Research Intern

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 world's 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 40,000 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.

• 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 master's 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.