Ying Huang
North Dakota State University, ND·Engineering
Power grids and other energy systems have to keep running through blizzards, floods, droughts and cyberattacks. When they fail, communities lose heat, water and money.
- Fields
Engineering
Earth & Environmental Science
Computer Science
- Topics
energy resilience
power systems
grid reliability
- Grants
- 1 known grant, through Feb 2027
What they work on
- Identify key risks to North Dakota's energy systems from extreme weather and cyber threats, and assess statewide research capacity and gaps, through capacity assessments and scenario development.
- Define priority research areas linking physical, energy-water and cyber resilience, drawing on interdependent energy system modeling, artificial intelligence, data-driven analysis, risk assessment and resilience optimization.
- Build a statewide collaboration among five North Dakota institutions, industry and communities, guided by advisory committees, to design the scope and coordination of a future E-RISE research initiative and an energy workforce plan.
More about the research
North Dakota's energy sector faces all of these risks. This planning project lays the groundwork for a larger statewide research and education effort. That effort would make the state's energy systems more resilient, able to withstand and recover from disruptions, and more reliable.
Why it matters
Extreme weather and cyber threats can knock out energy systems and cause large economic losses. By mapping risks and setting research priorities for physical, water-related and cyber resilience, this planning work could lead to more reliable energy infrastructure for communities across all North Dakota counties. It could also offer insights that other states can use.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Kwanghee Won
South Dakota State University, SD·Engineering
Develop a strategy to restore power across multiple connected microgrids after extreme weather, putting critical community and household loads first, using a multi-timescale predictive control and estimation framework with grid-forming (GFM) inverters.
Qinghua Li
University of Arkansas, AR·Computer Science
Develop methods to assess the risk of security vulnerabilities in energy system operational technology and choose the most effective ways to mitigate them, including lowering the cost and risk of patching.
Di Shi
New Mexico State University, NM·Engineering
Model multi-scale climate dynamics, including flooding, drought and temperature extremes, and link them to sociodemographic energy maps of three rural communities.
The school
North Dakota State University: 4 labs on PI Pages, $200M a year on research, 129 research doctorates a year.
Reach out
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