Collaborative Research: Dynamic Grid Optimization under High Renewable Penetration: Multis — NSF Award to Iowa State University (I
Growth of renewable energy leads to new challenges for electric power grid planning and operation. Many renewable energy resources, such as solar and wind, heavily depend on the weather conditions that are inherently uncertain. Such uncertainty is usually revealed progressively over time. Consequently, the grid plannin
| Award title | Collaborative Research: Dynamic Grid Optimization under High Renewable Penetration: Multis |
|---|---|
| Award ID | 2523935 |
| Awardee | Iowa State University |
| City | AMES |
| State | IA |
| Amount obligated | $150,000 |
| Principal investigator | Bai Cui |
| Program | AMPS-Algorithms for Modern Pow, OFFICE OF MULTIDISCIPLINARY AC |
| Start date | 09/15/2025 |
| Abstract | Growth of renewable energy leads to new challenges for electric power grid planning and operation. Many renewable energy resources, such as solar and wind, heavily depend on the weather conditions that are inherently uncertain. Such uncertainty is usually revealed progressively over time. Consequently, the grid planning and operation decisions need be adjusted accordingly across multiple stages to achieve optimal efficiency. The multistage decision structure calls for study on multistage grid op |
| Source | NSF Awards |
$799/mo
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