Abstract
Sudden losses of generation or load can lead to instantaneous changes in electric grid frequency and voltage. Extreme frequency events pose a major threat to grid stability. As renewable energy sources supply power to grids in increasing proportions, it becomes increasingly important to examine when and why extreme events occur to prevent destabilization of the grid. To better understand frequency events, including extrema, historic data were analyzed to fit probability distribution functions to various frequency metrics. Results showed that a standard Cauchy distribution fit the difference between the frequency nadir and prefault frequency (f_(C-A)) metric well, a standard Cauchy distribution fit the settling frequency (f_B) metric well, and a standard normal distribution fit the difference between the settling frequency and frequency nadir (f_(B-C)) metric very well. Results were inconclusive for the frequency nadir (f_C) metric, meaning it likely has a more complex distribution than those tested. This probabilistic modeling should facilitate more realistic modeling of grid faults.
Original language | American English |
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Number of pages | 8 |
State | Published - 2017 |
Event | International Workshop on Large-Scale Integration of Wind Power into Power Systems as well as on Transmission Networks for Offshore Wind Power Plants (Wind Integration Workshop) - Berlin, Germany Duration: 25 Oct 2017 → 27 Oct 2017 |
Conference
Conference | International Workshop on Large-Scale Integration of Wind Power into Power Systems as well as on Transmission Networks for Offshore Wind Power Plants (Wind Integration Workshop) |
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City | Berlin, Germany |
Period | 25/10/17 → 27/10/17 |
NREL Publication Number
- NREL/CP-5D00-70029
Keywords
- electric grid frequency
- probabilitic modeling
- renewable energy
- voltage