Dynamic phasor modeling of type 3 wind turbine generators for large-scale power system transient stability studies
Bibliographic record
Abstract
The wind power penetration has been increasing significantly, and this trend is likely to continue. As wind power penetration levels increase, interconnecting large-scale wind power plants (WPPs) into the existing power system has become a critical issue. Therefore, appropriate wind turbine generator models are required to conduct transient stability (TS) studies. While it is possible to construct detailed and accurate models of manufacturer-specific wind turbine generators in electromagnetic transient (EMT) simulators, such models are not suitable for large-scale transient stability studies due to their high computational complexity. The Western Electricity Coordinating Council (WECC) Renewable Energy Modeling Task Force (REMTF) is working towards developing generic wind turbine generator models that would be applicable for a range of general purpose system-level studies. However, such the generic models are typically over-simplified and not able to predict some of the phenomena, e.g. the unbalanced disturbance which is easily captured by the EMT simulations. In this research, a numerically-efficient model for the doubly-fed induction generator (DFIG) is developed that can predict steady state, balanced and unbalanced disturbances, and is sufficiently generic. The new DFIG model is based on the dynamic-phasor (DP) based machine models, which have been recently developed for the EMT simulators and can work with fairly large time-steps (up to several milliseconds) approaching that of the TS program solution. The WPP models have been implemented in MATLAB/Simulink® to assess the improved accuracy and computational efficiency. The new DP-based DFIG model is tested in a single machine infinite bus case and a two-area four-machine network to validate the model’s responses to balanced and unbalanced conditions of the grid. The accuracy of new DFIG model is shown to be significantly better compared to traditional TS models, which is achieved at a slightly increased computational cost. The result of this research will provide more accurate dynamic phasor based models of WPP for TS analysis. Since TS programs are widely used by utilities over the world, the new DP-based DFIG model will contribute to more reliable and accurate studies. This, in turn, will enable more reliable integration of large-scale WPPs into the existing and expanding power grids.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".