Extended-frequency dynamic phasor modelling of LCC-HVDC systems for electromagnetic transient simulations
Bibliographic record
Abstract
A new model for line-commutated converter (LCC) HVDC systems based upon the concept of extended-frequency dynamic phasors is developed in an electromagnetic transient (EMT)-based simulation platform. The proposed model is capable of representing LCC-HVDC converters during normal as well as abnormal operating modes, such as system imbalances and commutation failure, by automatically adjusting its parameters based upon converter terminal quantity measurements. The model offers a high level of accuracy with reduced computational burden as a suitable replacement for conventional switch-based models of LCC in EMT simulation platforms. The proposed model is then extended to real-time EMT simulations. The performance of the proposed model is first evaluated against detailed EMT simulations of a simple LCC system. The evaluation is then extended to simulation of large electric networks such as CIGRE HVDC benchmark and IEEE 12-bus systems with an embedded LCC-HVDC link. Simulation results confirm that the proposed dynamic phasor-based model retains EMT-grade accuracy even at large simulations time steps. Significant acceleration ratios reaching up to an order of magnitude are observed in the simulations using the proposed model compared with conventional EMT models. A real-time EMT variant of the model is then implemented in RTDS real-time simulator. The performance of the dynamic phasor-based model is investigated against existing real-time LCC models with large and small time steps in a hardware-in-loop simulation scenario. The results confirm that the proposed dynamic phasor model retains the same level of accuracy as existing small time-step real-time models while using significantly larger time-steps, thus relieving the burden of real-time computations.
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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".