Impact of IBR Negative-Sequence Current Injection on Ground Fault Temporary Overvoltage and Ground Overcurrent Protection
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Inverter-based resources (IBRs) are proliferating in distribution and transmission systems. These resources have been driving changes in industry paradigms, grid codes, standards, and recommended practices. One established utility system design is effective grounding for ground fault temporary overvoltages (GFTOV). This was derived entirely on the premise of a traditional grid, with utilities conforming their practices over the decades with the expectation of this topology to continue. As IBRs proliferate, traditional practices are becoming ineffective in depicting expected behavior. As a result, management of GFTOV becomes critically dependent on IBR control algorithms and on the negative sequence impedance of the aggregate load of a distribution feeder. This requires a shift in direction for transmission and distribution operators. This paper includes an electric utility's lessons learned in the interconnection of a range of large scale IBRs to its distribution grid. Two case studies are presented to illustrate the drawbacks of conventional practices. It also exemplifies how the utility manages the problem and presents a forward-looking perspective on the evolution of rules, standards, and practices.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it