Performance Assessment of Active Frequency Drifting Islanding Detection Methods
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Full frame distilled prediction
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.
- Candidate categories
- none
- Consensus categories
- none
- Domain
- Candidate signal: noneConsensus signal: none
- Study design
- Candidate signal: Bench or experimentalConsensus signal: Bench or experimental
- Genre
- Candidate signal: EmpiricalConsensus signal: none
- Teacher disagreement score
- 0.841
- Threshold uncertainty score
- 0.823
- Validation status
machine_predicted_unvalidated·codex-gemma-dda1882f352a
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)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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.
- Teacher spread
- 0.234 · how far apart the two teachers sit on this one work
- Validation status
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
Abstract
Islanding detection is a mandatory feature for grid-connected inverters. The effectiveness of passive islanding detection methods (IDMs) is usually demonstrated by means of nondetection zones (NDZs) represented in a power mismatch space (/spl Delta/P versus /spl Delta/Q). Active frequency drifting IDMs have been shown to provide improved performance but their theoretical NDZ cannot be described in the /spl Delta/P versus /spl Delta/Q space for a general RLC load. This paper shows that a load parameter space based on the values of the quality factor and resonant frequency of the local load (Q/sub f/ versus f/sub 0/) can be used in these cases. It employs a single curve to represent the NDZ of frequency drifting IDMs for any RLC loads. Equations that represent NDZs of three common active IDMs in the Q/sub f/ versus f/sub 0/ load parameter space are derived and it is shown that the slip mode frequency shift and the Sandia frequency shift IDMs can be designed to guarantee islanding detection for equivalent RLC loads with a quality factor smaller than a design value. The accuracy of the NDZs is verified with simulation and experimental results.
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.
The record
- Venue
- IEEE Transactions on Energy Conversion
- Topic
- Islanding Detection in Power Systems
- Field
- Engineering
- Canadian institutions
- SNC-Lavalin (Canada)Concordia University
- Funders
- not available
- Keywords
- IslandingRLC circuitControl theory (sociology)AC powerQ factorElectronic engineeringPhysicsPower (physics)Computer scienceEngineeringVoltageElectrical engineeringElectric power systemCapacitorOptics
- Has abstract in OpenAlex
- yes