A Novel Reclosing Scheme for Mitigation of Distributed Generation Effects on Overcurrent Protection
Bibliographic record
Abstract
This paper proposes a novel scheme to mitigate distributed generation (DG) effects on existing fuse-recloser protection infrastructure in radial distribution networks. The proposed scheme employs a control unit, variable load bank, and dedicated recloser at the point of common coupling (PCC). It detects the increase in the DG terminal current producing a tipping signal when it exceeds a preset value. The proposed scheme also receives a fault detection signal from the head-end recloser via a fast communication channel. Upon verifying both signals, the scheme disconnects the DG unit from the system. Simultaneously, it connects a transfer impedance at the PCC to operate the DG unit at its prefault load-sharing condition. This allows the DG unit to continue supply to the transfer impedance at the prefault load-sharing condition, that is, maintain operation at the prefault level with no need for immediate shut down. Furthermore, it also allows the DG to maintain its speed and frequency at the prefault levels which, in turn, allows faster reconnection of the DG unit to the system after successful reclosing. For the case of unsuccessful reclosing or the case where the fault is not cleared within the set utility time set frame, the proposed scheme shuts the DG source down. The transfer impedance is selected from a variable load bank and is a function of the prefault load-sharing condition; therefore, a sensitivity survey was performed during the investigations of this paper to cover all possible system operating conditions and its corresponding transfer impedances. In the context of this paper, multiple in-depth time-domain simulations are conducted to ascertain the efficiency of the proposed scheme in mitigating the impact of DG sources on existing overcurrent protection infrastructure. Time-domain simulations have been conducted using a typical distribution network in the EMTP-RV software environment for validation purposes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".