Low-frequency Disturbance Injection for Active Islanding Detection of Multiple Electronically-interfaced Distributed Generation Units
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Bibliographic record
Abstract
This thesis proposes and evaluates the application of a low-frequency disturbance injection, as an active islanding detection method, in a microgrid with multiple electronically-interfaced Distributed Generation (DG) units. Each DG unit is interfaced to the microgrid through a two-level Voltage-Sourced Converter (VSC). The low-frequency disturbance signal for islanding detection is injected through the q-axis control of each VSC unit. The low-frequency signal is at 1 Hz with an amplitude of up to 2.5 % of the rated VA of the VSC unit and augments the reference signal of the q-axis control.\n\nThe effectiveness of the low-frequency injection for islanding detection is examined under two distinct VSC control scenarios. In the first scenario, each VSC only injects pre-determined real- and reactive-power components in the system and does not participate in frequency/voltage control. In the second scenario, the VSC controls are also equipped with frequency/real-power and voltage/reactive-power droop characteristics and thus share power and participate in frequency and voltage control of the microgrid, specifically in the islanded mode.\n\nThe investigations reported in this thesis show that the proposed islanding detection method can effectively detect an islanding event under both VSC control strategies, subject to the conditions that UL and/or IEEE anti-islanding standards impose. The studies show that an islanding event can be detected within 536 ms subsequent to the instant of islanding.\n\nAs part of this thesis, an eigen analysis software tool has been developed that can systematically investigate the impact of low-frequency disturbance injection on the small-signal stability and dynamic performance of the microgrid, prior and subsequent to an islanding event.\n\nThis thesis concludes that the low-frequency disturbance injection-based method can be successfully applied to a multi-DG system, since (i) islanding detection is achieved within applicable standards requirements by all DG units in the system, and (ii) the low-frequency disturbance injection signal has no noticeable impact on the dynamics nor the small-signal stability of the system if its magnitude is kept below a pre specified limit.
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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