Reliability-Based Incremental PMU Placement
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
This paper presents a new reliability-based incremental phasor measurement unit (PMU) placement method via an enumeration-based integer linear programming optimization approach. By evaluating the proposed reliability indices for node and system observability, incremental PMUs are sequentially placed on the locations where the reliability of entire system's observability can be best improved at each step. As a result, a pre-set desired reliability of the system's observability can be achieved while using the minimal number of PMUs. The proposed method is generic and flexible in a way that different kinds of failures that impact the reliability of system observability can be easily included in the method. The 1st-order and 2nd-order failures of PMUs and lines are considered in this paper. The proposed method is validated using a 4-node system, the IEEE 14-node system and the IEEE RTS 96 test system. Simulation results show that the proposed method is effective and efficient in enhancing the reliability of observability for any system regardless of what the initial PMU placement of the system may be.
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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 | 0.001 | 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