Performance Analysis of Optimization Based Static Distribution State Estimation Techniques
Bibliographic record
Abstract
Distribution System State Estimation (DSSE) is a popular technique used to estimate the operating states of a distribution system on a feeder basis. This paper presents two DSSE algorithms, the conventional Node Voltage based State Estimation (NVSE) and Branch Current based State Estimation (BCSE) methods, formulated as optimization problems using the WLS estimator. The models are validated on a 33-bus distribution feeder and the convergence of estimated states to true states are analyzed. The performance comparison of the conventional WLS driven NVSE with the BCSE method, is carried out in terms of squared error and average root mean square error (ARMSE) of system state values. Finally, the NVSE optimization problem was solved by varying the number of Phasor Measurement Units (PMU) units installed to study the impact of the number of PMU measurements state estimation performance.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".