Measurement-based Optimal Power Flow with Linear Power-flow Constraint for DER Dispatch
Bibliographic record
Abstract
This paper proposes a measurement-based method to obtain optimal power-flow (OPF) solutions that optimize distribution-system operations by dispatching active- and reactive-power outputs of distributed energy resources (DERs). Central to the proposed method is the estimation of a linear power-flow model from synchronized voltage and power-injection data collected from distribution-level phasor measurement units (D-PMUs). The estimated model is then incorporated into an OPF problem as an equality constraint. We formulate a quadratic cost function that enables co-optimization of DER active- and reactive-power costs, voltage deviations away from prescribed reference levels, as well as active- and reactive-power deviations from desired setpoints. Via numerical simulations of the IEEE 33-bus distribution test system, we demonstrate that the proposed measurement-based method yields sufficiently accurate solutions compared to model-based OPF solutions. Furthermore, we highlight the adaptability of the proposed method in case an accurate network model is not available.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".