Optimal Smart Inverter Volt-Watt and Volt-Var Settings to Maximize Fair Contribution in Voltage Regulation
Bibliographic record
Abstract
Overvoltage resulting from the high penetration of photovoltaic (PV) sources in distribution networks is a major challenge. Approaches to mitigate such overvoltage conditions include curtailment of PV active power and the injection of reactive power by PV inverters. This paper proposes a centralized control strategy to optimize the Volt-Watt and Volt-Var profiles such that active and reactive power of all PV inverters are controlled to not only to mitigate against overvoltage conditions but to do so in a manner where curtailment of active power is equalized or balanced in a fairly manner across all inverters. The Imperialist Competitive Algorithm (ICA) algorithm is used to optimize the objective functions. MATLAB and Open DSS software are used to simulate the grid model and optimize goals.
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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".