A Novel Stochastic Volt/VAR/Pressure Optimization-Based Conservation Voltage Reduction Technique in Integrated Electricity and Natural Gas Systems With PV Smart Inverters
Bibliographic record
Abstract
This paper proposes a novel two-stage stochastic Conservation Voltage Reduction (CVR) technique in integrated electricity and natural gas systems, where the mixed-integer second-order cone programming (MISOCP) model is used to coordinate legacy voltage regulation devices (on-load tap changers (OLTCs) and capacitor banks (CBs)) with photovoltaics (PV) smart inverters. In the first stage, optimal hourly day-ahead settings of OLTCs and CBs, and the base reactive power settings of smart inverters are determined. After considering uncertainties in the forecasted load and PV power generation, reactive power adjustments from smart inverters through droop control are determined in the second stage. A two-step algorithm is also proposed to improve the solving speed of the stochastic problem. The proposed stochastic CVR technique is validated using the modified IEEE 33-bus electricity and 7-node natural gas test system, IEEE 123-bus electricity and 20-node natural gas test system, and a large unbalanced 404-node distribution system currently operated by Saskatoon Light and Power in Saskatoon, Canada, integrated with a 20-node natural gas network.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".