Load-Flow Time-Series Simulation of a Distribution Grid with PV Modules and Voltage Regulation
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Bibliographic record
Abstract
Load-flow time-series (LFTS) simulation is a common type of simulation used for assessing the power flow and the system voltage over a large time window for renewable energy integration studies. This paper presents a JavaScript-based execution of LFTS simulations in EMTP software and analyzes the effect of photovoltaic (PV) generation, volt-var control, and voltage regulators on the grid voltage for the IEEE-34 benchmark distribution grid. This study considers realistic profiles for the load demand and the PV generation. The accuracy of the LFTS simulation results is verified by comparison with time-domain simulation results. The results show that a combined usage of voltage regulators and volt-var control can help to mitigate undervoltage issues on a highly loaded node if sufficient PV generation is installed. Volt-var control provides additional support for the grid voltage without significantly impacting the active power flow at the distribution grid's connection point with the transmission grid.
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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 | 0.000 | 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 it