A Tool for Power Quality Assessment in Electric Submersible Pump Systems with Variable Frequency Drives
Bibliographic record
Abstract
Abstract This paper introduces an initial version of a standalone interactive numerical simulation tool for assessing power quality in electric submersible pump (ESP) applications. The tool replicates the steady-state behavior of low- and medium-voltage ESPs supplied by pulse-width modulated variable frequency drives (PWM-VFDs) at different operating points. This tool for replicating the voltage current waveforms supplied to the ESP motor and the instantaneous electromagnetic torque in the motor airgap is beneficial for electrical and non-electrical engineers involved in the design, analysis, and operation of ESP power systems. The tool is based on a rigorous modeling approach, where the induction machine and a pump load have been modeled as a two-moment inertia system connected to a multi-pi section model of the transmission cable. A low-voltage two-level VFD connected to a step-up transformer and a medium-voltage cascaded H-bridge multilevel inverter has been incorporated with an optional sine wave filter (SWF). VFDs have closed-loop controllers, with their parameters tuned to accommodate system setup. Depending on the parameters of the systems, more than 1344 operating points can be simulated from the graphical interface, thus showing its wide range of use in the oil and gas industry. To demonstrate the accuracy of the method and the proposed tool, the results of this tool are compared with those from field measurements. This type of tool is new to the ESP industry. It has been covered by an intuitive easy-to-use graphical interface, where only a selection of key system parameters has been enabled and made available to the users. No advanced simulation skills are needed, time and frequency domains’ results are automatically generated and can be easily exported to reports. The tool is a Windows-based standalone software.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".