A Power Quality Assessment of Electric Submersible Pumps Fed by Variable Frequency Drives under Normal and Failure Modes
Bibliographic record
Abstract
This paper proposed a simplified modeling approach for a power quality (PQ) assessment of Electric Submersible Pumps (ESP) systems supplied by the two-level, the neutral-point-clamped three-level, and the cascaded H-bridge (CHB) multilevel inverter VFD topologies. The VFD switching function models and their analytical expressions are proposed to understand how they can create high-frequency components that might excite the resonance mode in a transmission cable or a rotating shaft system. Voltage, current, and motor airgap torque harmonics induced by each VFD topology in a balanced operation mode are derived and correlated to the PWM carrier and motor operating frequencies. The motor airgap harmonics are calculated based on Concordia’s transformation of voltages and currents in αβ-plan. These harmonic components are represented in the form of Campbell diagrams. An analysis of harmonics under unbalanced conditions was also conducted in a CHB VFD topology-powered ESP system with failed and bypassed cells. The investigated modulation technique is a neutral-shift PWM method that enables the system to operate balanced line-line voltages even if the line-neutral voltages are unbalanced. The effects of modifying the electrical spectrum using the neutral-shift PWM method on electrical and mechanical spectra are analyzed. The results of the Matlab/Simulink-based simulation show that the proposed full ESP system model is highly accurate in both normal and failure modes. The results are consistent with theoretical predictions and are graphically shown in the time and frequency domains for easy analysis. Hybrid experimental–numerical results on a reduced-scale laboratory setup are also discussed to confirm the correctness of the suggested developments.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".