Methodology Calculation for Reactive Power Compensation in Industrial Enterprises
Why this work is in the frame
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Bibliographic record
Abstract
Much attention is paid to problem of reducing losses of electric energy in electric power industry of many countries, especially in Ukraine. Distribution networks of industrial enterprises in Ukraine are characterized by two voltage levels -0.4 and 10 kV. Active power factor of industrial power consumers is determined by nature of process and many electrical installations have low cos values. Significant flows of reactive power and, as a result, additional irrational losses of electric energy take place in the distribution networks of enterprises as a result. Purpose of this article is to improve methodology of design justification for selection of main elements of internal power supply system of industrial enterprise to obtain rational compensation of reactive power in distribution network of enterprise. Existing methodology for designing a reactive power compensation system involves use of averaged indicators of unit cost of power equipment (transformers, compensating devices) and is based on assumption of linear nature of dependence of these indicators on power of equipment. Study of these dependencies for equipment of number of manufacturers showed their nonlinear character that is not formalized. Article proposes methodology for selecting number and power of compensating devices at same time as power transformers of workshop substations according to criterion of minimum annual reduced costs for these power supply system elements at design stage of power supply system. Proposed method takes into account real cost of power equipment, which can be used in reactive power compensation system at designed enterprise and provides choice of option that meets technical requirements of regulatory documents and has a minimum annual cost.
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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 | 0.001 |
| 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 | 0.001 |
| 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 it