The harmonic impact project — IEEE-1459 power definitions trialed in revenue meters
Bibliographic record
Abstract
Most meter specifications presently do not define accuracy requirements in the presence of harmonics. Meter designs could therefore use different definitions or algorithms that produce different measurements in the presence of harmonics. Smart Grid environments with Distributed Generation could have significant levels of distortion, and revenue meters must be able to distinguish between the energy traded at 60 Hz (50Hz) and harmonics. The IEEE-1459 Standard provides a power definition model that is ideal for revenue metering. Efforts to revise Canadian meter specifications to cater for harmonic-rich environments have been hampered by several factors, including a lack of empirical data on the magnitude of the problem and concerns that present meter technology could not address the problem cost-effectively. BC Hydro initiated the Harmonic Impact Project (HIP) to show that off-the-shelf smart meters could implement the proposed definitions, and to obtain and evaluate empirical field data based on several power definitions. The HIP project confirms that these metering inequities exist and that their magnitude can be significant. The project also confirms that the IEEE-1459 fundamental-only power definitions are suitable for revenue metering and can be implemented by present meter technology.
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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 | 0.035 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".