Benchmarking Electro-Energetic Performance of Industrial Systems by using Novel Concept of Benchmarking Energy Factor (BEF)
Bibliographic record
Abstract
The electro-energetic efficiencies of Industrial Systems and Processes (IS&P) are currently monitored by using different types of Energy Performance Indicators (EnPI). The EnPI represents a ratio between energy spent [kWh] per unit of product, area, volume, or other quantity directly related to production. The EnPI values are supposed to be collected in a centralized data system enabling benchmarking activity at national level. One of the major barriers for this process is related to the ethical and legal issues impeding disclosure of proprietary information. On the other hand, the tedious normalization process due mainly to volatile and un-reliable reference value is another major barrier for benchmarking process. As a result the accuracy of benchmarking IS&P represents always a challenge for governments and for corporations implementing ISO 50001. The use of unitless indicator i.e. Benchmark Energy Factor (BEF) overcomes the current barriers. The paper proposes a new concept of using Mathematical Model Benchmarking (MMB) and Benchmarking Energy Factor (BEF). The concept enables a new approach towards energy efficiency in industrial and commercial sector and help level the playing field for energy management. The use of Basics of engineering and the laws of physics indicate that only wasted energy, namely Energy at Risk (E@R) values can be controlled. The waste energy (E@R) variation is embedded in unitless Benchmarking Energy Factor (BEF). Proposed method makes possible to determine accurately the (E@R) under variable material and environmental conditions making possible to manage the energy losses and eliminating the tedious process of normalization. The benchmark rating is then solely based on how close the true energy consumption within an industrial process gets to the ideal state. Once E@R is known, it will be logical proceeding with benchmarking plants, industrial systems and commercial buildings assessing their capability of managing Energy at Risk by focusing on in-situ testing. The paper presents the basics of MMB and basic use of BEF applied to standards accompanied by the case studies inspired from real life (industrial refrigeration and mining industries). The MMB concept can be used by any IS&P owner enabling easy implementation of ISO 50001. The unitless BEF indicator enables a reliable and credible rating system model describing electro-energetic efficiency of any IS&P and can be used by Utilities (for their DSM programs), Natural Resources Canada (NRCAN) or U.S. Department of Energy - Energy-Star Certification for Plants Program as an alternative to the existent benchmarking practice. Canadian Standard Association, Canadian Utilities and NRCAN is currently preparing Guideline Standards of benchmarking industrial and commercial systems and processes by using the novel BEF concept.
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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 | 0.000 | 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 | 0.001 |
| 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".