Benefits of Micro-grids for the Cement & Mineral Industries
Bibliographic record
Abstract
Using various industrial cases this paper presents the potential effectiveness of the modern microgrid system to provide electricity bill reduction to energy intensive plants, depending on their location. The presented microgrid system is a 2 MWp PV and 2.26 MW/4.2 MWh mixed-technology battery storage, grid connected, which supplies a manufacturing facility and offices. A project being developed in Central America at a Cement grinding plant, with 5 MWp PV, 1 MW/4MWh hybrid flow battery storage, grid connected under the “electricity as a service” (PPA) scheme, How the Global Adjustment (demand charges) scheme of the Ontario grid is being solved with battery storage, even where electricity is cheap. Why technology such as flow batteries is relevant to the specifics of the Cement Industry. The importance of local regulations & legislations and the relationship with the local utilities emphasize the uniqueness of each project and the difficulty implementing them. On-going equipment cost reduction should nevertheless bring more projects on-line in the coming years. Cases studies of various projects applicable to the cement industry including a micro-grid project and flow batteries development will be presented. The objective is electricity bill reduction.
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".