Implementing a second generation CCS facility on a coal fired power station – results of a feasibility study to retrofit SaskPower's Shand power station with CCS
Bibliographic record
Abstract
Abstract In 2018, the International CCS Knowledge Centre (CCS Knowledge Centre) conducted a feasibility study with SaskPower to determine if a business case could be made for a postcombustion, carbon capture retrofit of SaskPower's Shand Power station, a 305‐MW, single‐unit, lignite coal‐fired power station located near Estevan, Saskatchewan. Specifically, Mitsubishi heavy industries’ KM CDR technology was evaluated for this study. While no decision has been made, should SaskPower decide to proceed, the Shand carbon capture and storage (CCS) project would produce the second, full‐scale capture facility in Saskatchewan with a nominal capacity of 2 million tonnes of CO2 (Mt) per year. This paper summarizes the key technical and economic findings of this study. Notably this study found that the capital costs of the potential Shand CCS facility are decreased by 67% on a per tonne of CO2 captured basis when compared to the CCS retrofit of Unit 3 at the Boundary Dam Power Station (the world's first industrial scale CCS installation on a coal fired power station). The proposed capture facility would also have a load following operational profile, reduction in parasitic loses by employing heat integration strategies, and need no additional water draw to provide the required increase in cooling duty. © 2020 The Authors. Greenhouse Gases: Science and Technology published by Society of Chemical Industry and John Wiley & Sons, Ltd.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".