Towards a Clean and Sustainable Distributed Energy: The Potential of Integrated PEMFC-CHP
Bibliographic record
Abstract
The use of fossil fuels within the current infrastructure for domestic energy supply is one of the main causes of anthropogenic emissions. The mitigation options to meet the ambitious carbon reduction targets set by the UK government are discussed in this paper, including the use of carbon capture and storage technology, clean renewable energy integration and a proposed system of integrated fuel cell combined heat and power (FC-CHP) technology. Analysis shows that the use of carbon capture and storage (CCS) technology within the current infrastructure can abate half the electricity associated CO2 emissions; however, this comes at a high cost penalty. The emissions associated with domestic heat cannot be prevented without changes in the energy infrastructure. Hydrogen powered fuel cells can provide clean energy at a range of scales and high efficiencies, especially when employed with a CHP system. However, production of CO2 free hydrogen is essential for fuel cell technology to contribute substantially to a low carbon economy globally. In this work three methods were investigated for small scale distributed hydrogen production, namely steam methane reforming, water electrolysis and cold plasma jet. The criteria used for comparisons include the associated CO2 emissions and the cost of energy production. Cold plasma jet decomposition of methane shows a high potential when combined with integrated FC-CHP technology for economically viable and CO2 free generation of energy, especially in comparison to water electrolysis. Including the value of the solid carbon product makes the plasma system most attractive economically.
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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 | 0.000 |
| 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".