Comparative techno-economic assessment of solid oxide fuel cells versus hydrogen-fueled internal combustion engines for institutional energy management
Bibliographic record
Abstract
• Techno-economic assessment of hydrogen fuelled CHPs for institutional sector. • Comparative study of solid oxide fuel cell versus hydrogen fuelled combustion engine CHPs. • Incorporating real-word heat, electricity, and temperature data for accurate feasibility studies. • Evaluating the impact of future advancements in capital cost and lifespan on solid oxide fuel cell feasibility. Hydrogen is globally recognized as a transformative energy carrier, offering a pathway to a sustainable and low-carbon future. Its integration into energy systems, particularly through combined heat and power (CHP) technologies, provides an efficient and reliable solution for institutional energy management while supporting global decarbonization efforts. This study examines the potential of hydrogen-based CHPs in decarbonizing the energy management of the University of Alberta (UofA) in Canada, aligned with the objectives outlined in the university’s master energy plan. A comparative analysis using real operational data evaluates two hydrogen-based CHP technologies: solid oxide fuel cell (SOFC) and hydrogen-fueled internal combustion engine (HICE). Results indicate that a 70 MW CHP system could meet the university’s total energy demand with a heat-to-power ratio ranging from 0.4 to 4.1, depending on seasonal changes. While the HICE-based CHP features a lower capital cost of $140 million, annual operational costs of $24.25 million, and levelized cost of energy (LCOE) of 20.1 ¢/kWh, it emits over 4 tons of nitrogen oxides (NOx) annually. In contrast, the SOFC-based CHP system, while having higher capital, operational expenditures, and LCOE of $280 million and $66.32 million per year, and 33.5 ¢/kWh, respectively, delivers superior environmental performance, positioning it as a more sustainable solution. Additionally, as SOFC technology matures, its long-term economic feasibility is expected to improve significantly. Therefore, although the HICE-based CHP is currently more economical, SOFC systems hold a great potential as the preferred sustainable energy solution for UofA or similar institutions with decarbonization and sustainability mandates.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".