Design, Simulation, Optimization, Techno-Economic Analyses and Life-Cycle Analyses of Solid-Oxide Fuel Cell Power Plants
Bibliographic record
Abstract
The global electricity generation industry is very reliant on the use of fossil fuels, particularly natural gas and coal. However, it is quickly becoming a reality that the over-consumption of these resources will continue to lead to significant global damage via global warming, ecosystem destruction, and the depletion of these so-called non-renewable re-sources. To combat this issue, renewable sources such as wind, biofuels and solar are be-coming much more prevalent in the power generation industry, but significant economic, reliability and availability barriers to entry will prevent these sources from being major contributors to the power industry for decades. To this end, this thesis focuses on the design, operation, optimization and life cycle analysis of an integrated solid-oxide fuel (SOFC) cell power plant integrated with com-pressed air energy storage (CAES). This plant, fueled by either natural gas or coal, can make much more efficient use of their limited non-renewable fuel sources, and are capable of achieving nearly 100% carbon capture at the plant boundary. This plant is intended to serve as a more efficient and environmentally responsible alternative to current power generation methods while still exploiting remaining fossil fuels to their fullest extent. This thesis details the design, sizing and simulation of integrated SOFC/CAES plants in Aspen Plus so that full feasibility and techno-economic analyses may be performed, the results of which are then compared to the current state-of-the-art (SOTA) options. In order to compare the plants on an environmental level, full cradle-to-grave life-cycle analyses using the ReCiPe 2008 method are completed for each SOFC-based plant and all comparable SOTA options under a wide range of assumptions and plant configurations, such as the use of carbon capture strategies. Furthermore, detailed reduced-order dynamic models of the integrated SOFC/CAES plants are developed and simulated with a newly developed rolling-horizon optimization method to assess the load-following capabilities of the integrated plant. Real scaled demand data for the market of Ontario, Canada for the years 2013 and 2014 are used as the demand data for the simulations. This thesis takes strides in proving the feasibility of an integrated SOFC/CAES power plant for providing clean, efficient, reliable and cost-effective power using fossil fuels. The next steps for this project involve the development of a lab-scale pilot plant, which would be used to validate simulation results and provide an opportunity for the real-time application and assessment of the potential of this plant design.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".