Energy and Exergy Analysis of a Power Plant Based on a Three Reactor Chemical Looping Reforming System
Bibliographic record
Abstract
Chemical looping reforming (CLR) is an innovative way of simultaneously producing hydrogen (H2) and capturing carbon dioxide (CO2). In CLR process the fuel and the oxidizer do not meet and therefore, there is no energy penalty for separating CO2 as opposed to the conventional power plants. Only thing required to do to obtain pure H2 and CO2 is to condense the water vapor in both the streams. The process is divided into three steps: oxidation of fuel in the fuel reactor (FR) to form CO2 and H2O, reduction of steam to form H2 in the steam reactor (SR) and the complete oxidation of the metal oxygen carrier (OC) in the air reactor (AR). When the CLR system is integrated with a full power plant, there are energy losses in each of the components. It is necessary to know where the exergy is being destroyed and where it can be avoided. Therefore, an exergy analysis has been performed on the plant consisting of CLR system, steam cycle (SC) which incorporates triple pressure heat recovery steam generator (HRSG) and the compression system for compressing H2 and CO2 to high pressures ready for consumption or sequestration. This study employs an Aspen plus model to investigate the influences of various operating parameters such as the flow rates of fuel, air, steam and OC on the electrical, H2 and exergetic efficiencies of the plant. The results show that the electrical and the H2 efficiencies are dependent on the reactor temperatures. The reactor temperatures can be easily controlled by varying the flow rates of the reactants. It is observed from the results that higher electrical efficiencies are obtained at lower fuel, steam and air flow rates and higher OC flow rates. While the higher H2 efficiencies are obtained at lower flow rates of OC, air and steam and higher flow rates of fuel. Since the exergetic efficiency depend on the output of the plant which is H2, then the similar criteria is required to obtain high exergetic efficiency as that of H2 efficiency.
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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".