Multigeneration-CAES system with biomass energy integration: Energy implications and exergoeconomic
Bibliographic record
Abstract
Using biomass energy , this research evaluated the energy, exergy and exergoeconomic characteristics of the combination of the multigeneration system (MGS) and the compressed air energy storage system (CAES). It features a combined Brayton and compressed air energy storage sub-cycle (CBACS) and a combined proton exchange membrane (PEM) electrolysis and heating sub-cycle (CPEAHS). Hot water is generated economically during off-peak hours, while electricity, hot water, hydrogen, and oxygen are generated during peak hours. Through evaluating the system's charge/discharge, it was found that the MGS-CAES can produce 681 kW of electricity, 5.8 kg/s of hot water, 5.4 kg/h of hydrogen, and 6.7 kg/h of oxygen, making its implementation feasible. As part of our parametric study , we explored how decision variables, including the entry temperature of the gas turbine , the entry pressure of the compressed air storage cavern (CASC), the CASC outlet pressure and biomass mass flow rate affect thermal and economic performance. Upon lowering the entry temperature of the gas turbine , the round-trip productivity increased by 1.1 %, and the overall capital investment and overall cost of the product were both reduced to 85.8 $/h and 111 $/h. The exergy destruction cost rate reaches its minimum value of $ 64.24 per hour at an inlet pressure of 2200 kPa for the CASC system., while rising the CASC outlet pressure improved the MGS-CAES exergy round trip efficiency by 3.4 %. It is estimated that biomass mass flow rate growth resulted in an enhancement of heat and electricity production.
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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".