Comprehensive Examination of a Green Hybrid Biomass-Integrated Compressed Air Energy Storage System with PEM Hydrogen Production Across Various Operating Modes
Bibliographic record
Abstract
The shift to renewable energy is vital for creating a cleaner world and addressing the growing energy demands of modern societies. Energy storage technologies play a key role in this transition, enabling efficient integration of renewable sources. This study introduces an innovative system that uses biomass as its primary fuel and incorporates compressed air energy storage (CAES) technology to handle peak energy demand effectively. CAES is selected due to its suitability for large-scale applications. Additionally, waste heat recovery is integrated to enhance overall efficiency, enabling the simultaneous production of electricity, hydrogen, and hot water. The system is evaluated across three operational periods (off-peak, mid-peak, and peak) to ensure its adaptability and performance. It is designed to maximize resource utilization while reducing energy losses, making it a sustainable and practical solution to current energy and environmental challenges. A comprehensive evaluation encompassing energy, exergy, economic, and environmental aspects is conducted. The results show an overall system efficiency of 61 %, with CAES achieving energy and exergy round-trip efficiencies of 66.9 % and 51.3 %, respectively. The plant produces hydrogen at a rate of 5.65 g/s during mid-peak and off-peak periods, and hot water at a consistent rate of 7.8 kg/s across all operating periods. • Introducing a flexible and innovative configuration based on biomass energy and ESSs to achieve sustainable power. • Conducting a comprehensive analysis of technical, economic, and environmental aspects across various operational periods. • Utilizing waste heat recovery through the ORC and PEM units.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".