Thermodynamic design and assessment of a self-powered plant using integrated solar and biomass system with energy storage solutions
Bibliographic record
Abstract
This study develops a solar-powered energy system that integrates a solar tower, multistage gas turbines, an Organic Rankine Cycle (ORC), biomass and plastic gasification subsystems, and Compressed Air Energy Storage (CAES) and evaluates its performance. The present system is then assessed by considering thermodynamic, economic and environmental aspects, highlighting its efficiency in waste biomass and plastic utilization for energy conversion while minimizing exergy losses. The system achieves an annual AC energy production of 41,304,708 kWh, with an overall energy efficiency of 31 % and exergy efficiency of 53 %, highlighting its effective energy recovery and utilization. The biomass and plastic gasification subsystem stand out with 61 % energy efficiency, showcasing its capability to efficiently convert organic and synthetic waste into usable energy. Additionally, the CAES subsystem provides excellent energy storage and peak power delivery, enhancing system flexibility and reliability. The solar tower subsystem contributes significantly by harnessing solar energy, reflecting the systems strong alignment with renewable energy goals. A sustainability assessment is also conducted, to study some aspects of energy, exergy, and resource utilization efficiency to support a long-term environmental viability. Economically, the system demonstrates the potential for further cost optimization and scalability as technologies mature, with strategic improvements in key components expected to enhance long-term financial sustainability. The present system is further considered for potential implementation in the city of Isparta, Turkey, a region well suited for solar energy production and biomass utilization, providing a location-specific approach to optimizing renewable energy integration.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".