Development of a large-scale integrated solar-biomass thermal facility for green production of useful outputs
Bibliographic record
Abstract
The present paper develops a new multigeneration plant to produce multiple commodities from two combined renewable energy sources, solar thermal and biomass and considers a specific case study administered for the city of Al Lith in the Kingdom of Saudi Arabia. The plant generates power, heating, refrigeration, hydrogen, chlorine, concentrated sodium hydroxide, ammonia, urea, and fresh water, which are commodities at high demand in the area. The energy efficiency is determined to be 53% with an annual generation of over 1036 GWh of power and cogenerated 858 GWh of heating, nearly 23 GWh of refrigeration effect, over 11,300 tons of ammonia, almost 1800 tons of urea, over 113,000 tons of concentrated sodium hydroxide and over 905,000 m 3 of fresh water. The exergy contents of heating, refrigeration, power and commodity products represent a total of 45% of the sources, which leads to a multigeneration platform's exergy efficiency. The system includes an integrated biomass gasification combined cycle with a biomass oxy-gasifier. The Aspen Plus simulations of the oxy-gasifier determined that the oxygen-to-biomass weight fraction should be set to 0.15, whereas the steam-to-biomass weight fraction is around 0.1. The exhaust gas recirculation is applied to enhance power generation rate and efficiency. The recirculation ratio of exhaust gas is found to be 0.21 if power generation efficiency is to be maximized and 0.28 if the power generation rate is to be maximized. The fluctuating and intermittent nature of the solar energy resource causes poor economics when this energy is to be captured in isolation or itself only. The current paper demonstrates that the hybridization of solar and biomass energy together with integrated processes for multiproduct generation enhances the overall competitivity of the renewable energy system. To address this aspect, the objective of the paper is to develop and assess a new integrated flowsheet for hybrid renewable resource multigeneration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".