Comparative study of the discharge architecture for a multi-energy pumped thermal energy storage system using finite dimension thermodynamics
Bibliographic record
Abstract
This study presents a comparative assessment of the conventional discharge architecture of multi-energy Pumped Thermal Energy Storage (m-PTES) systems and an alternative configuration. In traditional architecture, the whole stored energy is devoted to supplying heat to the Rankine cycle which produces both electricity and useful thermal energy. On the contrary, in the alternative one, part of the stored energy is directly recovered through a heat exchanger to deliver thermal energy. The other part is used for the Rankine cycle. Thus, this cycle involves a lower capacity but it operates with the external environment as a heat sink. The performance of both configurations was analyzed using Finite Dimension Thermodynamics (FDT), considering key indicators such as power cycle efficiency, total required power, and heat exchanger conductances. This study uses the context of an industrial natural resource extraction process as a case study. The results show that the proposed configuration is more efficient when the external environment temperature is lower than the useful heat sink temperature. Additionally, this architecture achieves higher efficiencies for high power-to-heat ratios and storage temperatures below 497 °C. This research significantly contributes to the study of m-PTES systems by introducing a new discharge strategy, providing a detailed comparison with the conventional approach using FDT, and proposing heat exchanger optimization to minimize conductances.
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 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 | 0.000 | 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) | 0.001 | 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".