Quantifying the value of pumped storage hydro (PSH) in the Saudi electric grid
Bibliographic record
Abstract
The potential increase of the connected capacity of renewable energy sources in Saudi Arabia will open the doors for more investment in energy storage especially pumped storage hydro (PSH). New PSH, particularly in areas with increased wind and solar capacity, would significantly improve system reliability while reducing the need to construct new fossil-fueled generation. PSH is proving to be an established technology for renewable power because it can absorb excess generation and release it during peak demand times. PSH can also provide many ancillary services to the power system that should be added to the benefits of PSH projects, such as increased flexibility, primary frequency response, following reserves, and fast-acting regulation reserves. PSH is typically not adequately represented during the optimization of the commitment and dispatch formulations in which reduces their perceived benefits. The paper discusses how to quantify PSH benefits to the power system operators so that the PSH projects would be more economically viable to the Kingdom and more appealing for private investment. Potential market changes that can help PSH in today's restructured markets are presented and discussed in this paper.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".