Dispatching thermal power plants under water constraints
Bibliographic record
Abstract
Climate change has exposed the vulnerability of power utilities to low water availability for hydropower generation and to high river temperatures for thermoelectric power plants. In this study, we focus on a region whose power system is controlled by an operator that relies on a set of thermal power plants to generate electricity, and consider the conventional economic dispatch problem in the presence of cooling water scarcity and climate change constraints. Specifically, we consider water constraints on the amount of water that can be consumed by the power plants, and heat constraints on the amount of heat that be transferred to the environment by the thermoelectric power plants. We focus on a practical scenario in which the power plants are aligned on a river shared by all the power plants. We then propose a general optimal power flow (OPF) framework. The proposed economic dispatch problem is NP-hard. We have developed numerical techniques to compute sub-optimal solutions to the proposed problem. Finally, we show the impact of climate change (i.e., water availability and heat constraints) on electricity generation.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".