A Dual-Uncertainty Two-Stage Fractional Programming Model for Reginal Power Systems in the Province of Ontario, Canada
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Bibliographic record
Abstract
This study proposed a dual-uncertainty two-stage fractional power system management (DUTSF-PSM) model to deal with uncertainties and dual objectives in the power management system of Ontario. This model integrates interval linear programming (ILP), chance-constrained programming (CCP), mixed-integer linear programming (MILP), and two-stage stochastic programming (TSP) methods into the framework of a linear fractional programming (LFP) model. Two-objective issues and capacity expansion schemes under multiple uncertainties can be addressed by the DUTSF-PSM model. Economic and environmental elements are considered in the objective function of the DUTSF-PSM model at the same time in order to get maximal system benefit with minimum environmental influence. This model can tackle effectively the tradeoff between the economic and environmental objectives. Through the DUTSF-PSM model for power systems in Ontario, the maximal system efficiency based on the least environmental influence under different levels of constraint-violation probabilities can be achieved. The results indicate that both hydroelectric and wind power have development potential when the economic and environmental factors are considered in the objective function at the same time. In addition, the results of factorial analyses reflected that the effect of CO2 emission of each power generation technology on the system revenue is most significant among the chosen three factors.
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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 | 0.000 | 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 | 0.000 | 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 it