Multi-objective short-term hydro-thermal scheduling using bacterial foraging algorithm
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Bibliographic record
Abstract
In this paper, the optimization problem of the short-term hydro-thermal scheduling (STHTS) is addressed considering the environmental aspects. To solve this multi-objective problem, an improved bacterial foraging algorithm (IBFA) is implemented. In addition to minimizing the cost function, the minimization of gaseous emission is also considered. Operating cost of thermal generating units, NO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</sub> , SO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> and CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> emission are minimized over the scheduling period considering various thermal and hydro constraints. The environmentally constrained STHTS problem, as it is the case of the classic one, is a dynamic large-scale nonlinear optimization problem which requires solving unit commitment and economic power load dispatch problems. The bacterial foraging algorithm (BFA) is a recently developed evolutionary optimization technique based on the foraging behavior of the E. coli bacteria. The BFA has been successfully employed to solve various optimization problems; however, for large-scale problems, it shows poor convergence properties. In fact, the basic BFA cannot be applied to solve complex problems such as the STHTS problem. To tackle this problem considering its high-dimensional search space, significant improvements are introduced to the basic BFA. The algorithm is validated using a well known hydro-thermal generation system. Results are obtained and the trade-off set of solutions is successfully captured.
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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