Energy Management in a Network of Grid-Connected Microgrids/Nanogrids Using Compromise Programming
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Bibliographic record
Abstract
A new multi-objective optimization model is proposed for efficient integration of a group of microgrids/nanogrids with local energy storage devices into the power grid. In this model, the individual microgrids/nanogrids can exchange power locally among each other as well as with the external electricity grid. A pricing regime is introduced in which differences in the local and grid buy and sell time-of-use prices of electricity incentivize local inter-microgrid/nanogrid exchanges of power over power exchange with the grid. A novel formulation of a multiple-objective constrained optimization is presented for solving the microgrids/nanogrids energy management problem under the proposed electricity pricing regime. This approach is based on minimization of l <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> or l <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> distances of the microgrids/nanogrids cost vector to a utopia point in the solution space. Components of the utopia point are defined as the minimum cost achievable by the corresponding microgrid/nanogrid when it always uses the favorable local buy/sell prices. The proposed optimization models are in the form of convex linear/quadratic programs without any binary or integer variables for l <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> /l <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> norms. Results of numerical simulations with on-line rolling horizon optimization of the storage device power flow decisions demonstrate the effectiveness of the proposed methods.
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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 | 0.001 |
| 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