Priority-Based Microgrid Energy Management in a Network Environment
Bibliographic record
Abstract
The paper presents a method for energy storage dispatch and sharing of renewable energy resources in a network of grid-connected microgrids. The proposed scheme provides for local inter-microgrid and microgrid-to-grid power transactions, enabling them to collectively share their storage and renewable energy capacity in order to reduce their electricity cost. The storage dispatch commands and the share of local and grid power transactions for the individual microgrids are determined by solving a multi-objective optimization problem over a receding control horizon, using forecasts of the net power demands of the microgrids. This multi-objective optimization is formulated as a lexicographic program, to allow for preferential treatment of groups of microgrids based on pre-assigned priorities. The original optimization model is convex but nonlinear. A linear counterpart of the problem is derived that is suitable for online computation. Numerical simulations with real demand and renewable generation data demonstrate the effectiveness of the proposed strategy in reducing the electricity costs of the microgrids in accordance to their priority in the network.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".