Using Thermal Energy Storage to Relieve Wind Generation Curtailment in an Island Microgrid
Bibliographic record
Abstract
The uncertainty and intermittency of the available wind resource in nature would potentially cause wind generation curtailment when the flexibility of the integrated power grid is limited, especially in small-scale microgrids for islands. In this paper, an optimal configuration method is proposed to use thermal energy storage (TES) to relieve wind generation curtailment in an island microgrid. The thermal network is modeled along with the electrical network to utilize its regulation capability, while TES is introduced as an additional flexibility resource. The detailed cost models of combined heat and power (CHP) units and TES are presented to realize the objective of minimizing the overall operating cost. The performance of TES in improving wind power utilization is firstly validated by using an electrical boiler (EB) as a benchmark and further analyzed under different scenarios considering the growths of wind power capacity, electrical load, and heat load. The effectiveness of the proposed method is validated using real-world data obtained from the practical island microgrid.
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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 | 0.000 | 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) | 0.001 | 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".