Modeling and energy management of hangar thermo-electrical microgrid for electric plane charging considering multiple zones and resources
Bibliographic record
Abstract
Achieving net zero goals by 2050 is driving an energy transition towards clean electrical energy. Consequently, many initiatives have been proposed aiming to reduce carbon emissions in the building and transportation sectors, focusing, for instance, on the implementation of efficient heating and cooling systems based on heat pumps and the use of electric planes. Microgrids can effectively integrate thermal and electrical energy resources and loads to satisfy customer demands while providing technical, economic, and environmental benefits. Thus, this paper proposes the implementation of a model of a hangar microgrid and its Energy Management System to optimize the dispatch of resources of such thermo-electrical airport grid, using a Model Predictive Control approach to address uncertainties, and including a detailed building thermal model, heat pump modeling for the heating and cooling systems, and battery degradation. The proposed mathematical model of the Energy Management System is applied to a model of a microgrid being developed for a hangar at the Waterloo Wellington Flight Centre in Ontario, Canada, taking into account the specific characteristics of the microgrid’s components, the expected energy consumption of the equipment and the electric plane used for pilot training based on field measurements, and multi-room temperature control requirements, seeking to ensure a reliable and cost-effective operation, while considering the occupants’ comfort in different spaces. The results indicate that the proposed Energy Management System model, featuring multi-room temperature control through multiple thermal resources, can achieve significant savings in operational costs and CO2 emissions compared to a scenario where the microgrid is not deployed and another where a single-room building thermal model with a single heat pump is included. • Modeling of a hangar microgrid with Solar PV, batteries and e-plane charging. • Hangar microgrid Energy Management System (EMS). • Hangar thermal model with multiple rooms and heat pumps versus a single-space model. • Independent dispatch of multiple cooling and heating systems of a hangar building. • Application to a hangar at Waterloo, Ontario, to showcase the microgrid advantages.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".