Real-Time Emulation of Residential Buildings by Hardware Solution of Multi-Layer Model
Bibliographic record
Abstract
Building modeling and consumption analysis are important elements of smart grid applications. The models of residential buildings in Nordic countries, where multi-layer slabs are mandatory to meet energy efficiency requirements, the modeling task becomes particularly challenging. In fact, the complexity of the detailed model rises as the number of layers and thermal zones increases. In some cases, this situation limits the implementation of model-based predictive control where the computation time for execution of the model must be as short as possible to achieve optimized loop time performance. To that end, this paper proposes the development of a modular, accurate and flexible real-time multi-zone and multi-layer building emulation system representing the dynamic thermal-electric behavior of residential buildings. The proposed hardware implementation architecture includes space and water heating systems, which are the main consuming loads in Nordic countries. The emulation system can perform in accelerated simulation or in real-time modes, either for one building or for a virtual park of buildings. Experimental validation using measurement data of occupied Canadian buildings with different insulation characteristics and using a hardware-in-the-loop configuration has permitted to corroborate the usefulness of the proposed emulation system.
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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".