A New Bi-Objective Approach for Optimal Sizing of Electrical and Thermal Devices in Zero Energy Buildings Considering Environmental Impacts
Bibliographic record
Abstract
This paper proposes a new bi-objective optimization model, trading-off cost and environmental impacts, for sizing the key electrical and thermal devices in a zero energy building (ZEB), i.e., a building that roughly generates as much renewable energy as it consumes annually. A salient novel feature is the consideration of the environmental impacts, computed through a rigorous life cycle assessment approach, of buying electricity from the grid and manufacturing devices. Furthermore, an enhancement of the proposed model, as compared to the existing models, is to prioritize storing the ZEB excess of energy rather than selling it to the grid. The proposed solution approach of the initial mixed-integer nonlinear programming model relies on McCormick relaxation linearization to obtain a more tractable mixed-integer linear model. An augmented ε-constraint method is applied to solve the obtained bi-objective model. Finally, considering the building owners' willingness-to-pay for environmental impacts, a decision-making criterion is proposed to select the optimal size of the devices among all non-dominated solutions of the Pareto front.
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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".