Assessing vulnerability to energy poverty through occupant-centric building simulations
Bibliographic record
Abstract
Energy poverty is a global issue that exists even in developed countries such as Canada. As of today, it is still a challenge to understand how building characteristics and diversity of occupants needs influence the risk of energy poverty. The objective of this paper is to develop a new framework to assess the risk of energy poverty by combining a probabilistic occupant behaviour model, a building energy model, and an energy poverty evaluation method. Monte Carlo simulations of 3,000 occupant profiles yielded energy rate distributions among households potentially occupying a specific dwelling, which can then be compared to recognized energy poverty thresholds (2M method). This work was repeated for three types of dwellings (average, code-compliant, and high-performance) and different energy rates. The study findings indicate that one-person households remain the most vulnerable to energy poverty within the simulated population. The risk of energy poverty is substantially heightened in buildings with lower energy performance. With a Market Basket Measure income, the fraction of one-person households facing energy poverty is 53.68% in the average-performance building and reduces to 13.73% and 0.12% in code-compliant and high-performance buildings, respectively. Energy poverty risk is also very sensitive to energy price variation and household annual income. It was also found that households with a Market Basket Measure income that were classified as not facing energy poverty shared distinct features compared to those who did (e.g., lower heating set-point temperature). The paper offers a method to help building designers and policy-makers to better consider energy poverty issues. • Monte Carlo simulations are carried out to assess risks of energy poverty. • The design of residential buildings is an important determinant of energy poverty. • Smaller households are more vulnerable to energy poverty. • Energy poverty in lower-performance buildings is more sensitive to energy rates. • Behaviors that prevent energy poverty typically lead to more discomfort.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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 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".