The Challenges of Designing and Building a Net Zero Energy Home in a Cold High-Latitude Climate
Bibliographic record
Abstract
Edmonton, Canada is far from the equator at 53°34' N latitude – closer to the pole than Tasmania – with winter design temperatures of -32°C and a winter solstice with only 7.5 hours of daylight. This presented significant technical challenges to an interdisciplinary group working at designing a ‘net-zero’ energy house, a house that produces as much energy as it consumes over a year. Though there is an abundance of solar energy in the spring and summer, the key design challenges come in winter with cold temperatures, the greatest demands for space and water heating and domestic electricity, and short days with sun angles within 13° of the horizon. A number of systemic challenges and barriers to the wide-spread implementation of solar and energy efficiency technologies in residential, commercial and industrial sectors exist that are related to municipal, provincial and national policies. These barriers will be similar in other Canadian cities and cities around the world. Examples include subsidised utility energy prices, little value given to environmental benefits, building code restrictions, planning restrictions, lack of simple access to the electrical grid, lack of qualified design professionals, technicians and trades, lack of expertise in an integrated design process, lack of appropriate design software, lack of building-integrated solar products, untested energy efficient products and processes, and products focussed on buildings with large energy consumption. This paper provides an overview of how the technical challenges in designing and building the Riverdale NetZero house, which will be completed and operational by 2008 April, were overcome. It will also provide an overview of the policy barriers that are being encountered in the implementation of net zero energy technologies including recommendations to mitigate or remove those barriers.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".