On the Modelling and Analysis of Converting Existing Canadian Residential Communities to Net-Zero Energy
Bibliographic record
Abstract
Rising energy costs and international pressure has motivated governments and homeowners to reduce the energy consumption and greenhouse gas (GHG) emissions of new and existing dwellings.A popular technical approach to this problem is the adoption of net-zero energy targets, which can achieve substantial energy and GHG emissions reductions.Often focused on new builds, there is growing interest in retrofitting existing buildings to net-zero.Addressing existing stock is essential since they will continue to be a significant portion of the building stock for several decades.Net-zero is not limited to single buildings, and potential benefits of communityscale retrofit projects include greater economic viability and economies of scale.However, challenges faced by such projects include few demonstrations in practice, and the need of detailed analytical models to analyze techno-economic feasibility.Another challenge is the lack of consensus on formal net-zero definitions.This research was conducted to explore the feasibility and performance of retrofitting Canadian residential communities to net-zero, and the impact of netzero definition on design.To meet this objective, a new modelling approach was developed which builds upon the detailed and validated Canadian Hybrid Residential End-Use Energy and GHG Emissions Model (CHREM).A new Canadian residential appliance and lighting bottom-up model was developed and integrated into CHREM which realistically captures the behaviour, variability and aggregate electrical demands of communities.Building envelope retrofit models, ground-source heat pump (GSHP) space heating, and heat pump hot water models were incorporated into CHREM.A new methodology was developed to estimate the impact of envelope retrofits on airtightness.iii Retrofit community-scale energy systems considered included solar thermal and photovoltaic (PV) systems, district heating and thermal energy storage, and microturbine cogeneration.Detailed models of these systems were developed in the TRNSYS energy simulation tool.An optimization algorithm was used to determine the cost-optimal net-zero solutions for representative residential communities.Commonly used site and source net-zero energy definitions were considered.The results indicate that deep envelope upgrades and PV and GSHP system retrofits have potential to achieve net-zero and significant GHG reductions.The results also indicate that site net-zero likely realizes more GHG reductions compare to source net-zero.It has been my pleasure to have spent the last few years working and studying at Carleton.I have learned and grown so much, and met so many kind, wonderful, and intelligent people.I am eternally grateful to my supervisors Dr. Ian Beausoleil-Morrison and Dr. V. Ismet Ugursal for taking me on as a student.Their mentorship, encouragement, and support in this endeavour has been incredible.While I am happy to be completing my studies,
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".