Holistic and integrated energy system optimization in reducing diesel dependence of Canadian remote Arctic communities
Bibliographic record
Abstract
This dissertation demonstrates novel holistic approaches on how to link policy, clean energy innovations, and robust energy modeling techniques to help build more resilient and cost-effective energy systems for the Canadian Arctic region and remote communities in general. In spite of the diversity among Arctic jurisdictions, various energy issues and challenges are shared pan-territorially in the North. For instance, 53 out of 80 remote communities in the Northern territories rely exclusively on diesel-based infrastructures to generate electricity, with heating oil as their primary source of heat. This critical dependence on fossil fuels exposes the Indigenous peoples and other Canadians living in the North to high energy costs and environmental vulnerabilities which is exacerbated by the local and global catastrophic effects of climate change in the Arctic. Aside from being strong point sources of greenhouse gases and other airborne pollutants, this reliance on carbon-intensive sources of energy elevates risk of oils spills during fuel transport and storage. Further, conventional transportation mode via ice roads is now increasingly unreliable because of the rising Arctic temperatures which is twice the global average rate. As a result, most fuels are being transported by small planes which contribute to high energy costs and fuel poverty rates, or via boats which also increases the risk of oil spills in the Arctic waters. \n \nMethodologically, this thesis presents a multi-domain perspective on how to accelerate energy transitions among Northern remote communities. In particular, a multi-objective optimization energy model was developed in order to capture complex trade-offs in designing integrated electrical and thermal energy systems. In comparison with traditional single-objective optimization approach, this technique offers diversity of solutions to represent multiple energy solution philosophies from various stakeholders and practitioners in the North. A case study in the Northernmost community of the Northwest Territories demonstrates the applicability of this framework - from modeling a range of energy solutions (supply and demand side aspects) to exploring insights and recommendations while taking into account uncertainties. Overall, this dissertation makes a set of contributions, including: (i) Development of a robust energy modeling framework that integrates complex trade-offs and multiple overlapping uncertainties in designing energy systems for the Arctic and remote communities in general; (ii) Extension of previous Arctic studies - where focused has solely been on the electricity sector - by integrating heating technology options in the proposed modeling framework in conjunction with methods on obtaining `high performance' buildings in the North; (iii) Overall energy system performance evaluation when integrating heat and electricity sectors, as well as the role of battery storage systems and diesel generator on facilitating variable renewable energy generation among isolated communities; (iv) Formulation of a community-scale energy trilemma index model which helps design policies that are accelerating (or hindering) energy transitions among remote communities by assessing quantitatively challenges relating to energy security, affordability, and environmental sustainability; (v) Synthesized holistic insights and recommendations on how to create opportunities for Indigenous peoples-led energy projects while discussing interwoven links between energy system operations, relationship building and stakeholders engagement, policy design, and research (energy modeling and analysis). \n \nCollectively, the new methods and recommendations demonstrated herein offer evidence-based decision making and innovative solutions for policy makers, utility companies, Indigenous peoples, and other stakeholders in the Arctic and beyond.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".