Analysis of PV-Diesel Hybrid Microgrids for Small Canadian Arctic Communities
Bibliographic record
Abstract
Most Canadian remote communities are supplied electricity partly or wholly generated by diesel generators, which results in high electricity costs mostly due to the cost of transporting fuel to the remote locations. A large portion of the financial budget from the government or local community is allocated to cover the cost of diesel electricity generation. Renewable energy integration can substantially reduce the cost of electricity generation and greenhouse gases (GHGs) emissions in these remote communities. The annual solar photovoltaic (PV) potential for these northern arctic communities ranges from 850 to 1150 kWh/kWp; therefore, a significant portion of the community energy requirement can be supplied by the PV system. This article presents the impact of PV integration on the system's annual performance and project economic aspects of small remote northern microgrids for integrating varying penetration levels of centralized PV systems. The modeling of a typical PV-diesel hybrid system considering the electrical performance, emissions, and economics of various generation sizes and control strategies has been addressed. The methodology presented in this article can help quantify the PV energy integration limit (without any spill/curtailment) and economic feasibility of new PV system integration in current arctic microgrids.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".