Achieving 100% Renewable and Self-Sufficient Electricity in Impoverished, Rural, Northern Climates: Case Studies from Upper Michigan, USA
Bibliographic record
Abstract
The development of 100% renewable electricity (RE) systems play a pivotal role in ensuring climate stability. Many municipalities blessed with wealth, an educated and progressive citizenry, and large RE resources, have already reached 100% RE generation. Impoverished municipalities in unwelcoming environments both politically and climatically (e.g., northern latitudes with long, dark winter conditions) appear to be incapable of transitioning to renewables. This study challenges that widespread assumption by conducting a detailed technical and economic analysis for three representative municipalities in the Western Upper Peninsula of Michigan. Each municipality is simulated with their own hourly electricity demand and climate profiles using an electrical supply system based on local wind, solar, hydropower, and battery storage. Sensitivities are run on all economic and technical variables. Results show that transition to 100% RE is technically feasible and economically viable. In all baseline scenarios, the 100% RE systems produced a levelized cost of electricity up to 43% less than the centralized utility rates, which are predominantly fueled by gas and coal. Current policies, however, prevent such self-sufficient systems from being deployed, which are not only detrimental to the global environment, but also aggravate the economic depression of such regions. Potential energy savings advance the prohibitive energy justice principle.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".