When the Sun Sets on Net Metering: How the Cancellation of Net Metering Impacted the Potential Adoption of Residential Rooftop Solar Photovoltaics in Regina, Saskatchewan
Bibliographic record
Abstract
Rooftop solar photovoltaics will play a role in decarbonizing electricity generation and meeting global climate goals . Policymakers can benefit from understanding how their policy choices impact rooftop solar PV adoption . We conduct a case study of Regina, Saskatchewan to determine the extent to which solar policy changes in that Canadian province have impacted the relative desirability of rooftop solar PV . We assess financial returns that can be achieved in Regina under three policy scenarios : net metering , net billing , and net billing with a capital incentive . We use GIS analysis to identify suitable roofs in Regina and assess any shading that may occur . We calculate hourly capacity factors for these roofs using solar irradiation data , temperature data , and shading factors . We match the simulated solar output results with hourly load data to simulate over 4 million potential roof - load combinations and calculate NPV and net monthly return for each combination . We conduct a telephone survey of 451 Regina residents to assess willingness to install solar at different levels of financial return and compare these results to our solar simulations . Our results indicate that a move from net metering to net billing reduced financial returns from rooftop solar and lowered solar potential from 129 Gigawatt- hours ( GWh ) per year to 99 GWh / yr in Regina. The introduction of a capital incentive grant by the federal government has helped increase solar potential upwards to 120 GWh / yr . The capital incentive grant may also help overcome high discount rates by providing a larger upfront benefit to households that install solar.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".