Economic Impacts of Curtailing Wind Turbine Operations for the Protection of Bat Populations in Ontario
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Wind energy is a growing industry in Canada to meet the demand for a renewable supply of energy. However, wind turbine operation represents a high mortality risk for bat populations, and regulators often require that steps are taken to mitigate this risk. The result is concern among operators about lost revenue potential. This study was, therefore, designed to estimate the theoretical financial impact of curtailing turbine operations to mitigate for bat mortality for all wind farms that were constructed and operating in Ontario, Canada, as of 1 January 2020 (n = 87 wind farms). Empirical data from the Canadian Wind Farm SCADA and meteorological systems are not publicly available; thus, we were compelled to use data from the Canadian Wind Turbine database, the Environment and Climate Change Canada Wind Atlas, and the Independent Electricity System Operator to calculate the total theoretical energy production for all wind turbines in the province using manufacturer power curves and a measure–correlate–predict linear regression method. We estimated the financial impacts for all wind farms on the assumption that operations were curtailed when the Wind Atlas modelled local wind speed was <5.5 m/s between 6 pm of one day and 6 am the following day, between 15 July and 30 September, using the lower and upper limits of power-purchase agreement rates for Ontario wind farms: 115 and 150 CAD/MWh. We used generalized linear modelling to test whether the variability in production loss was predicted based on factors related to turbine design and site wind speeds. We estimated that total annual wind energy production would be reduced from 12.09 to 12.04 TWh if all Ontario wind farms implemented operational curtailment, which is equivalent to a difference of 51.2 GWh, or 0.42%. Production loss was related to turbine cut-in speeds and average site wind speeds recorded between 15 July and 30 September. The estimated profit losses were 6.79 ± 0.9 million CAD compared to estimated earnings of 1.6 ± 0.21 billion CAD, which suggests that mitigating bat mortality may represent a small cost to the industry relative to the conservation benefits for bat populations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 it