On the Value of Saved Power in net-zero North-Eastern America
Why this work is in the frame
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Bibliographic record
Abstract
We compute the Value of Saved Power: the value of replacing electricity by efficiency measures, delivering the same energy service. The way one would replace the cost of thousands of kilowatthours for heating, by the cost of insulating a house. Our analysis is especially relevant in an energy transition era, where power prices are poised to increase under two factors: increased demand due to electrification, and decarbonization of the power system. In contrast to virtually all previous studies on the “value of efficiency”, we compute a marginal cost of power that accounts for the transition effect. This, we argue, is the appropriate cost to use. The impact is substantial. At the scale of North Eastern North America, a decarbonized, least-cost power system for 2040 is modeled, and the marginal cost of electricity is derived: the cost of the most expensive terawatt-hours. Our model expands generation, interregional transmission, and storage capacities in a cost-optimal fashion, leveraging a full-scale, one-year, hourly operations model. In the various scenarios explored, positive value to saving power is found in all but extreme cases; and in what we consider to be the most probable scenarios, we find enormous value, of the order of 10 to 80 cents per kWh. Furthermore, since we conservatively assume optimal cooperation between states and provinces in developing and running the power system, the value of saved power could in fact be underestimated. For a power system undergoing major transformation (with loads up to doubling due to electrification, and power-based net emissions curbed to nil), our results underscore the importance of computing the value of saved power by using the marginal cost of power including expansion costs; not the current power costs. To our knowledge, ours are the first estimates of the values of saved energy for a transitioned, high-load, decarbonated power system.
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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 | 0.001 |
| 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