Exploring energy grid resilience: The impact of data, prosumer awareness, and action
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
The transition of energy grids toward future smart grids is challenging in every way: politically, economically, legally, and technically. While many aspects progress at a velocity unthinkable a generation ago, one aspect remained mostly dormant: human electricity consumers. The involvement of consumers thus far can be summarized by two questions: "Should I buy the eco-friendly appliance? Will solar pay off for me?" However, social and psychological aspects of consumers can profoundly contribute to resilient smart grids. This vision paper explores the role of active consumer-producers (prosumers) in the resilient operation of smart energy grids. We investigate how data can empower people to become more involved in energy grid operations, the potential of heightened awareness, mechanisms for incentives, and other tools for enhancing prosumer actions toward resilience. We further explore the potential benefits to people and system when people are active, aware participants in the goals and operation of the system.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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 it