User-Related Issues in Design and Use of Smartgrids Seen as Complex Sociotechnical Systems: Example of the VERTPOM Project
Bibliographic record
Abstract
The impact of human activities on the environment is no longer to be demonstrated today and concerns many fields. With a view to environmental protection, applied to global warming limitation and fossil fuels preservation, Smartgrids are currently emerging, especially, under the impetus of European and French legislation. In emerging technologies, end-user-related issues, articulated with the design process, continue to raise conceptual, methodological and operational questions. The perspective of complex sociotechnical systems is useful for Smartgrids and to underline the necessary multidisciplinary approach to design. Yet raised for decades, the articulation of multidisciplinary approaches in the design of complex systems still questions fundamental problems today. These questions are all more unresolved in the context of innovative technologies such as Smartgrids. The objective of this paper is to propose 1) a conceptual reflection applied to the design of these Smartgrids seen as emerging sociotechnical systems, and 2) a case study by illustrating with the VERTPOM project. On the one hand, we discuss four fundamental points in user-centered design of Smartgrids: we describe the legislative impulses for the rollout of smart metters and the emergence of Smartgrids, we highlight the supplier/consumer synergy that is essential for efficient energy management, we explain the importance of adapting systems to the wide public in domestic, professional and public situations in the context of consumer control of energy demand, and we address the issue of the more traditional field of supervision and control of complex dynamic processes by operators. On the other hand, we present the VERTPOM project aiming at developing a set of digital tools for energy management and energy efficiency in order to make a positive energy territory that produces more energy than it consumes by introducing the project and its actors and explaining how design acceptable Smartgrids for consumers and operators of energy suppliers.
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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 | 0.010 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".