Digitalization & Facility Management: Energy Flexibility of Existing Buildings
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
Future energy systems will require buildings to be able to manage their energy demand and generation in dynamic ways. The technical realization of such energy flexibility in buildings in response to local climate conditions, occupant needs and grid requirements is currently quantified in research and development projects, many of which take place in newly erected buildings as flagships for the related digitalization and seamless automation of technical building services. However, building stock and facility management portfolios tend to consist of existing buildings with differing, highly diverse performance qualities that may pose a problem for generic solutions. The objective of this paper is to highlight potential options, and to sketch an engineering perspective of making existing buildings energy-flexible. For this purpose, on-going work in various control research projects is selected to present issues in (1) the development of a suitable controller, (2) home and building automation design, and (3) building commissioning and diagnostics for future building controls. Non-technical requirements for quality of performance in these cases are summarized. In conclusion, and based on the reviewed projects, a potential strategy for building management is the avoidance of risks and costs associated with the introduction of energy flexibility by using published standards and open protocols for automation, and by documenting their as-operated status in a digital format in all buildings.
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