MétaCan
Menu
Back to cohort
Record W4402169432 · doi:10.3390/en17174425

Positive Energy Districts: Fundamentals, Assessment Methodologies, Modeling and Research Gaps

2024· article· en· W4402169432 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEnergies · 2024
Typearticle
Languageen
FieldEngineering
TopicIntegrated Energy Systems Optimization
Canadian institutionsConcordia University
FundersConcordia UniversityCanada Excellence Research Chairs, Government of CanadaEuropean Commission
KeywordsEnvironmental scienceEngineering

Abstract

fetched live from OpenAlex

The definition, characterization and implementation of Positive Energy Districts is crucial in the path towards urban decarbonization and energy transition. However, several issues still must be addressed: the need for a clear and comprehensive definition, and the settlement of a consistent design approach for Positive Energy Districts. As emerged throughout the workshop held during the fourth edition of Smart and Sustainable Planning for Cities and Regions Conference (SSPCR 2022) in Bolzano (Italy), further critical points are also linked to the planning, modeling and assessment steps, besides sustainability aspects and stakeholders’ involvement. The “World Café” methodology adopted during the workshop allowed for simple—but also effective and flexible—group discussions focused on the detection of key PED characteristics, such as morphologic, socio-economic, demographic, technological, quality-of-life and feasibility factors. Four main work groups were defined in order to allow them to share, compare and discuss around five main PED-related topics: energy efficiency, energy flexibility, e-mobility, soft mobility, and low-carbon generation. Indeed, to properly deal with PED challenges and crucial aspects, it is necessary to combine and balance these technologies with enabler factors like financing instruments, social innovation and involvement, innovative governance and far-sighted policies. This paper proposes, in a structured form, the main outcomes of the co-creation approach developed during the workshop. The importance of implementing a holistic approach was highlighted: it requires a systematic and consistent integration of economic, environmental and social aspects directly connected to an interdisciplinary cross-sectorial collaboration between researchers, policymakers, industries, municipalities, and citizens. Furthermore, it was reaffirmed that, to make informed and reasoned decisions throughout an effective PED design and planning process, social, ecological, and cultural factors (besides merely technical aspects) play a crucial role. Thanks to the valuable insights and recommendations gathered from the workshop participants, a conscious awareness of key issues in PED design and implementation emerged, and the fundamental role of stakeholders in the PED development path was confirmed.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.860
Threshold uncertainty score0.625

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.059
GPT teacher head0.352
Teacher spread0.293 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it