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Record W4322208014 · doi:10.1016/j.prime.2023.100133

Sustainability and carbon neutrality in UK's district heating: A review and analysis

2023· review· en· W4322208014 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.

Bibliographic record

Venuee-Prime - Advances in Electrical Engineering Electronics and Energy · 2023
Typereview
Languageen
FieldEngineering
TopicIntegrated Energy Systems Optimization
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSustainabilityEnvironmental economicsGreenhouse gasCarbon neutralityGovernment (linguistics)Dominance (genetics)Environmental resource managementBusinessEnvironmental scienceEngineeringEconomics

Abstract

fetched live from OpenAlex

The UK is currently approaching a critical point in the fight against climate change. To achieve carbon neutral by 2050, it is crucial that the way in which buildings are heated are reviewed to determine the most suitable solution. The UK government has acknowledged that district heating (also referred to as heat networks) forms an important part of their plan for future sustainability in heating homes as well as improving energy costs. At present, there are five generations of district heating with distinctive improvements between each. However, research shows a lack of progression with only minor improvements to efficiencies and carbon emissions in the past two decades. Therefore, this paper aimed to review the key technologies and design principles of the low-impact network which shall be implemented into future networks to ensure sustainability and carbon neutral. Furthermore, data were utilised from UK government's ‘Heat Network Project Pipeline’ documents which cover a wide range of projects supported through the development stage by the UK Heat Network Delivery Unit. A statistical analysis was also undertaken to identify popular heat source technologies currently being implemented into the UK networks. Information such as technologies, size and costs were analysed to establish the intercorrelations, which may influence the type of technologies being selected. The results show that 56% of total networks contained Combined Heat and Power (CHP) as a primary heat source, of which over 40% were gas fired CHP, displaying the current dominance of the technology. Overall, it is evident in the UK that, the new networks have been improved from previous generations with a high concentration of renewable energy technologies and heat recovery methods being used. However, there is still a high reliance on natural gas, which does not fulfil the characteristics of a low-impact heating network.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.670
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.006
GPT teacher head0.256
Teacher spread0.250 · 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