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Techno-economic analysis of a combined cooling, heating and power (CCHP) system for a Canadian solar community as a retrofit

2025· article· en· W7092181537 on OpenAlexafffundabout

Bibliographic record

VenueEnergy Conversion and Management · 2025
Typearticle
Languageen
FieldEngineering
TopicThermodynamic and Exergetic Analyses of Power and Cooling Systems
Canadian institutionsToronto Metropolitan University
FundersNatural Resources CanadaNatural Sciences and Engineering Research Council of CanadaToronto Metropolitan University
KeywordsPower (physics)Solar energyEconomic analysisSolar powerPhotovoltaic systemElectricity generation

Abstract

fetched live from OpenAlex

This study proposes technological improvements to the Drake Landing Solar Community (DLSC) through a retrofit energy system integrating an organic Rankine cycle (ORC) and heat pump (HP) to meet year-round demands: district heating (DH), district cooling (DC), domestic hot water (DHW), and borehole thermal energy storage (BTES) charging. Seasonal combined cooling, heating and power (CCHP) system for summer and combined heating and power (CHP) system for winter operations are financially modeled, yielding a simple payback period of 25.8 years and a discounted payback period of 35 years at 3 % discount rate. The levelized cost of energies (LCOE) are 1.02 US$/kWh for DHW, 0.99 US$/kWh for DH, and 1.38 US$/kWh for DC. Major technological improvements include: 1) elimination of excess heat rejection from solar loop improving solar energy utilization, 2) generation of electricity through an ORC leading to potential grid independence, and 3) elimination of natural gas consumption reducing greenhouse gas (GHG) emissions. The proposed system delivers a net annual electricity output of 15,773 kWh, offsets 33.2 tons of GHG emissions, and saves C$5,644/year in carbon tax by 2030.

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.

How this classification was reachedexpand

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.864
Threshold uncertainty score0.915

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.004
GPT teacher head0.195
Teacher spread0.191 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2025
Admission routes3
Has abstractyes

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