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Record W4224125781 · doi:10.3390/en15082938

Recent Advances in Small-Scale Carbon Capture Systems for Micro-Combined Heat and Power Applications

2022· article· en· W4224125781 on OpenAlexafffund
Wahiba Yaïci, Evgueniy Entchev, Michela Longo

Bibliographic record

VenueEnergies · 2022
Typearticle
Languageen
FieldEngineering
TopicCarbon Dioxide Capture Technologies
Canadian institutionsNatural Resources Canada
FundersOffice of Energy Research and DevelopmentNatural Resources Canada
KeywordsProcess engineeringCogenerationEnvironmental scienceFossil fuelOrganic Rankine cycleCarbon capture and storage (timeline)Prime moverCombustionElectricity generationIntegrated gasification combined cycleWaste heatCombined cycleWaste managementTurbineEngineeringClimate changeMechanical engineeringHeat exchangerPower (physics)Chemistry

Abstract

fetched live from OpenAlex

To restrict global warming and relieve climate change, the world economy requires to decarbonize and reduce carbon dioxide (CO2) emissions to net-zero by mid-century. Carbon capture and storage (CCS), and carbon capture and utilization (CCU), by which CO2 emissions are captured from sources such as fossil power generation and combustion processes, and further either reused or stored, are recognized worldwide as key technologies for global warming mitigation. This paper provides a review of the latest published literature on small-scale carbon capture (CC) systems as applied in micro combined heat and power cogeneration systems for use in buildings. Previous studies have investigated a variety of small- or micro-scale combined heat and power configurations defined by their prime mover for CC integration. These include the micro gas turbine, the hybrid micro gas turbine and solid-state fuel cell system, and the biomass-fired organic Rankine cycle, all of which have been coupled with a post-combustion, amine-based absorption plant. After these configurations are defined, their performance is discussed. Considerations for optimizing the overall system parameters are identified using the same sources. The paper considers optimization of modifications to the micro gas turbine cycles with exhaust gas recirculation, humidification, and more advanced energy integration for optimal use of waste heat. Related investigations are based largely on numerical studies, with some preliminary experimental work undertaken on the Turbec T100 micro gas turbine. A brief survey is presented of some additional topics, including storage and utilization options, commercially available CC technologies, and direct atmospheric capture. Based on the available literature, it was found that carbon capture for small-scale systems introduces a large energy penalty due to the low concentration of CO2 in exhaust gases. Further development is required to decrease the energy loss from CC for economic feasibility on a small scale. For the micro gas turbine, exhaust gas recirculation, selective gas recirculation, and humidification were shown to improve overall system economic performance and efficiency. However, the highest global efficiencies were achieved by leveraging turbine exhaust waste heat to reduce the thermal energy requirement for solvent regeneration in the CC plant during low- or zero-heating loads. It was shown that although humidification cycles improved micro gas turbine cycle efficiencies, this may not be the best option to improve global efficiency if turbine waste heat is properly leveraged based on heating demands. The biomass-organic Rankine cycle and hybrid micro gas turbine, and solid-state fuel cell systems with CC, are in early developmental stages and require more research to assess their feasibility. However, the hybrid micro gas turbine and solid-state fuel cell energy system with CC was shown numerically to reach high global efficiency (51.4% LHV). It was also shown that the biomass-fired organic Rankine cycle system could result in negative emissions when coupled with a CC plant. In terms of costs, it was found that utilization through enhanced oil recovery was a promising strategy to offset the cost of carbon capture. Direct atmospheric capture was determined to be less economically feasible than capture from concentrated point sources; however, it has the benefit of negative carbon emissions.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.952
Threshold uncertainty score0.589

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.005
GPT teacher head0.193
Teacher spread0.188 · 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 designNot applicable
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

Citations11
Published2022
Admission routes2
Has abstractyes

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