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Record W2952146473 · doi:10.5539/enrr.v9n3p1

Micro Combined Heat and Power Systems – Evaluation of a Sample Application

2019· article· en· W2952146473 on OpenAlexvenueno aff
Anayo Ezeamama, E. G. Albrecht

Bibliographic record

VenueEnvironment and Natural Resources Research · 2019
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsPayback periodBoiler (water heating)ElectricityEnvironmental scienceNatural gasInvestment (military)Electricity generationEnvironmental economicsOperations managementProcess engineeringComputer scienceWaste managementEconomicsPower (physics)EngineeringProduction (economics)Microeconomics

Abstract

fetched live from OpenAlex

The growing need for a secure, cost-effective, less polluting and efficient form of energy has contributed to an increasing interest in the use of micro combined heat and power (MCHP) systems. In this paper, the environmental performance and economic feasibility of a 1 kWe internal combustion engine (ICE) MCHP system in a one-family house was assessed and compared with the baseline scenario were residential energy demands are met with grid electricity and natural gas fired condensing boilers. The result of the analysis shows that MCHP systems present opportunities for savings in energy costs. Based on a social discount rate (SDR) of 5 % and a calculated 3259 operating hours, a simple payback period of about 4.8 years was derived as the time needed to recover the extra investment cost of the ICE unit. The result of the sensitivity analysis reveals that, both the running hours and price of electricity have significant effects on the payback period of the project. Considering the end of useful life period of the systems, MCHP offer a good replacement for conventional gas boilers of 90 % efficiency. However, their high initial costs (when compared to high efficiency condensing boilers), could be seen as the major factor hampering market diffusion. Also, considering the optimal environmental benefits, MCHP system produced more on-site CO2 emissions in reference to the condensing boiler but generally, annual CO2 emission is reduced by about 38 % when compared to the overall separate generation of heat and power scenario.

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)0.001
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: Empirical
Teacher disagreement score0.137
Threshold uncertainty score0.210

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 head0.015
GPT teacher head0.255
Teacher spread0.240 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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