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Record W2918651364 · doi:10.3390/su11051403

System and Cost Analysis of Stand-Alone Solar Home System Applied to a Developing Country

2019· article· en· W2918651364 on OpenAlexafffund
Chowdhury Akram Hossain, N. Chowdhury, Michela Longo, Wahiba Yaïci

Bibliographic record

VenueSustainability · 2019
Typearticle
Languageen
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsNatural Resources Canada
FundersNatural Resources Canada
KeywordsPhotovoltaic systemRenewable energyElectricityEnvironmental economicsFossil fuelElectricity generationBusinessNatural resource economicsEngineeringEconomicsWaste managementPower (physics)Electrical engineering

Abstract

fetched live from OpenAlex

Power is one of the key requirements for the development of economies and upgrading of standards of living of developing countries. Countries such as Bangladesh depend largely on fossil fuels such as diesel fuel and natural gas to produce the main proportion of their electricity. However, this country’s combination of limited natural gas reserves high fuel prices and escalating costs of transmission and distribution lines has greatly increased the unit cost of electricity generation and it is becoming difficult for customers to pay for electricity. On the other hand, burning fuel causes environmental pollution that leads to global warming which is ultimately responsible for climate change and its devastating consequences. In this study, we have recommended a stand-alone system for the traditional consumption of domestic electric use at residential units in Bangladesh. We have shown a comparison of using the stand-alone photovoltaic (PV) system with the traditional grid connection. Although the initial set-up cost is high, it becomes profitable as people are supplied with electricity, which is being generated from PV as a result minimizing the energy cost from the grid, and in addition, they can later make savings from this system. This paper, therefore, aims at determining the optimum size of the rooftop solar home system that will fulfil all the criteria for powering up electrical appliances at an affordable price. Comparative analysis of both energy systems based on the cost calculation has been performed by means of the Hybrid Optimization of Multiple Energy Renewables (HOMER) software. The validity of this proposal and its usefulness is also analysed.

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)0.002
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.392
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
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 head0.222
Teacher spread0.216 · 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.

Study designObservational
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

Citations70
Published2019
Admission routes2
Has abstractyes

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