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Record W3138465449 · doi:10.33805/2576-8484.189

Technical and Economical Feasibility Analysis on Household-Scale Rooftop Solar Power Plant Design with On-Grid System in Semarang City

2021· article· en· W3138465449 on OpenAlexaboutno aff
Jaka Windarta, Singgih Saptadi, Denis Denis, Adi Satrio Dimas

Bibliographic record

VenueEdelweiss Applied Science and Technology · 2021
Typearticle
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsPayback periodInternal rate of returnPhotovoltaic systemNet present valueGrid parityEnvironmental scienceSolar powerPower stationEngineeringElectrical engineeringPower (physics)Production (economics)PhotovoltaicsEconomics

Abstract

fetched live from OpenAlex

Utilizing rooftops as a solar power plant system on the grid can be an effective and efficient solution to reduce electricity bills. This research aims to design and analyze the potential of 1215 Wp solar power plant rooftop with on grid system household scale in terms of techno economy. Using each of the two alternatives to the main components of solar panels and inverters, there were 4 variations of the component configuration design in this study. Variation 1 uses Canadian solar panels with solax inverters. Variation 2 uses Canadian solar panels with so far inverters. Variation 3 uses risen solar panels with solax inverters. Variation 4 uses risen solar panels with sofar inverter. Through PVSyst 6.43 software, with an average radiation average of 5.48 kWh/m2/day, the potential energy production of each variation of 1215 Wp rooftop solar power plant household scale are 1873 kWh, 1893 kWh, 1865 kWh and 1885 kWh. The investment cost of 1215 Wp rooftop solar power plant ranges from IDR25,220,000-IDR27,020,000 with Net Present Value ranges from IDR15,309,805- IDR17,421,839, Benefit Cost Ratio ranges from 1,489-1,588, Payback period ranges from 10.38 – 11.02 years and Internal Rate of Return value ranges from 8.8-9.56%.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.577
Threshold uncertainty score0.869

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
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 head0.018
GPT teacher head0.226
Teacher spread0.207 · 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 designBench or experimental
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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueEdelweiss Applied Science and TechnologySame topicPhotovoltaic System Optimization TechniquesFrench-language works237,207