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Record W4399274492 · doi:10.52005/ijeat.v7i1.101

Financial Analysis of 30.7 kW On Grid Rooftop PLTS in BLK Sukabumi Regency

2024· article· en· W4399274492 on OpenAlexaboutno aff
Marina Artiyasa, Ajat, Gina Syabani Yuda

Bibliographic record

VenueINTERNATIONAL JOURNAL ENGINEERING AND APPLIED TECHNOLOGY (IJEAT) · 2024
Typearticle
Languageen
FieldEngineering
TopicEngineering and Technology Innovations
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessGridFinanceMathematics

Abstract

fetched live from OpenAlex

The use of solar energy as a solar power plant (PLTS) has increasingly developed and received attention in the last few decades. BLK Sukabumi Regency has a building roof that has the potential to be used as a rooftop PLTS, so it can reduce electricity bills. This research aims to financially analyze the integration of rooftop solar PV at the Sukabumi Regency Job Training Center (BLK). In this research, planning and design of a rooftop PLTS with a capacity of 30.7 kW was carried out using Canadian Solar 320 W solar panels and an ICA Solar 30 kW inverter. The analysis results show that the construction of this rooftop PLTS requires initial investment costs of IDR 300,000,000.00 with annual operational costs reaching IDR 35,278,070.00 and total operational and maintenance costs for 20 years reaching IDR 558,453,870.40. Apart from that, this project has a Net Present Cost (NPC) value of IDR 894,907,600.00 with a payback period of approximately 12 years. After integration with Rooftop PLTS, electricity tariffs succeeded in decreasing by around 30% from IDR 900/kWh to IDR 630.64/ kWh, with a reduction in energy costs from IDR 63,370,935.00/year to 30,615,359.59/year. Based on the results of this research, the relevant suggestions are: implementing a 30 kW rooftop PLTS in BLK Sukabumi Regency as a step towards more sustainable use of renewable energy; conduct further feasibility studies to find alternative components such as solar panels or inverters that are more economical without sacrificing system performance; and consider utilizing renewable energy in other locations on a larger scale, such as government buildings or large industries, to reduce dependence on fossil energy sources.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.036
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.003
GPT teacher head0.203
Teacher spread0.200 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2024
Admission routes1
Has abstractyes

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