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Feasibility Analysis of a Solar Water Pumping System in Pakistani Conditions: A Case Study

2020· article· en· W3107734641 on OpenAlexafffund
Usman Ashraf, M. Tariq Iqbal

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhotovoltaic systemWater pumpingCapital costWork (physics)Power (physics)Environmental scienceSoftwareEngineeringComputer scienceAutomotive engineeringElectrical engineeringMechanical engineeringPhysicsOperating system

Abstract

fetched live from OpenAlex

In this paper, a feasibility and cost analysis of a PV based solar water pumping system is conducted for Pakistani conditions. A site was selected (Mustafa Research Farm) which is located at Wasti Jiuan Shah Sadiqabad, Rahim Yar Khan Pakistan. It is around 96.97 hectares, which is watered by 5 pumping systems. For this area, an optimized system was designed using HOMER Software, load for one of the pumping system was found to be 7.412kW. After simulation, the system requirement came out to be 56.8kW capacity for PV panels, a power converter requirement of 8.34kW and 270, 12V 105Ah batteries. Overall, initial capital cost of the proposed system was found to be $129,920. At the end of the paper, the proposed feasible system details and possible future work are discussed.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.750
Threshold uncertainty score0.974

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.044
GPT teacher head0.310
Teacher spread0.266 · 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 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

Citations1
Published2020
Admission routes2
Has abstractyes

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