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Record W4399303179 · doi:10.2166/wst.2024.149

Status of photovoltaic water pumping systems in Iran: A comprehensive review

2024· review· en· W4399303179 on OpenAlexafffund
Misagh Irandoostshahrestani, Daniel R. Rousse

Bibliographic record

VenueWater Science & Technology · 2024
Typereview
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsÉcole de Technologie SupérieureUniversité du Québec à Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhotovoltaic systemWater pumpingEnvironmental scienceEngineeringElectrical engineeringMechanical engineering

Abstract

fetched live from OpenAlex

This study investigates the current status of photovoltaic water pumping systems (PVWPSs) in Iran, a country endowed with significant solar irradiation potential, notably in its southern and central regions. Despite this potential, there is a scarcity of comprehensive studies on solar water pumping systems within the country. This purpose of this study is to conduct a thorough review of the existing literature to assess the state of solar water pumping in Iran. The adoption of PVWPS across various provinces demonstrates the system's versatility, proving effective in both highly sunny and less irradiated regions. Iran's widespread utilization of PVWPS is attributed to its ample irradiations, even in its northern areas, which possess lower solar irradiance levels. There are limited comprehensive studies encompassing technical, economic, environmental, and social aspects of solar PV water pumping projects in Iran. Most of the research has been conducted during the last few years, indicating an increased recognition of the possible advantages of this technology. Finally, this review provides valuable insights for researchers and farmers, showcasing the benefits of solar PVWPS. It sets the stage for further innovation and implementation in the country's agricultural landscape, emphasizing the need for continued exploration and adoption of this sustainable approach.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.884
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0060.005
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.058
GPT teacher head0.341
Teacher spread0.283 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations8
Published2024
Admission routes2
Has abstractyes

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