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Record W4407091678

Grid-Connected PV Systems: Impact Evaluation & Optimal Allocation and Sizing for Losses Minimization and Voltage Improvement (Jordanian Case Study)

2019· article· en· W4407091678 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2019
Typearticle
Languageen
FieldEngineering
TopicOptimal Power Flow Distribution
Canadian institutionsUniversité du Québec
Fundersnot available
KeywordsSizingMinificationGridPhotovoltaic systemComputer scienceReliability engineeringAutomotive engineeringOperations researchMathematical optimizationEngineeringElectrical engineeringMathematicsChemistry
DOInot available

Abstract

fetched live from OpenAlex

Jordan became one of the countries which looking for integrating Photovoltaic energy systems (PV) into power distribution systems. In this study, simulations and analysis were implemented on Irbid District Electrical Company (IDECO) grid to investigate the impact of distributed PV system on the power flow and voltage profile of the distribution network. The impact of different PV generation penetrations on the power flow and voltage profile is compared. Moreover, the impact of the location where PV is installed is investigated. Various test scenarios corresponding to different weather conditions such as solar radiation and temperature are simulated. Finally, Sizing and allocation of the PV system in the tested feeder are optimized according to sensitive of nodes to power losses and voltage improvement. In this paper, CYME power flow software and MATLAB program are used to investigate the results.

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.

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), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.344
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
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 head0.123
GPT teacher head0.497
Teacher spread0.374 · 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