MétaCan
Menu
Back to cohort
Record W4225651253 · doi:10.4236/ti.2022.132003

Applying Geographic Information System (GIS) for Solar Power Plants Site Selection Support in Makkah

2022· article· en· W4225651253 on OpenAlexvenueno aff
Abdulrahim Bayounis, Tarek Eldamaty

Bibliographic record

VenueTechnology and Investment · 2022
Typearticle
Languageen
FieldComputer Science
TopicSolar Radiation and Photovoltaics
Canadian institutionsnot available
Fundersnot available
KeywordsRenewable energyGeographic information systemSite selectionElectricitySolar energyEnvironmental scienceElectricity generationPhotovoltaic systemEnergy planningSolar powerComputer scienceEnvironmental resource managementEnvironmental economicsGeographyPower (physics)Remote sensingEngineering

Abstract

fetched live from OpenAlex

Solar energy is one of the most important components of renewable energy, which constitutes an important source of clean energy in many fields, especially water desalination and electricity generation. With the increase in electricity consumption in the Kingdom of Saudi Arabia at an annual rate of 5%, the National Initiative for the production of water and electricity was launched. The current study aims to apply a multi-standard GIS method to determine the most appropriate spatial sites for solar energy collection in the Makkah Administrative District. A set of conditions and criteria have been relied upon, whether planning criteria, environmental criteria, or an environmental criterion, to obtain a digital appropriate model that shows the best sites for constructing solar power plants. The study determined the required criteria by relying on literary studies and creating a digital geographic database for these requirements, and then integrating these requirements into an integrated geographic information system in order to obtain a spatial fit model. The results of the suitability indicate that all areas of Makkah Al-Mukarramah are suitable for the solar energy project with an appropriate percentage ranging between 30% and 80%. These results are promising for the renewable energy sector in Makkah Al-Mukarramah and should be taken into consideration. By analyzing these spatial sites and their degrees of suitability to standards, it was found that the lands that are characterized by an adequate share of more than 80% have an area of about 4000 square kilometers with a percentage of 3% of the total suitable lands. These highly suitable areas are concentrated on the governorates of the Makkah Al-Mukarramah Administrative Region, where the Taif governorate comes in the first place with 35% of the total area, followed by the two governorates of Turbah with 24%, and the Rania governorate with 14%. A digital map was made showing the spatial distribution of suitable lands for solar energy projects in the Makkah Al-Mukarramah Administrative Region. The study recommended applying the obtained results in the national plan for renewable energy sources in the Kingdom of Saudi Arabia.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.879
Threshold uncertainty score0.330

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.008
GPT teacher head0.205
Teacher spread0.197 · 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 designTheoretical or conceptual
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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueTechnology and InvestmentSame topicSolar Radiation and PhotovoltaicsFrench-language works237,207