Assessing the possibility of using wind energy in the East-South-Eastern part of Turkmenistan

The paper considers the assessment of the energy potential of wind energy in the eastern part of Turkmenistan, namely for the Koytendag district, various combinations of wind power plants are considered. It was determined that the installation of two wind power plants with a capacity of 0.75 MW does not cover the consumption of electricity. It was revealed that the minimum deficit is observed in February (12.6%), and the maximum in September (78.6%). It was analyzed that only in January there is an excess (12%). It was revealed that the installation of two wind power plants with a capacity of 1.5 MW gives an excess of 40% in December to 134% in March of energy consumed. The calculations made for the city of Atamurat considered various combinations of wind power plants, and as a result it was found that the installation of two wind power plants with a capacity of 0.75 MW each also does not cover consumption. It was found that for this case the minimum deficit is observed in July (16.5%), and the maximum in September (77.2%), and the maximum in January (2%) and March (17%). It was determined that the installation of two wind power plants with a capacity of 1.5 MW provides from 48.9% in August to 149.4% in March of the consumed amount. It is proposed as the optimal option for both regions to install one wind power plant with a capacity of 0.75 MW and one 1.5 MW with an output voltage of 690 V.

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-04-08
DOI
https://doi.org/10.1051/e3sconf/202562303004/pdf
Primary Topic
Ocular Surface and Contact Lens
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Assessing the possibility of using wind energy in the East-South-Eastern part of Turkmenistan

Springer Link (Chiba Institute of Technology)
Ocular Surface and Contact Lens
article

Assessing the possibility of using wind energy in the East-South-Eastern part of Turkmenistan

article en

Abstract

The paper considers the assessment of the energy potential of wind energy in the eastern part of Turkmenistan, namely for the Koytendag district, various combinations of wind power plants are considered. It was determined that the installation of two wind power plants with a capacity of 0.75 MW does not cover the consumption of electricity. It was revealed that the minimum deficit is observed in February (12.6%), and the maximum in September (78.6%). It was analyzed that only in January there is an excess (12%). It was revealed that the installation of two wind power plants with a capacity of 1.5 MW gives an excess of 40% in December to 134% in March of energy consumed. The calculations made for the city of Atamurat considered various combinations of wind power plants, and as a result it was found that the installation of two wind power plants with a capacity of 0.75 MW each also does not cover consumption. It was found that for this case the minimum deficit is observed in July (16.5%), and the maximum in September (77.2%), and the maximum in January (2%) and March (17%). It was determined that the installation of two wind power plants with a capacity of 1.5 MW provides from 48.9% in August to 149.4% in March of the consumed amount. It is proposed as the optimal option for both regions to install one wind power plant with a capacity of 0.75 MW and one 1.5 MW with an output voltage of 690 V.

Springer Link (Chiba Institute of Technology)
Affordable and clean energy
Openalex Percentile: Top 44%
Ocular Surface and Contact Lens
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.