A Novel Hybrid Model to Evaluate the Location of Net-Zero Energy Consumption Building based on Remote Sensing, Analysis Hierarchical Process and Machine learning DOI
Jing Kong, Оrken Mamyrbayev, Zaher Mundher Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬

et al.

Energy, Journal Year: 2025, Volume and Issue: unknown, P. 136477 - 136477

Published: May 1, 2025

Language: Английский

Investigating Land Suitability for PV Farm and Existing Sites Using a Multi-Criteria Decision Approach in Gaziantep, Türkiye DOI Creative Commons
Semih Sami Akay

Applied Sciences, Journal Year: 2025, Volume and Issue: 15(5), P. 2441 - 2441

Published: Feb. 25, 2025

Nowadays, renewable energy facilities are coming to the forefront in order protect nature and prevent climate change. In this context, location-based analyses carried out for most optimal use of resources. This study aims identify suitable locations photovoltaic (PV) farms Gaziantep using Analytical Hierarchy Process (AHP) Geographic Information System (GIS) technologies. The research incorporates various criteria, including solar radiation, land use, slope, aspect, distance road, fault line proximity, powerlines, wind speed evaluate potential sites production. AHP method is applied prioritize these criteria through a pairwise comparison matrix calculate weight values each factor. analysis reveals that approximately 80% Gaziantep’s PV farm installation, with southern region being favorable. Furthermore, between existing installations identified areas highlights high degree alignment, current located classified as or highly suitable. Additionally, it was determined 92% have been established within areas. indicates alignment zones installations, reflecting an effective site selection process based on criteria. concludes GIS-based tool rapid reliable decision-making selection, offering valuable approach future projects similar regions.

Language: Английский

Citations

0

A Novel Hybrid Model to Evaluate the Location of Net-Zero Energy Consumption Building based on Remote Sensing, Analysis Hierarchical Process and Machine learning DOI
Jing Kong, Оrken Mamyrbayev, Zaher Mundher Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬

et al.

Energy, Journal Year: 2025, Volume and Issue: unknown, P. 136477 - 136477

Published: May 1, 2025

Language: Английский

Citations

0