Güneş enerji panellerinde harita tabanlı uygunluk analizi
Map-based suitability analysis for solar energy panels
Yazar: FATİH ACAR
Danışman: DR. ÖĞR. ÜYESİ HÜSEYİN ESKİ
Sakarya Üniversitesi / Fen Bilimleri Enstitüsü / Bilgisayar ve Bilişim Mühendisliği Ana Bilim Dalı
Derece: Yüksek Lisans, 2024
Konu: Bilgisayar Mühendisliği Bilimleri-Bilgisayar ve Kontrol = Computer Engineering and Computer Science and Control

Özet:
Bu çalışma, güneş enerjisi panellerinin en uygun konumlarının belirlenmesinde
modern CBS tekniklerinin ve dinamik veritabanı kullanımının etkinliğini detaylı bir
şekilde incelemiştir. Çeşitli coğrafi bölgelerden elde edilen verilerin dinamik bir
veritabanında depolanmasıyla, güneş enerjisi potansiyelini etkileyen faktörlerin analiz
edilmesi ve bu faktörlerin güneş enerjisi uygunluğu üzerindeki etkisinin anlaşılması
hedeflenmiştir. CBS fonksiyonları, ilişkili tablolar ve fonksiyonlarla birlikte, her bir
parsel için uygunluk skorlarının üretilmesine olanak sağlamıştır. Bu skorlar, farklı
faktörlerin değerlendirilmesi ve ağırlıklandırılması sürecinde belirlenmiş ve güneş
enerjisi potansiyeli üzerinde önemli bir etkiye sahip olduğu gözlemlenmiştir.
Ağırlıkların ve kriterlerin belirlenmesinde farklı literatür kaynakları ve araştırmalar
göz önüne alınarak araştırmada varsayımsal değerler kullanılmıştır. Analiz sonuçlarına
göre, güneş enerjisi potansiyeli üzerindeki etkili bir şekilde belirlenmesine katkı
sağlamıştır. Özellikle, her bir parsel için en uygun konumların belirlenmesinde önemli
bir rol oynamıştır. Ayrıca, alt sınıfların değerlendirilmesi, analizlerin daha ayrıntılı ve
kapsamlı bir şekilde yapılmasını sağlamıştır. Bu alt sınıflar, analizlerin daha spesifik
ve detaylı bir şekilde gerçekleştirilmesine olanak tanımıştır. PostgreSQL veritabanı ve
PostGIS eklentisinin kullanımı, analizlerin daha etkin bir şekilde gerçekleştirilmesini
sağlamıştır. Bu araçlar, büyük veri setlerinin işlenmesi ve analizlerin
gerçekleştirilmesi sürecinde önemli bir avantaj sağlamıştır. Ayrıca, bu araçlar
sayesinde analiz sonuçları daha kolay erişilebilir ve paylaşılabilir hale gelmiştir. Sonuç
olarak, bu çalışma, güneş enerjisi santralleri için en uygun konumların belirlenmesinde
dinamik veritabanı analizlerinin ve CBS'nin önemini bir kez daha vurgulamaktadır. Bu
çalışmanın sonuçları, sürdürülebilir enerji üretimine katkı sağlamak için daha bilinçli
ve etkili kararlar alınmasına olanak tanımaktadır. Gelecekteki araştırmaların,
analizlerin doğruluğunu artırmak ve belirsizlikleri azaltmak için daha gelişmiş
yöntemlerin ve veritabanı araçlarının kullanılmasına odaklanması gerekmektedir.
Ayrıca, farklı coğrafi bölgelerde benzer analizlerin yapılması ve sonuçların
karşılaştırılması önemlidir, çünkü bu, güneş enerjisi potansiyelinin genel bir anlayışını
sağlayabilir ve bölgesel farklılıkları ortaya koyabilir. Bu tür karşılaştırmalar, güneş
enerjisi potansiyelinin daha etkili bir şekilde değerlendirilmesine ve stratejilerin daha
iyi oluşturulmasına yardımcı olabilir. Son olarak, bu çalışma sadece bir başlangıçtır ve
gelecekte yapılacak olan daha kapsamlı araştırmaların, güneş enerjisi santrallerinin yer
seçimi konusundaki bilgi ve yöntemlerin gelişimine katkı sağlayacağına inanıyoruz.

Abstract:
This thesis provides an in-depth exploration of modern Geographic Information
Systems (GIS) techniques and the use of dynamic databases to identify optimal
locations for solar energy panels. The study focuses on evaluating the potential for
solar energy across different geographical regions by employing dynamic databases to
store and analyze relevant data. By leveraging GIS functions and integrating various
datasets, the study aims to generate suitability scores for each parcel of land, taking
into account multiple factors and their respective weights. These scores are crucial in
understanding the factors that influence solar energy potential and in determining the
most suitable locations for solar panel installations.
The methodology involves a comprehensive literature review to examine the methods
and data used in past studies, particularly focusing on the impact of GIS and database
applications on site selection for solar energy systems. Serbia was selected as the study
area, and a local database architecture was meticulously planned and created. Factors
influencing solar energy suitability were identified in detail for the region, with classes
and subclasses defined for weighted total and weighted product methods. In
determining the weights and criteria, hypothetical values were used in the research by
taking into account different literature sources and research.
Data from various sources were collected, manipulated, and converted into appropriate
formats for analysis. Systematic procedures were established for class and criterion
determination, as well as data manipulation through the database structure. Suitability
analysis algorithms and functions were defined and integrated with the relevant classes
and subclasses to ensure the effective implementation of dynamic database
applications.
A database application function was developed to perform suitability analyses using
polygon data defined within the study area boundaries. The results of these analyses
were evaluated and interpreted based on scores. The PostgreSQL database and
PostGIS extension played a significant role in processing large datasets and conducting
analyses efficiently, making the results more accessible and shareable. The database
structure and GIS functions also provided a foundation for future analyses, facilitating
similar studies.
The introduction highlights the growing sensitivity in the energy sector towards
sustainability and environmental impact, with solar energy panels playing a leading
role among clean and renewable energy solutions. The dynamic changes in the energy
sector have accelerated research and solution-oriented approaches for solar energy
panels. Optimal positioning of these panels is crucial to maximize energy production
by utilizing sunlight most efficiently. The research focuses on identifying the most
suitable locations for solar energy panels through various analyses and methods,
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including GIS analyses and suitability criteria. This information not only enhances
energy efficiency but also minimizes environmental impacts, contributing to more
informed and strategic decision-making for sustainable energy production.
Key criteria in suitability analyses are vital in the optimal positioning process of solar
energy panels. These criteria should balance energy efficiency, economic
performance, and environmental sustainability. Accurate identification of factors
affecting panel performance not only increases energy production but also reduces
environmental impacts. For example, careful assessment of land use is crucial for
preserving natural habitats and increasing public acceptance. These criteria ensure that
energy projects meet not only technical success but also the expectations of various
stakeholders, prioritizing social and environmental compatibility. Effective use of
these criteria is essential for supporting sustainable energy production in the site
selection of solar energy panels.
GIS emerges as a powerful tool in site selection for solar energy panels, offering
comprehensive analyses. By evaluating geographic data in detail, GIS can create
detailed maps that include various factors such as solar energy potential, land slope,
seasonal changes, and shading. These analyses guide the ranking of potential locations
and the identification of the most suitable sites based on established criteria. The
structures of criterion data and their suitability for solar energy panels, along with their
impact on energy production, can be rigorously assessed through GIS analyses. This
information allows for optimized, environmentally and economically sustainable site
selections for solar energy panels. The analytical power of GIS supports strategic
decision-making in the planning and implementation of solar energy projects,
contributing significantly to sustainable energy production.
Various analytical methods and techniques are available to determine the most
effective locations for solar energy panels, with GIS playing a critical role. GIS
evaluates solar radiation potential, topographic features, and land use using remote
sensing and geographic data analysis, helping to identify regions where panels can
achieve the highest efficiency. Multi-criteria decision analysis (MCDA) is another
method used in conjunction with GIS, assessing and weighting various suitability
criteria to determine the most suitable locations. Analyzing solar radiation maps and
meteorological data also proves effective in evaluating panel performance. Integrating
these methods provides a comprehensive strategy for the optimal placement of solar
energy panels, maximizing sustainable energy production.
Solar power plants (GES) consist of numerous solar panels spread over a large area,
producing significant amounts of electricity. These facilities are used for large-scale
electricity production and are typically connected to the power grid. In addition to
many panels, they include supporting components such as inverters, mounting
systems, and monitoring and control equipment. They can cover several hectares or
more and contain hundreds or even thousands of solar panels.
The scope of the thesis involves map-based suitability analysis, multi-criteria decision
analysis, and the use of dynamic databases to identify optimal locations for solar
energy panels. The study evaluates solar energy potential, topographic features, and
land use using GIS's analytical power. Multi-criteria decision analysis methods are
employed to assess and weight different suitability criteria, optimizing the process of
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determining the best locations. By incorporating dynamic databases, the thesis aims to
provide a more effective and dynamic approach to site selection for solar power plants
based on current and real-time data. This comprehensive analytical approach offers a
strategic decision-making tool for the optimal positioning of solar power plants,
contributing to sustainable energy production.
The objective of the thesis is to conduct a detailed analysis of the methods and criteria
used in determining the most suitable locations for solar power plants. This involves
dynamic database usage, criteria scoring, and MCDA, which are critical in the site
selection process for solar power plants. Dynamic databases enable more effective
analyses based on current and real-time data, while criteria scoring and MCDA offer
a strategic approach to combining different factors and determining the best locations.
Another key goal is to evaluate the effectiveness of GIS analyses and other related
techniques in suitability analyses for solar power plants. These analyses provide a
comprehensive strategy for identifying optimal locations by creating detailed maps
that include critical factors such as solar energy potential, land topography, and usage.
Understanding the impact of criteria such as environmental sustainability, economic
suitability, and social acceptance on site selection aims to contribute to more informed
and effective decision-making in the planning and implementation of solar energy
projects.