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.
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, xxiii 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 xxiv 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.
Except where otherwise noted, this item's license is described as http://creativecommons.org/licenses/by/4.0/
