An integrated Bayesian Best-Worst Method and GIS-based approach for offshore wind power plant site selection: A case study in North Aegean and Marmara Sea (Türkiye)

Yıl 2023, Sayı: 82, 7 - 22, 30.06.2023

Zekeriya Konurhan , Melih Yücesan , Muhammet Gül

https://doi.org/10.17211/tcd.1214671

Öz

In today’s world, renewable energy sources are in great demand due to the negative effects
of fossil fuels on the environment. Wind power plants are an important renewable
energy source alternative to fossil fuel consumption. Offshore wind farms established in
coastal areas and seas are used effectively in many parts of the world. The wind power
plants, especially in the Northwest region of Turkey and the Aegean coasts, constitute
an important potential. This study selects suitable sites for offshore wind farms in the
Marmara Sea and North Aegean Coasts of Turkey by integrating the Bayesian Best-Worst
method (BWM) and GIS. Bayesian BWM improves the traditional BWM integrating the
preferences of multiple experts. In the study, 17 sub-criteria were determined under
four main criteria of “technical”, “socio-economic”, “environment,” and “location”. Experts’
judgments through the filled enabled the criterion weights to be obtained. The
criteria weights found using the Bayesian-BWM model were integrated into the GIS, and
suitable locations for the offshore wind farm were determined. Accordingly, the study
area off the coasts of Aliağa, Bozcaada, and Gökçeada on the North Aegean coast, and
the part south of the Marmara Sea and the area around Kapıdağ Peninsula are suggested
as suitable areas for wind power plants.

Anahtar Kelimeler

Offshore wind energy, Site selection, Bayesian BWM, GIS

Açık deniz rüzgar enerjisi santrali saha seçimi için entegre bir Bayesian En İyi-En Kötü Yöntemi ve CBS tabanlı yaklaşım: Kuzey Ege ve Marmara Denizi’nde (Türkiye) bir vaka çalışması

Öz

Günümüz dünyasında fosil yakıtların çevreye olan olumsuz etkilerinden dolayı
yenilenebilir enerji kaynakları büyük talep görmektedir. Rüzgâr santralleri, fosil yakıt
tüketimine alternatif önemli bir yenilenebilir enerji kaynağıdır. Kıyı bölgelerinde ve
denizlerde kurulan offshore rüzgâr santralleri dünyanın birçok yerinde etkin bir şekilde
kullanılmaktadır. Rüzgâr santralleri dikkate alındığında özellikle Türkiye’nin Kuzeybatı
bölgesi ve Ege kıyıları önemli bir potansiyel oluşturmaktadır. Bu çalışmanın amacı,
Bayesian Best-Worst yöntemini (BWM) CBS’ye entegre ederek Türkiye’nin Marmara
Denizi ve Kuzey Ege Kıyılarında açık deniz rüzgâr santralleri için uygun yer seçimini
belirlemektir. Bayesian BWM, birden çok uzmanın tercihlerini etkili bir şekilde entegre
ederek orijinal BWM’yi optimize eder. Çalışmada BWM modeli kullanılarak “teknik”,
“sosyo-ekonomik”, “çevre” ve “konum” olmak üzere dört ana kriter altında 17 kriter
belirlenmiş, kriterleri içeren anketler uzmanlar tarafından doldurulmuş ve son ağırlıkları
verilmiştir. Bayesian-BWM modeli kullanılarak bulunan kriter ağırlıkları CBS’ye entegre
edilmiş ve açık deniz rüzgâr çiftliği için uygun yerler bulunmuştur. Buna göre, Kuzey Ege
kıyılarındaki Aliağa, Bozcaada ve Gökçeada açıklarındaki çalışma alanı ile Marmara
Denizi’nin kısmen güneyi ve Kapıdağ Yarımadası çevresi rüzgâr santrali için uygun alanlar
olarak önerilmektedir.

Anahtar Kelimeler

Offshore Rüzgar Enerjisi, Yer Seçimi, Bayesyen BWM, CBS.

Kaynakça

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