Determining suitable container ports for offshore wind farms based on geographical information system-analytic hierarchy process: a case study of Marmara Sea

2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Samet Öztürk ◽  
Fatih Karipoğlu
Keyword(s):  
Information System ◽  
Wind Farms ◽  
Offshore Wind ◽  
Geographical Information ◽  
Marmara Sea ◽  
Analytic Hierarchy ◽  
Offshore Wind Farms ◽  
Container Ports ◽  
Hierarchy Process

scholarly journals Importance of offshore wind farms Marmara Sea for Turkey’s renewable energy targets: a case study Marmara Sea

2020 ◽  
Vol 2 (2) ◽  
pp. 25-38
Author(s):  
Fatih Karipoğlu
Keyword(s):  
Renewable Energy ◽  
Energy Demand ◽  
Renewable Energy Sources ◽  
Wind Farms ◽  
Environmental Data ◽  
Offshore Wind ◽  
Geographical Information ◽  
Marmara Sea ◽  
Offshore Wind Farms ◽  
Wind Potential

In Turkey, current energy generations are not sufficient for the existing energy needs and besides, energy demand is expected to increase by 4-6% percent annually until 2023. Therefore, the government aims to increase the ratio of renewable energy sources in total installed capacity to 30 percent by 2023. Turkey has three quarter seas around itself. So, Turkey has a high level offshore wind potential for energy generations. But there are not any offshore wind farms in Turkey seas. In this study, we aimed at assessing the viability of establishing offshore wind farms of Marmara Sea and to identify favorable sites for such farms using Geographical Information System (GIS) procedures and algorithms. GIS layers were created and a weighted overlay GIS model based on the above mentioned criteria was built to identify suitable sites for hosting a new offshore wind farm. Furthermore, EMODnet (the European Marine Observation and Data Network) and GWA (Global Wind Atlas) were employed for data acquisition to unlock fragmented and hidden marine data resources and to facilitate investment in sustainable coastal and offshore activities. Received technical, social and environmental data from different sources were processed in the GIS and we created the GIS-based model. Results showed that most of Marmara Sea offshore areas were unsuitable. There are only two suitable areas. It is apparent that the growth of offshore wind farms in Turkey will increase provided that the supporting mechanism and the necessary legislation are ensured.  

Levelised cost of energy analysis for offshore wind farms – A case study of the New York State development

2021 ◽  
Vol 239 ◽  
pp. 109923
Author(s):  
Yibo Liang ◽  
Yu Ma ◽  
Haibin Wang ◽  
Ana Mesbahi ◽  
Byongug Jeong ◽  
...  
Keyword(s):  
New York ◽  
Energy Analysis ◽  
New York State ◽  
Wind Farms ◽  
Offshore Wind ◽  
State Development ◽  
Offshore Wind Farms ◽  
York State ◽  
Cost Of Energy

scholarly journals Use of Analytic Hierarchy Process for Wind Farm Installation Region Prioritization–Case Study

Energies ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 2284 ◽  
Author(s):  
Rômulo Lemos Bulhões ◽  
Eudemário Souza de Santana ◽  
Alex Álisson Bandeira Santos
Keyword(s):  
Decision Making ◽  
Analytic Hierarchy Process ◽  
Wind Farm ◽  
Greenhouse Gas Emission ◽  
Wind Farms ◽  
Clean Energy ◽  
Poor Quality ◽  
Analytic Hierarchy ◽  
Hierarchy Process

Electricity generation via renewable sources is emerging as a possible solution to meet the growing demand for electricity worldwide. Additionally, the need to produce clean energy, with little or no pollutants or greenhouse gas emission is paramount. Due to these factors, wind farms are noticeably increasing in number, especially in Brazil. However, the vast size of the country and the poor quality of its infrastructure are among several factors that make it difficult for effective decision-making to accelerate the growth of this segment in Brazil. With the purpose of assisting government agencies, regulatory agencies and other institutions in this area, the use of a multi-criteria selection method called the analytic hierarchy process is proposed here to assist in decision-making and to select priority regions for implementing wind farms. This work focuses on a case study of the state of Bahia, in which 27 territories were selected for an installation priority evaluation. Computational tools were used to hierarchize these chosen territories, including Matlab, for the construction of the computational algorithm. The results indicate the priority pf the regions according to the established criteria, which allows installation locations to be mapped—these could serve as a basis for regional investment.

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