{"title":"多准则决策下的波能场址和转换器选择:一个案例研究","authors":"E. Ergul, Tayfun Ozbek","doi":"10.1680/jener.21.00087","DOIUrl":null,"url":null,"abstract":"Due to the increase in energy demand, the decline of fossil fuels in the coming years, climate change and environmental pollution, demand for renewable energy sources is growing rapidly. Many studies have been made on the potential of wave energy in the world and many wave energy converters have been developed. Although there is wave energy potential in Turkey, wave energy is hardly exploited. Main purpose of this study is to determine the most appropriate site and converter type for a wave energy power plant planned to be built in Turkey. For this purpose, a two-phased multi-criteria decision making (MCDM) structure is constructed. Analytic Network Process (ANP) and Fuzzy TOPSIS (Technique for Order Preference by Similarly to Ideal Solution) are selected as MCDM methods. Five cities located in the Black Sea coast which have high wave energy potential are selected as alternatives to the installation sites of the wave energy power plant. In the first phase, Sinop is determined as the most suitable wave energy power plant site by ANP. In the second phase, the most suitable wave energy converter to be installed in Sinop is determined as Oyster among the five alternatives by Fuzzy TOPSIS.","PeriodicalId":48776,"journal":{"name":"Proceedings of the Institution of Civil Engineers-Energy","volume":"6 1","pages":""},"PeriodicalIF":1.0000,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Wave energy site and converter selection with multi-criteria decision making: a case study\",\"authors\":\"E. Ergul, Tayfun Ozbek\",\"doi\":\"10.1680/jener.21.00087\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Due to the increase in energy demand, the decline of fossil fuels in the coming years, climate change and environmental pollution, demand for renewable energy sources is growing rapidly. Many studies have been made on the potential of wave energy in the world and many wave energy converters have been developed. Although there is wave energy potential in Turkey, wave energy is hardly exploited. Main purpose of this study is to determine the most appropriate site and converter type for a wave energy power plant planned to be built in Turkey. For this purpose, a two-phased multi-criteria decision making (MCDM) structure is constructed. Analytic Network Process (ANP) and Fuzzy TOPSIS (Technique for Order Preference by Similarly to Ideal Solution) are selected as MCDM methods. Five cities located in the Black Sea coast which have high wave energy potential are selected as alternatives to the installation sites of the wave energy power plant. In the first phase, Sinop is determined as the most suitable wave energy power plant site by ANP. In the second phase, the most suitable wave energy converter to be installed in Sinop is determined as Oyster among the five alternatives by Fuzzy TOPSIS.\",\"PeriodicalId\":48776,\"journal\":{\"name\":\"Proceedings of the Institution of Civil Engineers-Energy\",\"volume\":\"6 1\",\"pages\":\"\"},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2022-02-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Institution of Civil Engineers-Energy\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1680/jener.21.00087\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Institution of Civil Engineers-Energy","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1680/jener.21.00087","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
Wave energy site and converter selection with multi-criteria decision making: a case study
Due to the increase in energy demand, the decline of fossil fuels in the coming years, climate change and environmental pollution, demand for renewable energy sources is growing rapidly. Many studies have been made on the potential of wave energy in the world and many wave energy converters have been developed. Although there is wave energy potential in Turkey, wave energy is hardly exploited. Main purpose of this study is to determine the most appropriate site and converter type for a wave energy power plant planned to be built in Turkey. For this purpose, a two-phased multi-criteria decision making (MCDM) structure is constructed. Analytic Network Process (ANP) and Fuzzy TOPSIS (Technique for Order Preference by Similarly to Ideal Solution) are selected as MCDM methods. Five cities located in the Black Sea coast which have high wave energy potential are selected as alternatives to the installation sites of the wave energy power plant. In the first phase, Sinop is determined as the most suitable wave energy power plant site by ANP. In the second phase, the most suitable wave energy converter to be installed in Sinop is determined as Oyster among the five alternatives by Fuzzy TOPSIS.
期刊介绍:
Energy addresses the challenges of energy engineering in the 21st century. The journal publishes groundbreaking papers on energy provision by leading figures in industry and academia and provides a unique forum for discussion on everything from underground coal gasification to the practical implications of biofuels. The journal is a key resource for engineers and researchers working to meet the challenges of energy engineering. Topics addressed include: development of sustainable energy policy, energy efficiency in buildings, infrastructure and transport systems, renewable energy sources, operation and decommissioning of projects, and energy conservation.