Wave energy power plant site and converter type selection by using mcdm methods

Due to the increase in energy demand, the decline of fossil fuel types in the coming years, and especially due to global warming, climate change and environmental pollution, demand for renewable energy sources is growing rapidly. Hence, the studies based on alternative renewable energy sources have made great progress. One of these sources is wave energy. Many studies have been made on the potential of wave energy in the world and many wave energy converters (WECs) have been developed. Although there is wave energy potential in Turkey, three sides of which are surrounded by seas, this type of energy is hardly exploited. However, the importance of this energy type has been recognized and the planning of the establishment of wave energy plants has begun. It is important that an appropriate WEC is installed at an appropriate site to obtain maximum efficiency from the wave energy power plants. Main purpose of this thesis is to determine the most appropriate site and converter type for a wave energy power plant planned to be established in Turkey. Since there are many criteria for determining the most suitable site and converter type, a two-phased multi-criteria decision making (MCDM) structure has been constructed to realize this aim. ANP (Analytic Network Process) and Fuzzy TOPSIS (Techniques for Order Preference by Similarity to Ideal Solution) are selected as multi-criteria decision making methods. Five cities (Sinop, Samsun, Trabzon, Ordu, and Giresun) located in the Black Sea coast which have high wave energy potential and five WEC types (Oscillating Water Column, Oyster, Wave Dragon, Pelamis and McCabe Wave Pump) are determined as alternatives. The criteria affecting the selection of site and converter type were determined by literature review. In the first phase, Sinop is determined as the most suitable site to install the wave power plant by using ANP and Oyster is determined as the most suitable WEC type to be installed in Sinop by using Fuzzy TOPSIS in the second phase.