Ocean energy is one potential renewable energy alternative to fossil fuels that has a more significant power generation due to its better predictability and availability. In order to harness this source, wave energy converters (WECs) have been devised and used over the past several years to generate as much energy and power as is feasible. While it is possible to install these devices in both nearshore and offshore areas, nearshore sites are more appropriate places since more severe weather occurs offshore. Determining the optimal location might be challenging when dealing with sites along the coast since they often have varying capacities for energy production. Constructing wave farms requires determining the appropriate location for WECs, which may lead us to its correct and optimum design. The WEC size, shape, and layout are factors that must be considered for installing these devices. Therefore, this review aims to explain the methodologies, advancements, and effective hydrodynamic parameters that may be used to discover the optimal configuration of WECs in nearshore locations using evolutionary algorithms (EAs).

Ocean wave energy is an essential source of renewable power for coastal communities. Choosing the optimal site for the wave energy converter (WEC) deployment depends on a number of criteria. The characteristics of the WEC must be taken into account in the prediction power supply, whereas the local sea state is connected to elements like wave condition (as a representation of construction budget) and energy output as well as the influence of the exploitable storage of wave energy and its trend. As a result, this research provides a multi-criteria decision-making (MCDM) strategy for considering several factors simultaneously to choose the best possible site. The suggested MCDM technique incorporates two primary factors, i.e., exploitable storage of wave energy and energy production, into a single metric that takes into account both WEC efficiency of a particular type, WEPTOS, and sea state to aid decision-makers in the development of a pilot project. The method was then used to analyse the waves at two locations that had been identified as promising sites for harvesting wave energy along the coast of Oman. To further assess a site's potential upcoming pilot project and select the most efficient WEC, we compared the MCDM results at the stations with certain WEC types. In conclusion, optimal sites for placement of the WEPTOS WEC along the coast of Oman were identified considering the highest annual energy production and exploitable energy storage. Through solving the MCDM technique, 17 sites were pinpointed, and only 6 points were picked up.