文章基本信息

标题：A Comparative Study of Metaheuristic Algorithms for Wave Energy Converter Power Take-Off Optimisation: A Case Study for Eastern Australia
本地全文：下载
作者：Erfan Amini ; Danial Golbaz ; Rojin Asadi 等
期刊名称：Journal of Marine Science and Engineering
电子版ISSN：2077-1312
出版年度：2021
卷号：9
期号：5
页码：490
DOI：10.3390/jmse9050490
语种：English
出版社：MDPI AG
摘要：One of the most encouraging sorts of renewable energy is ocean wave energy. In spite of a large number of investigations in this field during the last decade, wave energy technologies are recognised as neither mature nor broadly commercialised compared to other renewable energy technologies. In this paper, we develop and optimise Power Take-off (PTO) configurations of a well-known wave energy converter (WEC) called a point absorber. This WEC is a fully submerged buoy with three tethers, which was proposed and developed by Carnegie Clean Energy Company in Australia. Optimising the WEC’s PTO parameters is a challenging engineering problem due to the high dimensionality and complexity of the search space. This research compares the performance of five state-of-the-art metaheuristics (including Covariance Matrix Adaptation Evolution Strategy, Gray Wolf optimiser, Harris Hawks optimisation, and Grasshopper Optimisation Algorithm) based on the real wave scenario in Sydney sea state. The experimental achievements show that the Multiverse optimisation (MVO) algorithm performs better than the other metaheuristics applied in this work.