4.8 Article

Design of tidal range energy generation schemes using a Genetic Algorithm model

期刊

APPLIED ENERGY
卷 286, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.apenergy.2021.116506

关键词

Tidal energy; Tidal lagoons; Tidal barrages; Genetic Algorithms; Operational optimisation; Tidal dynamics

资金

  1. China Scholarship Council (CSC)
  2. Cardiff University

向作者/读者索取更多资源

A novel Genetic Algorithm model was developed to design the most optimised Tidal Range Schemes for electricity generation, with a new scheme proposed for the Bristol Channel, UK. The comparison showed that the Genetic Algorithm model was capable of achieving similar outcomes to traditional Grid Search methods, while reducing computational time significantly.
One of the key aspects of Tidal Range Schemes globally is identifying the most appropriate site and the optimised design and operation of the scheme, to maximise societal needs and the benefits from electricity generation. Variations in the design parameters of Tidal Range Schemes for electricity generation could therefore lead to a very large number of design and operation scenarios. In this study, a novel Genetic Algorithm model was developed to deliver the complete design of the most optimised Tidal Range Schemes for electricity generation, including the number of turbines, sluicing areas and the maximum amount of electricity that could be generated, through identifying the most optimised operation scheme for a particular site. The Genetic Algorithm model has been used to design a new Tidal Range Scheme proposed for development in the Bristol Channel, UK, with a potential to generate about 7.16 TWh/yr. The design of the scheme was also investigated using a traditional grid search approach for a range of scenarios, together with the model being used to investigate the performance of the complete design of the scheme, evaluated through a comparison of the most optimised design in terms of electricity generation. This comparison has shown that the Genetic Algorithm model was capable of achieving largely the same outcomes and reducing the computational time by approximately 95% to that based on using traditional Grid Search methods.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.8
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据