Multi-objective optimization study of wave elimination and electricity generation performance of Savonius hydrokinetic turbine based on metamodel

Abstract

The floating power generation and wave elimination system is getting more and more attention because of its multiple functions. The Savonius hydrokinetic turbine (SHT) can be used for wave elimination and power generation of offshore platforms due to its good self-start performance and simple structure. The wave elimination performance (WEP) and electricity generation performance (EGP) are closely related to the parameters of SHT, and these parameters are coupled with each other. Improving the performance of SHT under wave conditions and quickly analyzing the relationship between performance and parameters is a topic worth studying. In this paper, a multi-parameter multi-objective metamodel is established by CFD and RBFNN to meet the accuracy. And then coupled with NSGA –II algorithm to solve the Pareto front, quickly determining the optimized parameters of the SHT according to the decision criterion. Finally, a physical model is used for experimental verification, and the influence of each parameter on the performance is further analyzed. After optimization, the WEP is 0.3834 and the EGP is 0.2256. 55.7% and 28.6% improvement over the conventional structure, respectively. The metamodel is well representative within the optimization range. The optimized model still shows better performance in other conditions.