Extracted power optimization of hybrid wind-wave energy converters array layout via enhanced snake optimizer

Abstract

In recent years, wind energy and wave energy are widely concerned as highly developmental clean energy alternatives to traditional energy sources. From the perspective of cost reduction and power output enhancement, in this study, a V27-225 kW wind turbine and wave energy converter are combined to construct a hybrid wind-wave energy converters (HWWEC), which greatly improves the power generation and operation stability. The optimization of wind-wave energy layout that involves strategically placing wave energy devices can directly influence the energy output of the whole system. To enhance the overall power generation efficiency, the optimal array configuration becomes a challenging but also promising solution regarding this concern. To optimize the array configuration that is composed of multiple HWWECS, this study develops an enhanced snake optimizer (ESO) based optimization scheme including chaotic initialization, asynchronous learning factors, and levy flight, which shows strong optimum searching ability while avoiding falling into local optimums. Simulation results under various case studies of three-line WECs consisting of three, six, and twelve buoys indicate that the ESO achieves the highest absorption power compared to other algorithms, particularly, the output power achieved by ESO is 144.337 kW higher than that obtained by the original SO.