# Predicting the performance of a floating wind energy converter in a realistic sea

### Significance Statement

This research paper focuses on the methods for predicting the working of a floating wind energy converter, for instance, a wind turbine set up on a floating platform moored to the sea bed. Practically, the performance analysis of the floating wind energy converter is normally performed by solving the converter motion equation with a complex convolution integral term that represents the hydrodynamic effects.

The computation of the convolution integral term is complicated, time consuming and demands a large amount of memory on the selected computing machine. Above all, most research works have investigated the performances of the wind energy converters in an ideal unidirectional random sea. The researchers have applied the wave spectra in these works as uni-directional spectra, meaning that the wave energy travels in one direction. However, wind-generated energy propagates in various directions.

Researchers led by Professor Yingguang Wang from Shanghai Jiao Tong University, China, investigated rigorously the performance of a floating wind energy converter set up in a realistic, multi-directional random sea. They considered in the numerical simulation process, all the wind loads acting on the energy converter. Above all, the authors adopted the new state space model, the FDI-SS model, to solve the motion equation of the floating wind energy converter. This was in a bid to enhance the efficiency of the simulation. Their work is published in Renewable Energy.

The authors adopted a 5MW wind turbine with a 3-blade turbine with 126m rotor diameter. The hub diameter was 3m and was 90m high above the still water surface. In order to analyze the performance of the proposed wind energy converter, they numerically integrated the vector-form time domain motion equations with a convolution integral term.

The researchers selected specific load cases for the operation condition. The 10-min average wind speed was 11.2m/s at the top of the tower and 0.15 turbulence wind intensity. They applied a Kaimal power spectrum to characterize the turbulence wind random field over the turbine’s rotor plane. The turbulence wind information was applied to calculate the wind loads prior to the numerical integration. The JONSWAP wave spectrum was adopted in the simulation process of the unidirectional random waves.

In the study, the wave height for a selected sea state was 5m, spectral peak period was 12.4s and peakedness factor was 2.0. The JONSWAP wave spectrum was unidirectional in the sense that the wave energy was travelling in one direction. However, in a realistic sea, wind generated wave energy propagates and spreads in various directions. Therefore, the authors multiplied the uni-directional wave spectrum by a spreading function in a bid to obtain a directional spectrum.

The results of their paper demonstrated a great need for using a realistic, multidirectional sea state when determining electrical generation as well as dynamic responses of the floating wind energy converter. Above all, with an aim of improving the simulation efficiency, the authors used a new state space model to estimate the convolution integral term when solving the motion equation of the floating converter.

Yingguang Wang and Lifu Wang systematically analyzed and compared the simulation results and confirmed the precision and efficiency of the proposed model. They found that the new FDI-SS model could be a helpful tool for the design of floating wind turbines, therefore, helping in the exploitation of renewable wind energy.

Figure caption: Simulated sea surfaces on a square of 128 [m] by 128 [m] based on a directional JONSWAP wave spectrum with Hs=7m, Tp=11s and a cos-2s type spreading function (s=15)).