ABSTRACT:

In recent years, offshore wind farm in the world has been rapid development, but compared to land-based wind farm, its cost by 60% or more. Among them, offshore wind turbine infrastructure costs the equivalent of twice the land-based wind turbine. In order to effectively lower the cost of offshore wind turbine, would need to make an accurate calculation of the overall structure, and as a basis for design, offshore wind turbine to improve the safety and economy. In view of this, the paper established the Soil-Foundation-Tower whole analytical model. In this model the non-linear material behavior of the subsoil is described using the Mohr-Coulomb model, contact pair is used to define interaction between the pile and soil, considering the geometric nonlinearity of the tower. The overall structure frequency and static response responses are analyzed using this model. This paper aims to through parameter sensitivity analysis to identify which design parameters have major impact on wind turbine structural safety, and comparing with present specification analysis method, promote the offshore wind turbine design capability.

INTRODUCTION

Offshore wind energy is becoming increasingly popular in the quest for renewable sources of energy. The continuous improvement in wind turbine technology means that the wind turbines have increased tremendously in both size and performance during the last 30 years(Simon-Philippe Breton,2009). In order to reduce the costs, the overall weight of the wind turbine components is minimized, which means that the wind turbine support structures become more flexible and thus more sensitive to dynamic excitation. Since the first natural frequency of the offshore wind turbines is close to the excitation frequencies of the rotor system, it is of outmost importance to be able to evaluate the natural frequencies of the wind turbine structure accurately as the wind turbines increase in size.

This content is only available via PDF.
You can access this article if you purchase or spend a download.