Presentations

Abstract

Offshore wind farms have the capacity to generate vast amounts of clean energy, but the challenging offshore environment leads to increased component failures, resulting in significant maintenance costs and downtime. To address these challenges, fault detection and isolation (FDI) and fault-tolerant control (FTC) methods have gained prominence in the past decade. FDI systems identify faulty components within wind turbines (WTs), while FTC systems aim to maintain turbine performance despite faults. These strategies can potentially reduce maintenance costs and downtime, making offshore wind energy more economically viable. The study introduces a Simulink-based toolbox, built upon the existing SimWindFarm simulator, which enables users to define wind farm layouts and specify when faults occur within the farm. The toolbox utilizes a simplified model that captures the essential dynamics of real wind farms while facilitating the development of FDI and FTC strategies. The model's simplicity allows for the simulation of numerous scenarios, crucial for data-driven FDI strategies that require a large number of simulations. The toolbox generates a wind field based on user-defined parameters, complying with international standards for offshore WTs. It considers various wake effects, including deficit, expansion, and centre effects. The model separates wind turbine components into different subsystems, simplifying code comprehension and simulation. The toolbox can simulate various fault scenarios, including sensor and actuator faults, within the wind turbines. It focuses on faults that allow turbines to continue operating suboptimally, aligning with the goal of developing FDI and FTC strategies for fault-tolerant operation. The study demonstrates the toolbox's utility by comparing it with FastFARM, highlighting its efficiency and accuracy in controller and FDI strategy development.