Fatigue mitigation of wind turbine system using multiple point model predictive control

Abstract

<span lang="EN-US">A multi-point model predictive control (MPMPC) is widely used for many applications, including wind energy system (WES), notably enhanced power characteristics and oscillation regulation. In this work, MPMPC is adapted to condense the fatigue load of the WES and improve the lifetime of the turbine assembly. The lifetime examination is carried out by considering the three chief parameters: basic lifetime until failure, short-time damage equivalent loads (DELs), and lifetime DELs. The simulation study is performed for two cases: blade root bending moments and tower top bending. Further, fatigue load examination is demonstrated to analyze the effectiveness of the proposed controller. The observed results show that the lifetime analysis of the wind turbine system displayed more excellent characteristics, i.e., 49.50% greater than MPC. Also, the fatigue load mitigation showed greater magnitude due to the control action of the proposed controller, about 37.38% grander than MPC. Therefore, the attained outcomes exhibit outstanding performance compared with conventional controllers.</span>

Wind Turbines Control Trends and Challenges: An Overview

“…In 2018, China accounted for more than fifty percent of worldwide offshore wind investments, investing $11.4 billion in thirteen new offshore wind projects. The Chinese government has approved 6,7 GW of offshore wind power and around USD 18 billion for development in 2019 [17].…”

“…These controllers typically employ metaheuristic algorithms, Artificial neural networks (ANNs), and Fuzzy logic controls (FLCs). Fuzzy logic controls are gaining popularity among WTs due to their adaptability and user-friendliness [17]; [21]; [32]; [37]. The effectiveness of a fuzzy logic controller is determined by the user's comprehension of the controller.…”

“…A WT controller based on ANN permits maximum output at wind speeds above the rated speed. Using ANN techniques, it is also possible to estimate the nonlinear properties of the WT [17]; [30].…”

“…When the wind speed is moderate, metaheuristic pitch angle controllers based on evolutionary algorithms can maintain system stability. When adjusting the generator's speed, it is customary to employ a control signal based on the reference speed [17]; [22].…”

“…As the controller gain rises, the system's sensitivity falls. Therefore, controller gain scheduling improves control system dependability [17].…”