Advancements in Wind Energy Technology and Control
*Corresponding Author: Prof. S脙赂ren Nielsen, Dept. of Wind Energy Technical University of Denmark, Denmark, Email: s.nielsen@dtu-demo.dkReceived Date: Jan 01, 2025 / Accepted Date: Jan 29, 2025 / Published Date: Jan 29, 2025
Citation: Nielsen PS (2025) Advancements in Wind Energy Technology and Control. Innov Ener Res 14: 436.DOI: 10.4172/2576-1463.1000436
Copyright: © 2025 Prof. Søren Nielsen This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permitsunrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.
Abstract
This compilation of research explores advanced strategies for optimizing wind turbine performance and integration. It covers
model predictive control for power optimization and fatigue load reduction, wake effect mitigation through farm layout optimization,
and deep learning for short-term forecasting. The work also delves into adaptive control for offshore turbines, AI for predictive
maintenance, real-time performance monitoring, pitch control optimization, aerodynamic blade design, and hybrid renewable energy
systems. These studies collectively aim to enhance energy capture, reliability, and grid stability.
