The global pursuit of renewable energy sources to mitigate the impacts of climate change has brought wind energy to the forefront of the sustainable energy landscape. Wind energy, which is derived from the kinetic energy of moving air masses, has attracted significant attention due to its environmentally friendly, inexhaustible, and cost-effective qualities. The utilization of this potential necessitates the efficient and effective management of wind energy systems (Singh, M et al., 2021). Within this chapter, the authors delve into the transformative capabilities of digital twins, the Internet of Things (IoT), and Artificial Intelligence (AI) in the optimization of wind energy systems. The combination of these technologies is positioned to fundamentally alter how wind energy systems are harnessed, monitored, and maintained.
Background and Significance
The utilization of wind as an energy source can be traced back centuries, during which early windmills were utilized to grind grains and pump water. However, it is only in recent decades that wind energy has developed into a significant participant within the global energy mix. The growth of wind power can be attributed to various factors, including advancements in turbine technology, the decrease in the cost of wind energy, and an increased emphasis on sustainable and clean energy sources.
One of the fundamental elements that impact the effectiveness and productivity of wind energy systems is the management of wind farms, including individual wind turbines, power distribution, and maintenance (Sahal et al., 2022 – Rasheed, 2020). These systems possess inherent complexity, encompassing a multitude of components such as the rotor, generator, gearbox, and control systems, all of which must function in harmony to optimize energy production. Nonetheless, the operation and maintenance of wind turbines and farms present numerous challenges, ranging from unpredictable wind patterns and fluctuating energy output to the significant costs associated with maintenance and downtime.
Consequently, the wind energy industry has been actively searching for innovative solutions to enhance the performance, reliability, and sustainability of wind energy systems. Digital twins, IoT, and AI have emerged as promising technologies in this pursuit.
The significance of this convergence of digital twins, IoT, and AI in wind energy cannot be overstated. The capability to monitor and manage wind energy systems with unparalleled accuracy and efficiency not only strengthens the economic viability of wind energy but also enhances its sustainability and environmental impact. It enables wind farm operators to minimize operational costs, reduce the carbon footprint, and prolong the lifespan of equipment, all of which contribute to the broader objectives of sustainability and the mitigation of climate change.
Within the context of a swiftly evolving energy landscape and escalating global endeavors to transition towards green energy sources, this chapter explores the transformative potential of digital twins, IoT, and AI within the wind energy sector. In doing so, it aims to furnish a comprehensive comprehension of these technologies and their practical applications, ensuring that professionals, researchers, and policymakers are suitably equipped to harness their advantages in the ongoing pursuit of a sustainable and clean energy future.