Meet the editor

Dr. Yan Li is a professor at the Engineering College, Northeast Agricultural University, China. He has more than 15 years of experience in research and teaching. His main research fields include energy engineering, agricultural engineering, and mechanical engineering. He teaches courses in introduction to new energy, fluid dynamics, and wind energy engineering for both undergraduate and graduate students. His current research

focuses on renewable energy, especially wind energy. He has more than fifty publications on wind turbines, wind turbine icing, and anti-icing technology to his credit. He is a member of the Chinese Aerodynamics Research Society, Chinese Society of Engineering Thermophysics, and Chinese Wind Energy Association.

## Contents


Preface

In recent years, with the increasing attention paid to environmental and energy issues in the world, the development and utilization of clean and renewable energy have been greatly valued and developed. Among the potential renewable energy sources, wind energy has become one of the most widely commercialized. However, wind turbines installed in cold regions often experience icing on the surface of their blades. Blade icing can cause many serious impacts on wind turbines and has become an important issue to address. This book focuses on the recent research progress on wind

turbine icing. It includes three research reports and three brief reviews.

de-icing methods in wind turbines.

maintenance strategies.

Investigating the distribution characteristics of icing on the blade surface is the basis for studying wind turbine icing. Numerical simulation is one of the important methods for icing research. In this book, an icing model coupling water film flow with water film evaporation considering airfoil surface roughness is developed to investigate the effect of icing conditions on the icing distribution characteristics of a blade airfoil for vertical-axis wind turbines by numerical simulation. The calculated results are in good agreement with the experimental results. The findings obtained through numerical simulation contribute to the theoretical basis for exploring anti-icing and

The most direct impact of icing on wind turbines is to reduce their power generation. Accurately predicting the power loss caused by icing conditions on wind turbines is very important. This book provides an overview of power loss estimation in wind turbines due to icing for establishing a foundation for deep research and investigations into the impact of icing on wind turbine power output. Various methodologies available for estimating power loss in wind turbines under icing conditions are collected and compared for analysis. Understanding the magnitude of power loss under icing conditions is crucial for optimizing wind turbine design, operation, and

The primary task in solving the problem of wind turbine icing is to accurately predict the occurrence of icing. Therefore, improving wind turbine ice prediction technology can assist wind farms in achieving more precise operation scheduling, avoiding needless shutdowns, and increasing power generation efficiency. This book reviews traditional wind turbine icing prediction methods. Specifically, it gives a detailed introduction to machine learning prediction methods. It provides a comprehensive description of the applicability and accuracy of various machine learning algorithms in wind turbine icing prediction and summarizes the applications and advantages.

The microscopic process of supercooled water droplets freezing on the blade surface is important for exploring the icing mechanism. This book examines the icing process of a single water droplet on a cold aluminum plate surface using a visualized method. The effects of volume and temperature on the icing characteristics are tested and acquired. The profile parameters of iced water droplets are processed and analyzed
