Sheng Huang

Distributed Optimal Control of Large-Scale Wind Farm Clusters: Optimal Active and Reactive Power Control, and Fault Ride Through, a new volume in the Elsevier Wind Energy Engineering series, explores the latest advances in distributed optimal control of large-scale wind farm clusters, also describing distributed optimal control techniques for high voltage ride through (HVRT). Both mathematical formulations and algorithm details are provided, along with MATLAB codes to replicate and implement distributed optimal control schemes. This is a valuable resource for anyone interested in the operation, control, and integration of wind power plants, wind farms, and electricity grids, both at research and operational levels. Researchers, faculty, scientists, engineers, R&D, and other industry professionals, as well as graduate and postgraduate students studying and working in wind energy will find this comprehensive resource a valuable addition to their work.

Permanent magnet synchronous motors (PMSMs) are essential in electromechanical systems like urban rail vehicles and wind power generation, thanks to their fast torque response and wide speed range. Model predictive control (MPC) offers high accuracy and dynamic response, making it suitable for PMSMs. However, MPC relies on accurate motor parameters, which may vary over time, leading to mismatches that affect performance. These mismatches can cause unstable switching frequencies and increased torque/flux ripples, becoming a common fault in PMSM systems. This book presents improved MPC methods to enhance robustness against parameter mismatches. It aims to help researchers understand advanced motor control strategies and assist engineers in applying these algorithms effectively to improve the operational performance of industrial motor systems.