Mahmoud A. Mossa – författare

Advanced Controls for Wind Driven Doubly Fed Induction Generators discusses the most advanced control algorithms used for enhancing the dynamics of a doubly fed induction generator (DFIG) operating at fixed and variable speeds, and which are used for different utilization purposes (standalone and grid connection). Extensive generator performance analysis has been introduced using various control topologies.Features:Presents modeling of wind energy conversion systems (WECS), including a wind turbine as a prime mover, a DFIG as a generation unit for electrical energy, and a three-phase induction motor as an isolated loadExplores a detailed description for the presented control algorithms in order to visualize the base principle of each methodIntroduces a comprehensive performance analysis for the DFIG using the formulated predictive voltage control scheme and other control techniques under different operating conditionsExamines the formulation of new control approaches which overcome the shortages present in previous DFIG control schemesPresents a detailed comparison between different control topologies for the DFIG to outline the most effective procedure in terms of dynamic response, structure simplicity, ripples, total harmonic distortion, and computational burdensThe book is written for researchers and academics working on advanced control systems and those interested in areas such as machine drives, renewable energy systems, 'adaptive control', modeling of WECS, and optimization theory.

Advanced Controls for Wind Driven Doubly Fed Induction Generators discusses the most advanced control algorithms used for enhancing the dynamics of a doubly fed induction generator (DFIG) operating at fixed and variable speeds, and which are used for different utilization purposes (standalone and grid connection). Extensive generator performance analysis has been introduced using various control topologies.Features:Presents modeling of wind energy conversion systems (WECS), including a wind turbine as a prime mover, a DFIG as a generation unit for electrical energy, and a three-phase induction motor as an isolated loadExplores a detailed description for the presented control algorithms in order to visualize the base principle of each methodIntroduces a comprehensive performance analysis for the DFIG using the formulated predictive voltage control scheme and other control techniques under different operating conditionsExamines the formulation of new control approaches which overcome the shortages present in previous DFIG control schemesPresents a detailed comparison between different control topologies for the DFIG to outline the most effective procedure in terms of dynamic response, structure simplicity, ripples, total harmonic distortion, and computational burdensThe book is written for researchers and academics working on advanced control systems and those interested in areas such as machine drives, renewable energy systems, 'adaptive control', modeling of WECS, and optimization theory.

This book addresses and disseminates state-of-the-art research and development in the applications of soft computing techniques for renewable energy systems. It covers topics such as solar energy, wind energy, and solar concentrator technologies, as well as building systems and power generation systems. In all these areas, applications of soft computing methods such as artificial neural networks, genetic algorithms, particle swarm optimization, cuckoo search, fuzzy logic, and a combination of these, called hybrid systems, are included. This book is a source for students interested in the fields of renewable energy and the application of the soft computing. In addition, our book can be considered as a reference for researchers and academics since it will include applications of soft computing in different renewable energy systems.

This book addresses and disseminates state-of-the-art research and development in the applications of soft computing techniques for renewable energy systems. It covers topics such as solar energy, wind energy, and solar concentrator technologies, as well as building systems and power generation systems. In all these areas, applications of soft computing methods such as artificial neural networks, genetic algorithms, particle swarm optimization, cuckoo search, fuzzy logic, and a combination of these, called hybrid systems, are included. This book is a source for students interested in the fields of renewable energy and the application of the soft computing. In addition, our book can be considered as a reference for researchers and academics since it will include applications of soft computing in different renewable energy systems.