This book brings together real-world accounts of using voltage stability assessment (VSA) and transient stability assessment (TSA) tools for grid management. Chapters are written by leading experts in the field who have used these tools to manage their grids and can provide readers with a unique and international perspective. Case studies and success stories are presented by those who have used these tools in the field, making this book a useful reference for different utilities worldwide that are looking into implementing these tools, as well as students and practicing engineers who...
This book brings together real-world accounts of using voltage stability assessment (VSA) and transient stability assessment (TSA) tools for grid m...
This book provides readers with an in-depth review of deep learning-based techniques and discusses how they can benefit power system applications. Representative case studies of deep learning techniques in power systems are investigated and discussed, including convolutional neural networks (CNN) for power system security screening and cascading failure assessment, deep neural networks (DNN) for demand response management, and deep reinforcement learning (deep RL) for heating, ventilation, and air conditioning (HVAC) control.
Deep Learning for Power System...
This book provides readers with an in-depth review of deep learning-based techniques and discusses how they can benefit power system applications...
This book provides a systematic introduction to power system sub/super-synchronous oscillations caused by grid-connected wind power generation. The authors look at why oscillations occur and present methods for examining the risk of oscillations. Coverage includes state-space model based analysis and impedance model based analysis, which are the two main methods for examining the power system sub/super-synchronous oscillations. In addition, new methods for examining oscillations in wind farms are proposed.
Analysis of Power System Sub/Super-Synchronous Oscillations...
This book provides a systematic introduction to power system sub/super-synchronous oscillations caused by grid-connected wind power generation. The au...
This book provides readers with an in-depth review of deep learning-based techniques and discusses how they can benefit power system applications. Representative case studies of deep learning techniques in power systems are investigated and discussed, including convolutional neural networks (CNN) for power system security screening and cascading failure assessment, deep neural networks (DNN) for demand response management, and deep reinforcement learning (deep RL) for heating, ventilation, and air conditioning (HVAC) control.
Deep Learning for Power System...
This book provides readers with an in-depth review of deep learning-based techniques and discusses how they can benefit power system applications...
This book provides a systematic introduction to power system sub/super-synchronous oscillations caused by grid-connected wind power generation. The authors look at why oscillations occur and present methods for examining the risk of oscillations. Coverage includes state-space model based analysis and impedance model based analysis, which are the two main methods for examining the power system sub/super-synchronous oscillations. In addition, new methods for examining oscillations in wind farms are proposed.
Analysis of Power System Sub/Super-Synchronous Oscillations...
This book provides a systematic introduction to power system sub/super-synchronous oscillations caused by grid-connected wind power generation. The au...
