Enhancing Resilience in Distribution Systems
Li, Fangxing Fran
Shi, Qingxin
Zhao, Guangjin
Enhancing Resilience in Distribution Systems presents practical guidance for readers on the challenges and potential solutions for resilience in modern power systems. The book begins by explaining the risks and problems for resilience presented by renewable-based power systems. It goes on to clarify the current state of research and propose several novel methodologies and technologies for analysis and improvement of power system resilience. These methods include deep learning, linear programming, and generative adversarial networks. Packed with practical steps and tools for implementing the latest technologies, this book provides researchers and industry professionals with guidance on the resilient systems of the future. Breaks down novel methodologies and tools from deep learning to generative adversarial networksSupports readers in implementing practical steps towards resilient renewable energyPresents practical guidance for readers on the challenges and potential solutions for resilience in modern power systems INDICE: 1. Resilience in Modern Distribution Systems 2. Solutions, Current Issues, and Future Challenges 3. Components in Distribution Systems 4. Optimal Planning to Enhance Distribution Resilience 5. Optimal Operation to Enhance Distribution Resilience 6. Machine Learning Can Help Form Microgrids for Better Resilience 7. More on Machine Learning: When the Extreme Event Data is Scarce 8. Conclusions
- ISBN: 978-0-443-23640-2
- Editorial: Elsevier
- Encuadernacion: Rústica
- Páginas: 250
- Fecha Publicación: 01/11/2024
- Nº Volúmenes: 1
- Idioma: Inglés