logo
Product categories

EbookNice.com

Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.

Please read the tutorial at this link.  https://ebooknice.com/page/post?id=faq


We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.


For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.

EbookNice Team

Data-driven Optimization and Control for Autonomous Energy Systems by Gang Wang, Jian Sun, Jie Chen ISBN 9789819517817, 9819517818 instant download

  • SKU: EBN-239943276
Zoomable Image
$ 32 $ 40 (-20%)

Status:

Available

4.6

15 reviews
Instant download (eBook) Data-driven Optimization and Control for Autonomous Energy Systems after payment.
Authors:Gang Wang, Jian Sun, Jie Chen
Pages:updating ...
Year:2025
Publisher:Springer
Language:english
File Size:13.83 MB
Format:pdf
ISBNS:9789819517817, 9819517818
Categories: Ebooks

Product desciption

Data-driven Optimization and Control for Autonomous Energy Systems by Gang Wang, Jian Sun, Jie Chen ISBN 9789819517817, 9819517818 instant download

This book introduces a pioneering framework for monitoring and controlling autonomous energy systems, distinguished by its use of physics-informed deep neural networks. These networks provide accurate estimations and forecasts, interlacing with advanced composite optimization algorithms to simplify the complex processes of state estimation. This approach not only boosts operational efficiency but also maximizes flexibility through a data-driven methodology integrated with physics-based principles. The framework leverages the power of neural networks to define the intricate relationship between system states and control policies, offering precise, robust control strategies that adapt to dynamically changing system conditions. This book is essential reading for professionals looking to enhance the performance and flexibility of energy systems through cutting-edge technology.
*Free conversion of into popular formats such as PDF, DOCX, DOC, AZW, EPUB, and MOBI after payment.

Related Products