Data-driven Optimization and Control for Autonomous Energy Systems - Jian Sun,Gang Wang,Jie Chen
-35% koodilla BOOKS
Toimitus 17-23 arkipäivässä
30 päivän palautusoikeus
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 maxim ... Täydellinen kuvaus
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Kuvaus
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.
Lisätietoja
| Kirjoittaja | Jian Sun, Gang Wang, Jie Chen |
|---|---|
| Julkaisija | Springer-Verlag GmbH |
| Julkaisuvuosi | 2025 |
| Kannen tyyppi | Kovakantinen |
| EAN | 9789819517817 |