Mohammad-Hassan Khooban

Applications of Deep Machine Learning in Future Energy Systems pushes the limits of current Artificial Intelligence techniques to present deep machine learning suitable for the complexity of sustainable energy systems. The first two chapters take the reader through the latest trends in power engineering and system design and operation, before laying out the current AI approaches and our outstanding limitations. Later chapters provide in-depth accounts of specific challenges and the use of innovative third-generation machine learning, including neuromorphic computing, to resolve issues from security to power supply. An essential tool for the management, control, and modelling of future energy systems, Applications of Deep Machine Learning maps a practical path towards AI capable of supporting sustainable energy. - Clarifies the current state and future trends of energy system machine learning and the pitfalls facing our transitioning systems - Provides guidance on 3rd-generation AI tools for meeting the challenges of modeling and control in modern energy systems - Includes case studies and practical examples of potential applications to inspire and inform researchers and industry developers

Applications of Deep Machine Learning in Future Energy Systems

Tomislav Dragicevic

Since delays are present in 99% of industrial processes, Control Strategy for Time-delay Systems covers all the important features of real-world practical applications which will be valuable to practicing engineers and specialists The book presents the views of the editors on promising research directions and future industrial applications in this area. Although the fundamentals of time-delay systems are discussed, the book focuses on the advanced modelling and control of such systems and will provide the analysis and test (or simulation) results of nearly every technique described in the book For this purpose, highly complex models are introduced to ‎describe the mentioned new applications which are characterized by ‎time-varying delays with intermittent and stochastic nature, several types of nonlinearities, and the presence ‎of different time-scales. Researchers, practitioners and PhD students will gain insights into the prevailing trends in design and operation of real-time control systems, reviewing the shortcomings and future developments concerning the practical system issues such as standardization, protection and design.

Mohammad-Hassan Khooban

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