With the increasing penetration of renewable energy, smart grid is facing great challenges, which could be divided into two categories. On the one hand, the endogenous uncertainty of renewable energy and electricity loads leads to the great difficulties in smart grid forecast.



On the other hand, the massive devices as well as their complex constraint relationships bring about significant difficulties in smart grid dispatch.







Owe to the rapid development of artificial intelligence in recent years, several artificial intelligence enabled computational methods are successfully applied in the smart grid and achieve good performance. Therefore, this book is concerned with the research on the key fundamental issues of artificial intelligence enabled computational methods for smart grid forecast and dispatch, which consist of three main parts:



(1) Introduction for smart grid forecast and dispatch, in inclusion of reviewing previous contribution of various research methods as well as their drawbacks to analyze the characteristics of smart grid forecast and dispatch issues.



(2) Artificial intelligence enabled computational methods for smart grid forecast problems, which is devoted to present the recent development of deep learning and machine learning as well as their successful applications in smart grid forecast.



(3) Artificial intelligence enabled computational methods for smart grid dispatch problems, consisting of novel breakthroughs in intelligent decision-making approaches, in order to determinate the final optimal solution of smart grid dispatch.







The book is useful for university researchers, engineers, and graduate students in electrical engineering and computer science who wish to learn the core principles, methods, algorithms, and applications of artificial intelligence enabled computational methods.