Journal
CSEE JOURNAL OF POWER AND ENERGY SYSTEMS
Volume 4, Issue 3, Pages 362-370Publisher
CHINA ELECTRIC POWER RESEARCH INST
DOI: 10.17775/CSEEJPES.2018.00520
Keywords
Deep learning; deep reinforcement learning; reinforcement learning; smart grid
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Smart grids are the developmental trend of power systems and they have attracted much attention all over the world. Due to their complexities, and the uncertainty of the smart grid and high volume of information being collected, artificial intelligence techniques represent some of the enabling technologies for its future development and success. Owing to the decreasing cost of computing power, the profusion of data, and better algorithms, AI has entered into its new developmental stage and AI 2.0 is developing rapidly. Deep learning (DL), reinforcement learning (RL) and their combination-deep reinforcement learning (DRL) are representative methods and relatively mature methods in the family of AI 2.0. This article introduces the concept and status quo of the above three methods, summarizes their potential for application in smart grids, and provides an overview of the research work on their application in smart grids.
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