The new generation of artificial intelligence(AI)

i. e.

AI2. 0

has become a research highlight in recent years. Among AI2. 0

machine learning(ML)as a typical representative is an algorithm category that completes predictions and judgments for optimal decision-making through analyzing and learning a large amount of existing or generated data. AI2. 0 is developing rapidly in China

and it has been preliminarily applied to the energy and electric power system(EEPS)that contains smart grid(SG)and energy interconnection(EI)fields. To this end

this paper takes ML in AI2. 0 as an example to review the current application of seven representative MLs in EEPS from aspects of dispatch optimization and control decision-making

including reinforcement learning

deep learning

transfer learning

parallel learning

hybrid learning

adversarial learning

and ensemble learning. Finally

the prospects for the future development of ML are conducted

trying to provide some reference for the theoretical

technical and application studies of AI2. 0

especially ML in the field of EEPS in the future.