电力系统自动化2019，Vol.43Issue(1)：15-31,17.DOI:10.7500/AEPS20180814007
机器学习在能源与电力系统领域的应用和展望
Machine Learning for Energy and Electric Power Systems:State of the Art and Prospects
摘要
Abstract
The new generation of artificial intelligence (AI), i.e., AI 2.0, has become a research highlight in recent years.Among AI 2.0, 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.AI 2.0 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 AI 2.0 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 AI 2.0, especially ML in the field of EEPS in the future.关键词
人工智能/机器学习/能源与电力系统/智能电网/能源互联网Key words
artificial intelligence (AI)/machine learning/energy and electric power system (EEPS)/smart grid/energy interconnection引用本文复制引用
程乐峰,余涛,张孝顺,殷林飞..机器学习在能源与电力系统领域的应用和展望[J].电力系统自动化,2019,43(1):15-31,17.基金项目
国家自然科学基金资助项目(51477055,51777078) （51477055,51777078）
中国南方电网有限责任公司重点科技项目(GZKJQQ00000419) This work is supported by National Natural Science Foundation of China (No. 51477055 , No. 51777078 ), and Key Science and Technology Projects of China Southern Power Grid Company Limited (No. GZKJQQ00000419). （GZKJQQ00000419）
