摘要
近年来,人工智能特别是深度学习技术的迅速发展,给当今社会带来了巨大变革。首先梳理了人工智能尤其是机器学习的关键及前沿技术,阐述了包括强化学习、迁移学习、生成对抗神经网络、胶囊网络和引导学习等几种典型机器学习方法的特点。然后分析了机器学习在电力系统稳定性分析领域、协调调度领域以及负荷预测领域的典型应用场景,对比了其在解决特定问题时的优势。最后对应用情况进行了概括总结,展望了其在电力系统运行领域的应用前景。
In recent years, artificial intelligence, especially deep learning technology, has developed rapidly, bringing about tremendous innovation in social technology. This paper summarizes the key and cutting-edge technologies of artificial intelligence and expounds the characteristics of typical machine learning such as reinforcement learning, migration learning, generation of anti-neural network, capsule network and guided learning;then, it analyzes the deep learning technology in the field of stability analysis, coordination scheduling and load forecasting in the power system operation, which shows its advantages in solving specific problems. Finally, the paper summarizes the application and elaborates on the future application in electric power system operation.
作者
叶琳
杨滢
洪道鉴
陈新建
YE Lin;YANG Ying;HONG Daojian;CHEN Xinjian(State Grid Hangzhou Power Supply Co., Ltd., Hangzhou 310007, China;State Grid Taizhou Power Supply Company, Taizhou Zhejiang 318000, China)
出处
《浙江电力》
2019年第5期83-89,共7页
Zhejiang Electric Power
基金
浙江省电力有限公司科技项目(5211TZ170006)
关键词
人工智能
机器学习
强化学习
迁移学习
对抗神经网络
胶囊网络
引导学习
artificial intelligence
machine learning
reinforcement learning
migration learning
anti-neural network
capsule network
guided learning
作者简介
叶琳(1979), 女, 高级工程师, 从事电网运行方式与稳定分析工作。
