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作 者:张宁[1] 余扬昊 章家维 王毅[1] 刘羽霄 杨经纬 朱桂萍[1] ZHANG Ning;YU Yanghao;ZHANG Jiawei;WANG Yi;LIU Yuxiao;YANG Jingwei;ZHU Guiping(Department of Electrical Engineering,Tsinghua University,Haidian District,Beijing 100084,China)
机构地区:[1]清华大学电机工程与应用电子技术系,北京市海淀区100084
出 处:《中国电机工程学报》2023年第19期7749-7758,共10页Proceedings of the CSEE
基 金:清华大学本科生教育教学改革项目“电气工程学科《大数据技术及应用》课程竞争性课程实验设计与实施”(ZY01_02)。
摘 要:随着信息与数字技术的不断发展,大数据技术为电气学科带来了深远的影响,现有的电气工程本科人才培养中亟需补充大数据技术的相关知识。该文以清华大学电机系开设的“大数据技术及应用”课程为基础,总结面向电气工程学科的大数据课程的构建思路、教学实践与思考。综述大数据技术在电气工程领域的应用情况,提出面向电气工程的大数据教学的课程内容设计3大原则,构建“基础先导–机器学习模型与方法–电力系统应用–课程探索研究与展示”四阶段教学大纲。此外,课程在竞争性实验方面进行探索实践,培养学生的数据思维及解决电力系统实际问题的能力,通过引入实时反馈机制促进学生的持续思考与反复迭代。本课程希望通过大数据技术与电气工程学科前沿的教学探索,为我国高校电气类专业开设同类型课程提供有价值的参考。With the continuous development of information and digital technology,big data technology has brought profound influence to electrical engineering discipline.There is an urgent need to supplement relevant courses for cultivating electrical engineering undergraduates.Based on the course of"Big Data Technology and Its Applications"offered by the Department of Electrical Engineering,Tsinghua University,this paper introduces the construction,practice experience and thinking of big data teaching for electrical engineering.This paper reviews the application of big data technology in electrical engineering,puts forward three principles of content design of big data teaching for electrical engineering.A four-stage syllabus is proposed including mathematical basis,machine learning model and method,applications in power system,and research exploration.In addition,the course has carried out practice in competitive experiments to improve students’ability to solve power system practical problems using big data thinking.By introducing real-time feedback mechanism,the research curiosity of students'is promoted so that the learning experience is improved.Through the exploration of big data technology and electrical engineering,this course hopes to provide a reference for the construction of similar courses for universities in China.
关 键 词:大数据技术 机器学习 能源互联网 电力系统 竞争性实验
分 类 号:TM74[电气工程—电力系统及自动化]
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