基于强化学习的电采暖负荷类型识别研究  

Research on Electric Heating Load Type Identification Based on Reinforcement Learning

作　　者：杨安云 孙宏彬[1] YANG Anyun;SUN Hongbin(Changchun Institute of Technology,Changchun 130012,China)

机构地区：[1]长春工程学院,吉林长春130012

出　　处：《现代信息科技》2021年第9期10-12,15,共4页Modern Information Technology

基　　金：吉林省科技计划项目(20180101057JC,20190302106GX)。

摘　　要：随着新能源技术以及智能电网的发展,电采暖技术也得到了广泛的应用。若要促进该技术快速健康发展,电采暖负荷类型的有效识别尤为关键。因此,文章提出了基于强化学习的电采暖识别方法。文章首先介绍了结合K-Means和最大期望(EM)方法对实际功率数据进行聚类的方式,然后建立针对电采暖识别的强化学习的框架,最后对处理后的电采暖数据进行识别验证,分析验证了该方法的可行性。With the development of new energy technology and smart grid,electric heating technology has also been widely used.In order to promote the rapid and healthy development of this technology,the effective identification of electric heating load type is particularly important.Therefore,this paper proposes an electric heating identification method based on reinforcement learning.It first introduces the way of clustering the actual power data by combining K-means and expectation maximum(EM)method,and then establishes a reinforcement learning framework for electric heating identification.Finally,the processed electric heating data is identified and verified,and the feasibility of this method is analyzed and verified.

关 键 词：电采暖 强化学习 分类识别 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]