Global Energy Interconnection Journal Press

Home > View > Focus

Research and application of artificial intelligence service platform for the power field

2020-08-14

Research and application of artificial intelligence service platform for the power field

面向能源领域的人工智能服务平台研究与应用

Peng Liu¹, Wei Jiang², Xiaohui Wang¹, Hongmin Li¹, Hongjian Sun³

（1.China Electric Power Research Institute Co. Ltd., Beijing, 100192, P.R. China 2.State Grid Corporation of China, No. 86, West Chang'an Street, Xicheng District, Beijing, 100031, P.R. China 3.University of Durham, The Palatine Centre, Stockton Road, Durham, DH1 3LE, U.K.）

一分钟语音讲解

【HTML】【PDF】

Abstract

Conventional analysis methods cannot fully meet the business needs of power grids. At present, several artificial intelligence (AI) projects in a single business field are competing with each other, and the interfaces between the systems lack unified specifications. Therefore, it is imperative to establish a comprehensive service platform. In this paper, an AI platform framework for power fields is proposed; it adopts the deep learning technology to support natural language processing and computer vision services. On one hand, it can provide an algorithm, a model, and service support for power- enterprise applications, and on the other hand, it can provide a large number of heterogeneous data processing, algorithm libraries, intelligent services, model managements, typical application scenarios, and other services for different levels of business personnel. The establishment of the platform framework could break data barrier, improve portability of technology, avoid the investment waste caused by repeated constructions, and lay the foundation for the construction of “platform + application + service” ecological chain.

Keywords

Artificial intelligence platform, Deep learning, Neural network, Model training, Application scenarios.

Fig.1 Application architecture of electric AI platform

Fig.2 Technical architecture of the electric AI platform

Fig.3 Data architecture of the electric AI platform

Fig.4 Deployment architecture of the electric AI platform

本文引文信息

Liu P, Jiang W, Wang X, Li H, Sun H (2020) Research and application of artificial intelligence service platform for the power field. Global Energy Interconnection, 3(2): 175-185

刘鹏，蒋炜，王晓辉，李宏敏，孙宏建 (2020) 面向能源领域的人工智能服务平台研究与应用. 全球能源互联网（英文），3(2): 175-185

Biographies

Peng Liu

received Master’s degree from North China Electric Power University, Hebei, 2014 and Bachelor’s degree from Qingdao University of Science and Technology, Shandong, 2011. He is currently working at the China Electric Power Research Institute Co. Ltd., Beijing. His research interests include power big data platform, artificial intelligence technology, and Internet operation platform.

Wei Jiang

received doctor’s degree at Zhejiang University, Zhejiang, 2013. He is working in State Grid Corporation of China, Beijing. His research interests includes power big data technology, artificial intelligence platform and energy blockchain technology.

Xiaohui Wang

received the Doctor’s degree from North China Electric Power University, Beijing, 2012. He is currently working at the China Electric Power Research Insti- tute Co. Ltd., Beijing. His research interests include power big data technology, artificial intelligence, active distributed network, energy internet.

HongMin Li

received the Master’s degree from North China Electric Power University, Hebei, 2013 and Bachelor’s degree from North China Electric Power University, Hebei, 2010. She is working at the China Electric Power Re- search Institute Co. Ltd., Beijing. Her research interests include platform development and data visualization.

Hongjian Sun

(IEEE, S'07-M'11-SM'15)received the Ph.D. degree in Electronic and Electrical Engineering from the University of Edinburgh, U.K., in 2011. He held post- doctoral positions with King's College London, U.K., and Princeton University, USA. Since 2013, he has been with the University of Durham, U.K., as a Reader in Smart Grid (with a Lecturer position in 2013-2017).

Editor：Zhou Zhou