Research on Deep Belief Network of Wind Power Control Management Unit Based on Attack Identification. (September 2020)

• Record Type: Journal Article
• Authors: Liu, Wei; Huang, Zhiwei; Chen, Rui; Ding, Kai; Zhu, Xiaofan; Zhou, Junfeng; Zhou, Guoqi; He, Shengguo; He, Hongyan; Xiao, Shengyuan; Lu, Feng; Wang, Guoyou; Ning, Baifeng; Ding, Qing
• Is Part Of: Journal of physics. Volume 1646(2020)
• Publication Date: 2020-09
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1646/1/012120
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: With the continuous improvement of the level of economic development and the increasingly serious environmental problems, countries around the world are focusing more on renewable energy. Wind energy is an important category of renewable energy because of its advantages. However, wind power is very dependent on the climate environment. It operates in an open operating environment, and its communication depends on the network interaction method. With the proposal of the Internet of Everything, the power grid is developing in the direction of information and intelligence. There are more and more attacks, and the security and stability of wind power interface devices have been threatened. As the power grid involves many areas and households, once the power outage occurs, the economic losses will be huge and even cause major security accidents. This paper proposes a deep belief network research of wind power control management unit based on attack recognition to improve the safety and operational reliability of wind power generation.