Renewable Energy Generation and Load Classification based on H-K compound clustering algorithm. (June 2020)

• Record Type: Journal Article
• Authors: Sun, Yong; Li, Zhenyuan; Li, Dexin; Liu, Chang; Wang, Shengyan; Qiu, Fengkai; Zeng, Ming
• Is Part Of: Journal of physics. Volume 1549:Number 5(2020)
• Publication Date: 2020-06
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1549/5/052005
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: In this paper, the uncertainty of diesel generator (hereinafter referred to as DG) output and load demand is studied by multi scenario analysis. Firstly, this paper studies the timing characteristics of DG power generation and load demand, and describes the annual and daily distribution of photovoltaic power generation, wind power generation and load demand. Then it introduces the method of multi scene analysis, describes the process of dealing with the uncertainty in multi scene in detail, and generates enough scenes through the density function of classification probability to get the probability of each scene. Finally, H-K compound clustering algorithm is used to solve the above problems. The scale scene is compressed to get a typical "planning scene".