Browsing by Author "Chai, Yanxin"

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    Agricultural Load Modeling Based on Crop Evapotranspiration and Light Integration for Economic Operation of Greenhouse Power Systems
    (Chinese Society for Electrical Engineering (CSEE) in collaboration with CEPRI (China Electric Power Research Institute) and IEEE, 2019-12-07) Li, Zeming; Liu, Junyong; Xiang, Yue; Zhang, Xin; Chai, Yanxin
    The threat of environmental degradation attracts great attention to clean energy production and transportation. However, the limited scope of energy consumption causes large-scale of clean energy sources to be abandoned in Sichuan province. In the meantime, the development of modern greenhouse cultivation has transformed the agriculture industry to have a brand-new type of electrical load in the grid. Consequently, the agricultural load can be used to consume the clean energy while facilitating plant growth. In this paper, an innovative agricultural load model is proposed based on crop evapotranspiration and daily light integration. Furthermore, the proposed agricultural load model is also applied to investigate the electricity consumption of five types of crop planting. The results illustrate that the power consumption is primarily driven by artificial lighting compensation system.
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    Slope-based shape cluster method for smart metering load profiles
    (IEEE, 2020-01-10) Xiang, Yue; Hong, Juhua; Yang, Zhiyu; Wang, Yang; Huang, Yuan; Zhang, Xin; Chai, Yanxin; Yao, Haotian
    Cluster analysis is used to study the group of load profiles from smart meters to improve the operability in distribution network. The traditional K-means clustering analysis method employs Euclidean distance as similarity measurement, which is insufficient in reflecting the shape similarities of load profiles. In this work, we propose a novel shape cluster method based on the segmented slope of load profiles. Compared with traditional K-means and two improved algorithms, the proposed method can improve the clustering accuracy and efficiency by capturing the shape features of smart metering load profiles.