Research Articles

Calculation method of limit line loss of renewable energy distribution network

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  • 1. Research Center for Big Data Engineering and Technologies, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
    2. Development Planning Department, State Grid Shandong Electric Power Company, Jinan 250001, Shandong, China
    3. Linyi Power Supply Company, State Grid Shandong Electric Power Company, Linyi 276000, Shandong, China

Received date: 2019-11-25

  Online published: 2019-12-27

Abstract

With the advancement of renewable energy technology and increasing demand, the access of distributed generations introduces volatility and uncertainty to the power flow distribution within medium voltage distribution networks. Consequently, the volatile and uncertain nature significantly hinders the accurate line loss calculation and establishment of grid assessment indicators. This study proposes a semi-invariant calculation model that aids realize an efficient calculation approach for limit line loss of the distribution network containing renewable energy. Initially, according to the power flow calculation and statistical data, the semi-invariants of each node and generations in the distribution network are calculated. Next, the distribution function and probability density function of each state index are calculated with the Gram-Charlier (GC) series expansion formula. Finally, the limit line loss of the distribution network is determined according to the confidence interval. IEEE34 node system is chosen as an example in this study to analyse the influence of different node distributed power access on distribution network. The calculation accuracy of line loss calculation model based on semi-invariant method and its calculation speed advantage in large-scale distribution network application is verified.

Cite this article

ZHU Yue, GU Jie, WANG Chunyi, MOU Hong, CUI Guozhu, LI Yu, JIN Zhijian . Calculation method of limit line loss of renewable energy distribution network[J]. Journal of Shanghai University, 2021 , 27(5) : 833 -845 . DOI: 10.12066/j.issn.1007-2861.2191

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