Probabilistic Power Flow Method Considering Continuous and Discrete Variables

被引:4
|
作者
Zhang, Xuexia [1 ]
Guo, Zhiqi [1 ]
Chen, Weirong [1 ]
机构
[1] Southwest Jiaotong Univ, Sch Elect Engn, Chengdu 610031, Peoples R China
来源
ENERGIES | 2017年 / 10卷 / 05期
关键词
probabilistic power flow (PPF); discrete variable; cumulant method (CM); deterministic power flow (DPF) calculation; LOAD FLOW; DISTRIBUTION NETWORKS; PENETRATION; CUMULANTS; SYSTEMS;
D O I
10.3390/en10050590
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
This paper proposes a probabilistic power flow (PPF) method considering continuous and discrete variables (continuous and discrete power flow, CDPF) for power systems. The proposed method-based on the cumulant method (CM) and multiple deterministic power flow (MDPF) calculations-can deal with continuous variables such as wind power generation (WPG) and loads, and discrete variables such as fuel cell generation (FCG). In this paper, continuous variables follow a normal distribution (loads) or a non-normal distribution (WPG), and discrete variables follow a binomial distribution (FCG). Through testing on IEEE 14-bus and IEEE 118-bus power systems, the proposed method (CDPF) has better accuracy compared with the CM, and higher efficiency compared with the Monte Carlo simulation method (MCSM).
引用
收藏
页数:17
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