An Enhancement to Cumulant-based Probabilistic Power Flow Methodologies

被引:0
作者
Le, Duong D. [1 ]
Pham, Kien V. [1 ]
Ngo, Duong V. [2 ]
Huynh, Ky V. [2 ]
Nguyen, Nhi T. A. [3 ]
Berizzi, Alberto [3 ]
机构
[1] Danang Univ Sci & Technol, Dept Elect Engn, Danang, Vietnam
[2] Univ Danang, Danang, Vietnam
[3] Politecn Milan, Dept Energy, Milan, Italy
来源
2015 IEEE INNOVATIVE SMART GRID TECHNOLOGIES - ASIA (ISGT ASIA) | 2015年
关键词
Probabilistic power flow; uncertainty; cumulant; renewable energy; GRAM-CHARLIER EXPANSION; MONTE-CARLO-SIMULATION; POINT ESTIMATE METHOD; LOAD-FLOW; WIND; COMPUTATION; SYSTEMS; GENERATORS;
D O I
暂无
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
Renewable energy sources, such as wind and photovoltaic solar, have been increasingly integrated into electricity grids. They have introduced additional uncertainty to power systems along with uncertainty due to stochastic nature of demand. Traditional deterministic power flow does not provide sufficient information for the calculation and analysis of such power systems; therefore, to manage such uncertainties, probabilistic power flow methodologies need to be used. This paper presents a cumulant-based probabilistic power flow approach in which we develop a technique to deal with various probability distributions that represent different sources of uncertainty in power systems. The proposed approach is caried out on the modified IEEE-14 bus test system, showing good performance in comparison with the result obtained by Monte Carlo simulation.
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页数:5
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