Combined cumulants and Laplace transform method for probabilistic load flow analysis

被引:27
|
作者
Kenari, Meghdad Tourandaz [1 ]
Sepasian, Mohammad Sadegh [1 ]
Nazar, Mehrdad Setayesh [1 ]
Mohammadpour, Hossein Ali [2 ]
机构
[1] Shahid Beheshti Univ, Dept Elect Engn, Tehran, Iran
[2] Sargent & Lundy LLC, EAD, Chicago, IL 60603 USA
关键词
Laplace transforms; higher order statistics; probability; statistical distributions; load flow; power system planning; combined cumulants-Laplace transform method; power systems development; system element uncertainty; continuous probability distribution function; input random variable; MATPOWER 9-test systems; 118-bus test systems; CCLT technique; Monte Carlo simulation; cumulants with maximum entropy principle; CCME principle; GRAM-CHARLIER EXPANSION; POWER-FLOW; DENSITY-FUNCTION; MAXIMUM-ENTROPY; WIND GENERATION; COMPUTATION; SYSTEMS; SIMULATION;
D O I
10.1049/iet-gtd.2017.0097
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The simultaneity of power systems development and uncertainty of system elements has promoted the importance of probabilistic load flow (PLF) in the operating and planning studies of the system. This clarifies that the use of the fast and accurate approaches for PLF computation is necessary. To achieve this objective, this study presents an analytical technique, based on the properties of Laplace transform (LT). The suggested methodology is applicable for every continuous probability distribution function as the input random variable. The proposed procedure is applied to the MATPOWER 9- and 118-bus test systems. To validate the combined cumulants and LT (CCLT) technique, the results are compared with the Monte Carlo simulation and the cumulants method combined with the maximum entropy (CCME) principle. The test results show that the proposed approach gives accurate results, with the lower computational burden comparing CCME. Furthermore, the method formulation and case study results demonstrate that the CCLT method is mathematically straightforward and computationally efficient.
引用
收藏
页码:3548 / 3556
页数:9
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