LAPSE:2019.1501
Published Article
LAPSE:2019.1501
Probabilistic Power Flow Method Considering Continuous and Discrete Variables
Xuexia Zhang, Zhiqi Guo, Weirong Chen
December 10, 2019
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).
Keywords
cumulant method (CM), deterministic power flow (DPF) calculation, discrete variable, probabilistic power flow (PPF)
Suggested Citation
Zhang X, Guo Z, Chen W. Probabilistic Power Flow Method Considering Continuous and Discrete Variables. (2019). LAPSE:2019.1501
Author Affiliations
Zhang X: School of Electrical Engineering, Southwest Jiaotong University, Chengdu 610031, China
Guo Z: School of Electrical Engineering, Southwest Jiaotong University, Chengdu 610031, China
Chen W: School of Electrical Engineering, Southwest Jiaotong University, Chengdu 610031, China
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Journal Name
Energies
Volume
10
Issue
5
Article Number
E590
Year
2017
Publication Date
2017-04-26
Published Version
ISSN
1996-1073
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PII: en10050590, Publication Type: Journal Article
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LAPSE:2019.1501
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doi:10.3390/en10050590
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Dec 10, 2019
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Dec 10, 2019
 
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Original Submitter
Calvin Tsay
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