On possibilistic and probabilistic uncertainty assessment of power flow problem: A review and a new approach

被引:83
作者
Aien, Morteza [1 ,2 ]
Rashidinejad, Masoud [2 ,3 ]
Fotuhi-Firuzabad, Mahmud [4 ]
机构
[1] Grad Univ Adv Technol, Dept Energy, Kerman, Iran
[2] Kerman Chamber Commerce Ind Mines & Agr, Energy & Ind Commiss, Kerman, Iran
[3] Shahid Bahonar Univ Kerman, Dept Elect Engn, Kerman, Iran
[4] Sharif Univ Technol, Dept Elect Engn, Ctr Excellence Power Syst Management & Control CE, Tehran, Iran
关键词
Probabilistic uncertainty modeling; Possibilistic uncertainty modeling; Uncertain power flow; Unscented Transformation; LOAD-FLOW; MONTE-CARLO; GENERATION; MODEL; PROPAGATION; SYSTEMS;
D O I
10.1016/j.rser.2014.05.063
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
As energy resource planning associated with environmental consideration are getting more and more challenging all around the world, the penetration of distributed energy resources (DERs) mainly those harvesting renewable energies (REs) ascend with an unprecedented rate. This fact causes new uncertainties to the power system context; ergo, the uncertainty analysis of the system performance seems necessary. In general, uncertainties in any engineering system study can be represented probabilistically or possibilistically. When sufficient historical data of the system variables is not available, a probability density function (PDF) might not be defined, while they must be represented in another manner i.e. possibilistically. When some of system uncertain variables are probabilistic and some are possibilistic, neither the conventional pure probabilistic nor pure possibilistic methods can be implemented. Hence, a combined solution methodology is needed. This paper proposes a new analytical probabilistic- possibilistic tool for the power flow uncertainty assessment. The proposed methodology is based upon the evidence theory and joint propagation of possibilistic and probabilistic uncertainties. This possibilistic-probabilistic formulation is solved in an uncertain power flow (UPF) study problem. (C) 2014 Elsevier Ltd. All rights reserved.
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页码:883 / 895
页数:13
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