Interval Distribution Power Flow With Relative-Distance-Measure Arithmetic

Interval distribution power flow can analyze the uncertainties incurred by the random fluctuations of distributed renewable generation and load demand in distribution networks. The conventional interval arithmetic (IA) and affine arithmetic (AA) cannot fully apply the characteristics of general alge...

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Bibliographic Details
Published in:IEEE transactions on smart grid Vol. 12; no. 5; pp. 3858 - 3867
Main Authors: Ngo, Vietcuong, Wu, Wenchuan
Format: Journal Article
Language:English
Published: Piscataway IEEE 01.09.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Associativity
Correlation
Distribution network
Electric power distribution
Interval arithmetic
interval power flow
Linear programming
linear programming contractor
Load flow
Monte Carlo methods
Optimization
Power flow
Power systems
relative-distance-measure arithmetic
Reliability
Stress concentration
Uncertainty
ISSN:1949-3053, 1949-3061
Online Access:Get full text
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Summary:Interval distribution power flow can analyze the uncertainties incurred by the random fluctuations of distributed renewable generation and load demand in distribution networks. The conventional interval arithmetic (IA) and affine arithmetic (AA) cannot fully apply the characteristics of general algebra: associativity, inverse elements, distributive law, so the IA or AA based interval power flows (IPFs) are either very conservative or unreliable. Relative-Distance-Measure (RDM) arithmetic can overcome these defects in the conventional arithmetic for interval analysis and therefore a RDM based IPF is proposed in this paper. Furthermore, a linear programming contractor (LPC) is developed to solve this RDM based IPF, which can iteratively transform the IPF problem into serial linear optimization models and its results are reliable. Simulation results of IEEE 123-bus test systems show that the proposed IPF can obtain much better results than those of baseline methods in terms of accuracy and reliability.
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ISSN:1949-3053
1949-3061
DOI:10.1109/TSG.2021.3074018