PROBABILISTIC DISTRIBUTION BASED INTERVAL ARITHMETIC LOAD FLOW ALGORITHM FOR RADIAL DISTRIBUTION SYSTEM

Load flow is an essential tool for the study of radial distribution systems (RDS). The inputs to load flow solutions are subject to uncertainties due to load and line parameter variations. Unfortunately, load flow research has to date considered only fixed load and line parameters; inherent uncertai...

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Published inInternational journal of power & energy systems Vol. 26; no. 2; pp. 193 - 201
Main Authors Chaturvedi, A., Ranjan, R., Prasad, K., Sahoo, N.C.
Format Journal Article
LanguageEnglish
Published Anaheim, CA International Association of Science and Technology for Development 2006
Calgary, AB ACTA Press
Zurich
Subjects
Algorithms
Applied sciences
Computer simulation
Data collection
Electrical engineering. Electrical power engineering
Electrical power engineering
Electricity distribution
Exact sciences and technology
Interval arithmetic
Load
Load distribution
Methods
Normal distribution
Power networks and lines
Power supply
Standard deviation
Studies
Systems analysis
Uncertainty
Radial distribution
Probabilistic approach
Gaussian distribution
Power distribution planning
radial distribution systems
Interval arithmetic
Load flow
Experimental result
Algorithm performance
Electrical network
Power flow
Distribution function
Numerical simulation
Distribution network
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Summary:Load flow is an essential tool for the study of radial distribution systems (RDS). The inputs to load flow solutions are subject to uncertainties due to load and line parameter variations. Unfortunately, load flow research has to date considered only fixed load and line parameters; inherent uncertainties of the inputs were overlooked. In this article probabilistic distribution-based interval arithmetic approach is proposed to incorporate variations in load parameter. The uncertainties of load variation are represented as Gaussian distribution function. The proposed load flow is tested on standard test systems; the authors find that solutions obtained provide much wider information and all possible solution states are obtained in the closed bounded interval form. It is suggested that proposed power flow could be useful for planning and expansion planning of RDS, where future data always carry a high degree of uncertainties. Composite load model is also incorporated in the algorithm. [PUBLICATION ABSTRACT]
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ISSN:1710-2243
1078-3466
1710-2243
DOI:10.2316/Journal.203.2006.2.203-3540