Performance Of Newton-Raphson Method For Load Flow Analysis In ILL-Conditioned Systems

Mohamad Zukri, Rabiatul Adawiyah (2018) Performance Of Newton-Raphson Method For Load Flow Analysis In ILL-Conditioned Systems. Project Report. Universiti Sains Malaysia, Pusat Pengajian Kejuruteraan Elektrik dan Elektronik. (Submitted)

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Abstract

Power flow studies are widely used and essential for steady state analysis on power systems. Robustness of power flow is vital to assist engineers on difficult network configurations. In reality, the increase in peak demand and many more factor has increased the concern of the power system as this might cause the system to fall into ill-conditioned system. This paper presents a review of Newton-Raphson method for load flow analysis in ill-conditioned systems. The analysis was carried out on IEEE 30-Bus System via MATLAB programming. The main focus of this paper is to analyse the ill-conditioned cases of high R/X ratio and loading conditions in a transmission system by implementing the conventional Newton-Raphson method on the MATLAB platform. The parameters that are concerned in this research are the iteration number required for the system to converge and the computation time to run the load flow analysis in MATLAB. The value of R/X ratio and loading factor is increased gradually to observe the effect on the performance of Newton-Raphson in load flow analysis. A graphical presentation is included to compare how the increment of R/X ratio in individual lines and a group of lines would affect the iteration numbers of the system to converge. Meanwhile, for loading factor, the iteration number and computation time also being analysed.

Item Type: Monograph (Project Report)
Subjects: T Technology
T Technology > TK Electrical Engineering. Electronics. Nuclear Engineering
Divisions: Kampus Kejuruteraan (Engineering Campus) > Pusat Pengajian Kejuruteraaan Elektrik & Elektronik (School of Electrical & Electronic Engineering) > Monograph
Depositing User: Mr Engku Shahidil Engku Ab Rahman
Date Deposited: 26 Jul 2022 06:31
Last Modified: 26 Jul 2022 06:31
URI: http://eprints.usm.my/id/eprint/53603

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