An Improved Particle Swarm Optimization for Optimal Power Flow

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Author(s): Dieu Ngoc Vo (Ho Chi Minh City University of Technology, Vietnam)and Peter Schegner (Institute of Electrical Power Systems and High Voltage Engineering & Dresden University of Technology, Germany)
Copyright: 2013
Pages: 40
Source title: Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance
Source Author(s)/Editor(s): Pandian M. Vasant (Petronas University of Technology, Malaysia)
DOI: 10.4018/978-1-4666-2086-5.ch001

Keywords: Algorithms / Artificial Intelligence / Computer Science & IT / Information Science Reference

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Abstract

This chapter proposes a newly improved particle swarm optimization (IPSO) method for solving optimal power flow (OPF) problem. The proposed IPSO is the particle swarm optimization with constriction factor and the particle’s velocity guided by a pseudo-gradient. The pseudo-gradient is to determine the direction for the particles so that they can quickly move to optimal solution. The proposed method has been tested on benchmark functions, the IEEE 14-bus, IEEE 30-bus, IEEE 57-bus, and IEEE-118 bus systems, in which the IEEE 30-bus system is tested with different objective functions including quadratic function, valve point effects, and multiple fuels. The test results have shown that the proposed method can efficiently obtain better total costs than the conventional PSO method. Therefore, the proposed IPSO could be a useful method for implementation in the OPF problem.

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