Picture of wind turbine against blue sky

Open Access research with a real impact...

The Strathprints institutional repository is a digital archive of University of Strathclyde research outputs.

The Energy Systems Research Unit (ESRU) within Strathclyde's Department of Mechanical and Aerospace Engineering is producing Open Access research that can help society deploy and optimise renewable energy systems, such as wind turbine technology.

Explore wind turbine research in Strathprints

Explore all of Strathclyde's Open Access research content

Hybrid GA neuro-fuzzy damping control system for UPFC

Khan, Laiq and Lo, K.L. and Jovanovic, S. (2006) Hybrid GA neuro-fuzzy damping control system for UPFC. COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, 25 (4). pp. 841-861. ISSN 0332-1649

Full text not available in this repository. (Request a copy from the Strathclyde author)

Abstract

The aim of the paper is to develop a novel genetic algorithm (GA)-based supplementary NeuroFuzzy damping control system for the unified power flow controller (UPFC). The designed scheme employs a micro-GA (µ-GA) to avoid being trapped in a local minimum as opposed to the use of the classical back-propagation technique. The scheme also uses the "Grand-Parenting" technique for seeding the initial population to hasten the GA convergence speed. To further speed up the GA for solving the optimization problem, a parallel µ-GA scheme is also used. It has been discovered that a parallel µ-GA scheme with three computers setup is approximately three times faster than the µ-GA with a single computer node. Also when µ-GA is integrated with the "Grand-Parenting" technique for seeding the initial population, it would hasten the convergence speed. The control scheme exhibits strong robustness and excellent damping performance when tested on a multi-machine power system.