A Minimax Polynomial Approximation Objective Function Approach for Optimal Design of Power System Stabilizer by Embedding Particle Swarm Optimization

Bhanu Pratap Soni, Akash Saxena, Vikas Gupta


The paper presents a novel approach based on Minimax approximation and evolutionary tool Particle Swarm Optimization (PSO) to fabricate the parameters of Power System Stabilizers (PSSs) for multi machine power systems. The proposed approach employs PSO algorithm for find the setting of PSS parameters. The worth mentioning feature of this work is the formulation of objective function with the help of swing curves interpolation. A novel transformation known as minimax approximation is used for converting the objective into the polynomials of degree one, two and three. To construct the objective function based on interpolation second order sensitivity analysis is performed. The performance of the PSSs is tested under different topological changes, operating conditions and system configurations. Nonlinear simulation reveals that proposed PSSs are effectively deal with local and interarea modes of oscillations. PSS design obtained through lower order polynomial expression of objective function is able to deal with the oscillatory modes efficiently.


DOI: http://dx.doi.org/10.11591/telkomnika.v14i2.7602


Power System Stabilizer (PSS); Particle Swarm optimization (PSO); Automatic Voltage Regu-lator (AVR); Minimax Approximation

Full Text:



  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

shopify stats IJEECS visitor statistics