Hybrid fuzzy particle swarm optimization approach for reactive power optimization

Abstract EN

This paper presents a new approach to the optimal reactive power planning based on fuzzy logic and particle swarm optimization (PSO).

The objectives are to minimize real power loss and to improve the voltage profile of a given interconnected power system.

Transmission loss is expressed in terms of voltage increments by relating the control variables i.e.

reactive var generations by the generators, tap positions of transformers and reactive power injections by the shunt capacitors.

The objective function and the constraints are modeled by fuzzy sets.

A term ‘sensitivity’ at each bus is defined which depends on variation of real power loss with respect to the voltage at that bus.

Based on the Fuzzy membership values of the sensitivity, corrective action at a particular bus is taken i.e.

shunt capacitors are installed at the candidate buses based on real power loss and sets of solution.

Then, PSO is applied to get final solution.

PSO is used for optimal setting of transformer tap positions and reactive generations of generators.

The solution obtained by this method is compared with the solutions obtained by other evolutionary algorithms like genetic algorithm (GA), differential evolution (DE) and particle swarm optimization (PSO).