Economic dispatch using particle swarm optimization with bacterial foraging effect

This paper presents a novel modified particle swarm optimization (MPSO), which includes advantages of bacterial foraging (BF) and PSO for constrained dynamic economic dispatch (ED) problem. The proposed modified PSO consists of problem dependent four promising values in velocity vector to incorporate repellent advantage of bacterial foraging in PSO for the complex dynamic ED problem. It reliably and accurately tracks a continuously changing solution of the complex cost functions. As there is no differentiation operation in this method, all cost functions can easily be handled. The modified PSO has better balance between local and global search abilities and it can avoid local minima quickly. Finally, a benchmark data set and existing methods are used to show the effectiveness of the proposed method.

► A novel modified particle swarm optimization (PSO) for dynamic ED. ► An appropriate introduction of bacterial foraging effect in PSO. ► Potential application for real-time operation of dynamic ED and unit commitment.