| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 399824 | International Journal of Electrical Power & Energy Systems | 2013 | 7 Pages |
The power system needs to satisfy its customers demand with minimum cost and emission. Fuel cost has straight relationship with energy cost. This paper presents an advanced parallelized particle swarm optimization algorithm (PSPSO) for finding optimal combination of power generation units that minimizes the total fuel cost and emission. In this algorithm, time requirements for solving complex large-scale CEED problem can be substantially reduced using parallel computation and it performs the update of positions and velocities in the end of each iteration. The proposed approach is applied on four test systems and compared with other techniques. The results represent that PSPSO has better convergence than other techniques.
► A new parallel PSO (PSPSO) algorithm is proposed for solving CEED problem. ► The PSPSO updates all particle velocities and positions at the end of each iteration. ► The PSPSO improves calculation time and convergence. ► The robustness of the PSPSO is demonstrated through the application of it to four standard problems of power systems. ► The multi-objective problem is converted into single-objective form by means of price penalty factor.
