حل مشکلات اقتصادی همراه با بارگیری و انتشار با استفاده از الگوریتم جدید اکتشافی

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.