Author/Authors :
Keshavarz، Mohsen نويسنده Department of Electrical and Computer Engineering, Science and Research Branch, Islamic Azad University, Saveh, Iran , , Ranjbar، Ali Mohammad نويسنده Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran , , Sedighizadeh، Mostafa نويسنده Faculty of Electrical and Computer Engineering, Shahid Beheshti University, Tehran, Iran , , Sheikhi، Aras نويسنده Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran ,
Abstract :
Nowadays, given the rapid growth of socioeconomic
issues, more emphasis is being placed upon
providing the consumers with higher quality services.
Consequently, many modern societies are seeking to use
new energy management systems to reduce the
environmental pollutions and operational costs resulting
from electrical energy generation systems. So, benefiting
from various renewable energy resources, Micro Grid
(MG) could be considered as a substantial tool to reach
such objectives. According to this matter, the present
paper is aimed at introducing the, multiobjective Hybrid
Big Bang - Big Crunch (HBB-BC) algorithm to be used
for optimizing a sample MG. The problem is assumed to
be an optimization problem with nonlinear multiple
objectives, having different qualities and non-equal
limitations in order to reduce the cost and distribution of
pollutants. The proposed algorithm is applied in a sample
MG and the results are compared with other optimizing
algorithms such as particle swarm optimization (PSO)
and Big Bang - Big Crunch (BB-BC).
