Document Type : Original Article
Electrical Engineering Department, Engineering Faculty, Razi University, Kermanshah, Iran.
Electrical Engineering Department, Engineering Faculty, Razi University, Kermanshah, Iran
This study addresses Civilized Gravitational Search Algorithm (CGSA) as a new mass intelligence optimization algorithm for solving optimal single and multiple DG placement problems in the electrical distribution networks. The proposed technique utilizes the modified search procedure of Society Civilization Algorithm (SCA) combining with Newtonian laws of GSA. It mainly consists of two steps. The first step provides a candidate list for DG allocation based on active power loss minimization and the second one searches simultaneously the optimal DG size(s) and location(s) using Self-Adoptive Learning (SAL) strategy. In order to verify the capabilities and effectiveness of the suggested approach, all simulations are conducted through IEEE 33- and 69-bus electrical distribution networks. Moreover, 23 standard functions are examined to verify the stability of the proposed algorithm on different low- and high-dimensional functions. Comparisons demonstrate the superior performance of the presented method to provide better solution quality with a fast convergence characteristic.