Abstract: In this work, a Multi-Level Artificial Bee Colony
(called MLABC) for optimizing numerical test functions is presented.
In MLABC, two species are used. The first species employs n
colonies where each of them optimizes the complete solution vector.
The cooperation between these colonies is carried out by exchanging
information through a leader colony, which contains a set of elite
bees. The second species uses a cooperative approach in which the
complete solution vector is divided to k sub-vectors, and each of
these sub-vectors is optimized by a colony. The cooperation between
these colonies is carried out by compiling sub-vectors into the
complete solution vector. Finally, the cooperation between two
species is obtained by exchanging information. The proposed
algorithm is tested on a set of well-known test functions. The results
show that MLABC algorithm provides efficiency and robustness to
solve numerical functions.
Abstract: Distributed Generation (DG) systems are considered an integral part in future distribution system planning. Appropriate size and location of distributed generation plays a significant role in minimizing power losses in distribution systems. Among the benefits of distributed generation is the reduction in active power losses, which can improve the system performance, reliability and power quality. In this paper, Artificial Bee Colony (ABC) algorithm is proposed to determine the optimal DG-unit size and location by loss sensitivity index in order to minimize the real power loss, total harmonic distortion (THD) and voltage sag index improvement. Simulation study is conducted on 69-bus radial test system to verify the efficacy of the proposed method.