A hybrid metaheuristic optimization algorithm for distributed generation placement in

Due to increased demand for energy and a growing concern for the environment, Distributed Generation (DG) is now a very important element of many modern Power Systems. The objective of this research paper is to determine the Optimal Location(s) at which DG can be placed in Radial Distribution Networks (RDN) so as to minimize losses and improve voltage performance in the presence of the uncertainties associated with load variation and generation variability. Loss Sensitivity Factors (LSFs) are typically used to assist with the identification of buses suitable for the placement of DG, but they are limited by the linear approximation underlying LSFs and do not guarantee a global optimal solution. To supplement and improve the use of LSFs, a hybrid metaheuristic optimization for distributed generation placement in distribution systems has been developed by integrating the Gravitational Search Algorithm with the Sine Cosine Levy Flight Algorithm (GSA-SCLFA). This hybrid approach provides both a global exploration and a local exploitation capability which leads to a more effective way of placing DG. In addition to producing significant reductions in losses and improved voltage profiles, the hybrid approach produces a validation of the GSA-SCLFA approach through IEEE 33 and IEEE 69 bus Radial Distribution Networks, and thus demonstrates its superiority over the conventional and state-of-the-art optimization techniques. The performance results obtained through the use of the MATLAB/Simulink software package confirm the greater effectiveness of the proposed GSA-SCLFA approach compared to the other optimization techniques.