Optimal Integration of Multiple Renewable Energy Distributed Generations using Hybrid Optimization Technique

Recent times, the assimilation of renewable energy (RE) based distributed generation (DG) units in power distribution system (PDS) have become a major research area in electric power systems to improve the overall efficiency of PDS by reducing power losses and voltage drops. But, it is desired to integrate DG units at optimal place(s) and size(s) in order to achieve the anticipated objective(s). In this work, a hybrid optimization method using loss sensitivity factor (LSF) and a cuckoo search (CS) meta-heuristic algorithm is implemented for optimizing multiple renewable energy DG units in radial PDS to minimize total real power losses (TRPL). The proposed hybrid technique locates the optimal sites for DG placement using LSF and computes the optimal sizes via CSA. Besides, the computation of LSF significantly curtailed the search area for CSA to optimize DG sizes. The suggested hybrid optimization method is executed on standard symmetrical IEEE radial PDSs with 33 buses and 69 buses. The simulation study for the proposed technique is investigated for multiple Type I (solar photovoltaic system) and Type III (wind turbine) DG allocation. Furthermore, a numerical comparative analysis is performed between proposed and other optimization methods to assess effectiveness of proposed technique. The outcome of the comparative study highlighted that the proposed hybrid technique-based allocation of multiple RE-DGs achieved maximum power loss reduction and better voltage profile than other techniques. Furthermore, the outcome of this research work notified that Type III DG allocation has achieved more objective function minimization than Type I DG allocation.