Dingo Optimization Algorithm for Sizing and Allocation of Wind Energy Systems in Radial Distribution System

Many studies have investigated Distributed Generation (DG) using Renewable Energy Sources (RESs) to treat the rising global energy demand. These renewable sources also help reduce the environmental impacts associated with conventional power plants. Proper sizing and placement of DGs based on RESs are essential for improving the reliability, power quality, and bus voltage profile, power quality, and in Radial Distribution Systems (RDSs), especially about active losses. This work focuses on the use of DG represented by wind power systems in RDS. Therefore, in this study, wind turbines (WT), which is one of the most commonly utilized RES, are selected to give the optimized placing and volume. This optimization, which was carried out using the Dingo Optimization Algorithm (DOA), aims to improve system reliability by reducing active losses and improving the profile and quality of the voltage. The IEEE 69-bus system is used to test the performance of the developed method. Results indicate that the proposed DOA method not only correctly located the optimal size and placement of the WT as well, but also improved the voltage profile, and reduced active losses over existing methods. In addition, the developed DOA is proven to be effective for various types of loading constraints.