Reliability Analysis for an Optimal Dg Placement and Sizing for A Radial Distribution System

An increase in population results in the abandonment of the consumption of power, which results in a raise in the demand for power and a raise in environmental interest that has set the trend toward distributed energy sources. Hence, the present energy system is prone to various types of losses. Reliability has become a crucial factor in the distribution network. A system’s reliability was assessed by its capability of providing a persistent stream of high-quality electricity to the consumer, and it is often examined by employing the right indications. Many simulated, analytical, and heuristic algorithms are used for DG positioning, allocating, and delivering higher precision and consolidation. Too many simulation methods are employed in the literary works and the implementation of different software is given importance used by the various authors. For Type 1 appropriate placement and capacity Distributed Generator devices in the RDS, the PSO algorithm methodology is employed to examine the impact on system performance and loss reduction. Type I (injects real power) Distributed Generators are the one type of Distributed Generators discussed. The specified load model is constant power. Average Energy Not Supplied (AENS), Total Energy Not Supplied (TENS), & Average System Interruption Duration Index (ASIDI) is the reliability indices used in the investigation of system reliability [1]. The suggested technique’s usefulness is outlined in a 33-bus system with single and multiple Distributed Generators. The large reduction in system power losses, system reliability, and exceptional annual loss savings for the Type One Distributed Generator is compared to other existing research results from investigators. As a result, the obtained results are compared to those of existing analytical techniques along with meta-heuristic methodologies in order to show that the introduced methodology is superior. The outcomes have also been quantitatively validated.