Ali, Isam TahaYahya, Adel E. M.Amer, AymanSarreb, Rebha DawYahya, KhalidAldababsa, MahmoudHafez, Mohamed2024-09-112024-09-112023979-835037336-3https://doi.org/10.1109/EICEEAI60672.2023.10590146https://hdl.handle.net/11363/85992nd International Engineering Conference on Electrical, Energy, and Artificial Intelligence, EICEEAI 2023 -- 27 December 2023 through 28 December 2023 -- Zarqa -- 201143Photovoltaics (PV) are a rapidly growing source of energy worldwide and are typically installed as distributed generation in distribution systems. PV technology has emerged as a promising solution for increasing power demand and reducing greenhouse gas emissions. Placing PV systems in distribution systems is crucial for overall performance, but it is a complex task with multiple constraints and objectives. Particle Swarm Optimization (PSO) is a metaheuristic optimization technique based on bird flocking behavior that has proven to be a valuable tool for solving optimization problems. The PSO algorithm can find the optimal location, size, and orientation of PV panels in a distribution system, considering power losses, voltage stability, and system capacity. This work analyzes the Kirkuk City Power System (IEEE-5 BusBar) to find the optimal location and size for PV systems, improve voltage levels, and reduce losses. The PSO algorithm compares the power system before and after connecting the PV system. © 2023 IEEE.eninfo:eu-repo/semantics/closedAccessDistribution System; Optimum Placement; PSO; PVConference Object10.1109/EICEEAI60672.2023.105901462-s2.0-85200009627N/A