PSO algorithm for optimal placement of photovoltaic in distribution system

The progress made in the technology of photo voltaic (PV) has demonstrated potential in addressing the global demand for energy, reducing carbon dioxide (CO2) emissions, and safeguarding the ecosystem. The positioning of PV panels within the distribution network can considerably influence the overall system efficiency.. The best location for PV panels in a distribution system must be determined, however this is a difficult task with many requirements. In this case, tackling optimization problems has proven to be successful with the Particle Swarm Optimization (PSO) algorithm. A meta-heuristic optimization technique called the PSO algorithm mimics the behavior of bird flocks. It has been extensively used to identify the best solutions in many different industries, including renewable energy systems.The use of PSO algorithms to find the appropriate location and size of solar panels in the electrical grid system.The program looks at a number of variables, including power losses, voltage stability, and system capacity, to identify the best location that complies with the requirements and achieves the goals. The PSO algorithm has a number of benefits over conventional optimization methods, including ease of use, adaptability, and quick convergence. It utilizes a variety of standards to address a variety of issues in accordance with the goals. In order to enhance performance and make the integration of renewable energy sources easier, the PSO algorithm can be a valuable tool for figuring out where PV panels should be installed in a distribution system. E-TAP is a cutting-edge program for comprehensive power system analysis. In this work used Newton Raphson Method(NR) to analysis distribution system (IEEE-5 Bus Bar) with E-TAP software we get all power system voltage level, losses, load flow…etc. by code of Mat lab program for NR and PSO algorithm find the optimum location Bas Bar and size to connect PV system, find out voltage level before and after and see the level improving by using optimal location and size of PV system.