The demand for electricity continues to grow, distributed generation (DG) offers a viable solution to meet this increasing energy need. DG involves generating electricity on a small scale and placing it directly into the local power grid or where it’s needed. Determining the most advantageous location and appropriate capacity for DG is of utmost importance in improving the voltage stability of the power system, minimizing real power losses (RPL), and maximizing annual cost savings. Optimally situating DG within the distribution system can lead to positive results, including an improved voltage profile and reduced line losses. This paper employs a grey wolf optimizer with memory, evolutionary, and local search technique (MELGWO) to effectively allocate and size distributed generation within distributed networks. The algorithm’s performance is evaluated using test systems comprising 15- and 85-bus systems. The outcomes validate that the method works well in finding the right places and sizes for DGs.