<p>With a swift transition in popular opinion advocating the application of green innovations to promote the development of a more sustainable world, electric cars and other electric-powered equipment are being used more frequently. By utilizing distributed generation (DG), the burden that this technology places on existing power networks can be significantly reduced. This paper presents the latest developments in the coordinated control of distributed generation and electric vehicles in distribution networks, along with a comprehensive comparative analysis. Two case studies have been discussed: The first focuses on real power loss minimization in a distribution system using distributed generation with electric vehicle integration in static load models through a hybrid optimization of bacterial foraging optimization (BFOA) and particle swarm optimization (PSO) techniques for 16-bus and 75-bus systems; and the second investigates the comparative performance of two hybrid optimization techniques for reducing real power loss. The results indicate that the BFOA–PSO approach is more efficient than the genetic algorithm–Monte Carlo simulation (GA–MCS) technique. Furthermore, a comparative analysis between ZIP load models, realistic load models, and composite load models for distributed generation with electric vehicle planning in the 75-bus system under charging mode using the GA–MCS method has been carried out. Additionally, convergence comparison between BFOA–PSO and GA–MCS for real power loss minimization in the IEEE 33-bus distribution system has been analyzed. This paper also discusses the current market scenario, challenges, and future prospects in the coordinated operation of distributed generation and electric vehicles in modern power systems.</p>