Abstract— The increasing prevalence of distributed generation, particularly photovoltaic (PV)-based sources, in electricity distribution networks underscores the need for comprehensive studies on their impact on network operation. This paper addresses the significance of leveraging PV inverters to provide both capacitive and inductive reactive power support, thereby reducing the necessity for additional investments. By incorporating PVs in this dual role, the distribution network gains enhanced flexibility in managing voltage profiles, reducing dependency on additional investments in infrastructure. This dual functionality addresses the dynamic needs of the grid, offering a sustainable solution to optimize the network’s overall performance while harnessing the inherent capabilities of PV technology. In this investigation, Python-based Particle Swarm Optimization (PSO) and Firefly algorithms (FA) have been applied to ascertain the optimal amount of reactive power support for enhancing the voltage profile of the network, and the effectiveness of the algorithms are compared. The algorithms take into account the reactive power limits inherent in PV plants within the distribution network, and optimize the reactive power support that should be taken from each PV that won’t result in any curtailment in PVs’ active power generation, i.e., only the remaining capacity of the inverter is allowed for the reactive power support, if needed. The network is modeled, analyzed, and simulated using the DIgSILENT PowerFactory program, with seamless integration between the network model and the optimization algorithm facilitated through Python. The obtained results demonstrate that reactive power support from PV plants yields positive effects on the overall voltage profile of the network.