The demand for various sources of energy is unpredictably escalating in an astonishing rate. Conventional energy sources have started declining at a tremendous rate due to this increased demand. Environmentalists have started worrying about the future and have initiated many steps in order to fulfill present demands and also make sure that we do not compromise with the upcoming generations. Solar energy, one of the clean form energies found till date, is still a researchable topic among all scholars. Photovoltaic arrays use MPPT techniques in order to achieve high power even at undesirable environmental conditions. This helps the arrays to operate in the MPP region more often. This paper presents a case study of application of dragonfly algorithm, a recently developed swarm intelligence algorithm, inspired by the static and dynamic swarming behaviors of dragonflies, to maximum power point tracking (MPPT), to improve the efficiency of solar photovoltaic (PV) systems. The search for more techniques to tap solar energy has been a thirst among various researchers around the world. A conventional MPPT algorithm, incremental conductance method, was utilized for comparison with dragonfly algorithm in this paper. The results were evaluated and compared under different testing conditions, such as partial shading conditions. It was observed that dragonfly algorithm outperforms incremental conductance method and improves system efficiency. The dragonfly algorithm also seems to have an upper hand over other conventional methods as well. © 2021, Springer Nature Singapore Pte Ltd.