Summary This paper proposes a simultaneously allocating electric vehicle charging station (EVCS) and photovoltaic (PV) energy resources in smart grid considering uncertainties using a hybrid technique. The proposed hybrid technique is the combination of capuchin search algorithm (CapSA) and wild horse optimizer (WHO), and hence it is named as ECapSA technique. The dynamic behaviour of capuchin monkeys is enhanced by the wild horse's social life behaviour. That's why, it is called as enhanced CapSA (ECapSA) technique. In the proposed work, the following four main objectives are considered and formulated by the ECapSA technique: (a) minimization of energy loss, (b) minimization of 24‐h voltage deviation, (c) maximization of weightage to offer electric vehicle charging service for maximal users, and (d) minimization of land cost. The locations of electric vehicle charging station and distributed generation (DG) affect the power loss along voltage at the distribution network. Besides, the locations on the road network determine the land cost together with weightage. The proposed formulation solution is carried out in two layers: upper and lower layers. The electric vehicle charging station allocation is modelled in upper layer and distributed generation of the optimization in lower layer. Here, 24 h slots are considered for load variation and photovoltaic generation variation at the charging station (CS). The energy loss reduction is an objective of problem formulations instead of power loss reduction. The ECapSA technique is implemented in the MATLAB platform, its performance is analyzed with existing techniques.