The rate of integration of distributed generation (DG) using renewable sources is increasing in distribution networks because of their technical and economic advantages. However, mismatches in the timing of electricity demand and generation in distribution networks have restricted the penetration of non-dispatchable DGs such as photovoltaic (PV) plants. Such a problem associated with the integration of DGs in distribution networks could be eliminated using the proper application of battery energy storage systems. In this paper, optimal planning of battery-coupled distributed photovoltaic generators (BCDPGs) in distribution networks is presented. The optimal planning determines the size and location of BCDPGs and schedules the charging and discharging of the batteries, while minimizing the total energy losses subject to technical constraints. To estimate the output from PV modules, 15-year solar irradiance data is modeled using the beta probability density function. Mixed-integer optimization using a genetic algorithm is employed for solving the optimization problem. The numerical studies on a 33-node distribution network show the advantages of the proposed methodology. The results obtained through this study show the capability of the proposed method to optimally allocate BCDPGs to largely improve the quality of supply of power from non-dispatchable DGs in terms of reducing energy losses, improving bus voltages, and increasing penetration levels of renewable energy. The proposed approach can also be useful when applied to realistic networks for proper sizing and operations of battery-coupled photovoltaic plants. © 2017 Author(s).