This paper presents an innovative management strategy for distributed battery storages that greatly increases the capability of distribution networks to absorb and utilize photovoltaic (PV) generation. Optimal daily energy profiles for each storage unit are calculated using a Fourier series description based on one day ahead energy forecasts. Each battery charge/discharge profile is optimized to minimize a cost function that includes network and battery losses, battery cyclic costs and the network voltage profile. The optimization method combined an interior-point algorithm and pattern search algorithm. Simulations are carried out on a three-phase distribution system over a period of 24 hours at 15 minute interval with time varying loads. The adopted technique in this paper shows significant control abilities in peak shaving and load leveling. Results also indicate that proposed approach can enhance the performance of the grid by improving the voltage stability and reducing distribution losses thus providing the required security for consumers. Results also illustrate capacity and charging/discharging rates of batteries highly depend on the location of the controlled consumer battery and amount of controlled batteries.