A multi-agent system based distributed EMS (energy management system) is proposed in this paper to perform optimal energy allocation and management for grids comprising of renewables, storage and distributed generation. The reliable and efficient operation of smart grids is slackened due to the presence of intermittent renewables. As the load demand and renewables are uncertain throughout the day, an energy management system is essential to ensure grid stability and achieve reductions in operation costs and CO2 emissions. The main objectives of the proposed algorithm is to maintain power balance in the system and to ensure long cycle life for storage units by controlling their SOC (state of charge). The proposed EMS scheme is tested and validated on a practical test system, which replicates a small-scale smart grid with a variety of distributed sources, storage devices, loads, power electronic converters, and SCADA (supervisory control and data acquisition) system. This system is also connected to the utility grid and the power exchange is controlled with the help of a battery system through a fuzzy based decision making framework. The proposed algorithm is also extensively verified and tested using a series of sensitivity analyses and benchmarking with existing algorithms. (C) 2016 Elsevier Ltd. All rights reserved.