Abstract Balancing electricity demand and sustainable energy generation like wind energy presents challenges for the smart grid. To address this problem, the optimization of a wind farm (WF) along with the battery energy storage (BES) on the supply side, along with the demand side management (DSM) on the consumer side, should be considered during its planning and operation stages. An optimization framework with two levels to simultaneously decide the layout and operation of the WF/BES is put forward in this paper. The first‐level model consists of determining the WF/BES capacities, the WF configuration, and the connection buses. It is tackled by the mixed‐discrete particle swarm optimization algorithm. The multi‐objective optimization problem (MOOP) model in the second level determines the operation schedule of the WF/BES and other generators taking the DSM into consideration. The MOOP model in the second level is transformed to a single‐objective optimization problem via the maximum fuzzy satisfaction method, and is then solved by the genetic algorithm. The proposed model and the strategy are verified by the Barrow offshore WF test case, which is integrated into the IEEE‐118 system. Simulation results indicate that the wind and load patterns, the DSM and the BES price are the three key factors influencing the WF/BES design optimization.