Battery energy storage systems (ESS) are the proper technologies to reduce operational cost of electrical networks as well as smoothing wind uncertainty. However, some characteristics of the battery energy storage systems have not been accurately analyzed such as coordination of initial energy and depth of discharge (DOD) and determining their optimal levels. Moreover, the impacts of these parameters on the planning and operational costs have not been appropriately addressed. In order to address such shortcomings, current paper presents a unified stochastic planning on battery energy storage systems in electric power systems including wind power plants. The proposed planning considers following items as objective function and optimizes them: cost of energy in the network (i.e., generators fuel cost) and investment-operational costs and lifetime of battery energy storage systems. The design variable are also classified in three categories as (i) optimal generation scheduling (i.e., determining optimal generation pattern for all generators at each hour over the day), (ii) optimal energy storage planning (i.e., denoting capacity of batteries, nominal power of interfacing converters, and location of battery energy storage units), and (iii) optimal energy storage scheduling (i.e., determining optimal charging-discharging pattern, initial energy, depth-of-discharge, lifetime, and life-cycle for energy storage units). All of these items are carried out through stochastic modeling under wind power uncertainties. The paper presents a proper coordination between design variables such as initial energy and depth-of-discharge in order to minimize the network operational cost, maximizing lifetime of battery energy storage system, and smoothing wind uncertainty. The efficiency of the introduced methodology is demonstrated through various analyses and comparative studies.
