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Energy storage systems are one of the recent technologies utilized in order to achieve the stability and reliability of the power system with the integration of renewable energy sources. Energy storage systems can enhance system performance by means of the proper energy management. First, this paper presents a probabilistic modeling strategy for wind power and system demand. The modeling strategy utilizes Monte Carlo simulations to accurately consider the intermittent nature of wind generation and demand. Second, a linear programming optimization approach is performed to maximize system arbitrage benefits through optimizing operation of energy storage systems. Finally, two novel algorithms for optimal allocation of renewable energy resources and energy storage elements are proposed. The proposed algorithms are dependent on Big Bang Big Crunch optimization method and integrating the results of the modeling strategy with the optimization problem. The presented algorithms aim to minimize the net present value of energy loss cost in distribution systems. The proposed modeling strategy and optimization algorithms are implemented in MATLAB environment and tested on IEEE 33 bus system. Several case studies are done and the subsequent discussions show the effectiveness of the proposed algorithms. [ABSTRACT FROM AUTHOR]