Measuring the value of energy storage systems in a power network
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The increased use of renewable generators and their intermittent behavior motivates network operators to deploy energy storage systems. In this study, energy storage types, locations, and capacities are optimized for a capacitated electric power network with renewable generation. Short term operational decisions that include charging/discharging schedules and capacity management of the storage systems are included in this optimization framework to capture hourly, daily, and seasonal fluctuations of the demand, renewable generation, and energy prices. A Mixed Integer Linear Programming (MILP) formulation is developed but because of the computational complexity, a mathematical programming based metaheuristic algorithm is proposed. With a numerical study, the proposed heuristic method is proved to be highly effective compared to the MILP formulation and an existing state of the art algorithm. The effects of storage installation costs, line capacities, demand and generation variance on the values of storage systems and on the installation decisions are analyzed through numerical studies.