Abstract

The output of distributed generation resources depends on the weather conditions. This causes a fluctuation in the production of these resources and reduces the power quality. One of the solutions to overcome this problem is the use of energy storage systems. The use of these systems improves the operation indices of the grid. Energy storage systems, especially batteries, with all their technical capabilities, are high-cost systems. Therefore, installing them at any location with any random and non-optimum size can lead to higher cost. In this research, introducing the steps to realize an optimal energy management process, a method by which it can be possible to determine the optimal location, power and energy capacity of storage systems in a grid based on hourly data of the grid over a year (Includes loads and variable output power of distributed generation) is presented. the energy storage system used in this article is a vanadium redox flow battery. It is shown that the effect of storage device on the operation indices depends more on the installation location than on the storage capacity. The symbiotic organisms search algorithm has been used to solve the optimization problem. In the optimization process, in addition to improving the voltage profile, reducing losses and increasing network reliability, storage costs (Including the cost of investing, operating and repair) are minimized. The results obtained with Symbiotic algorithm are compared with other conventional algorithms such as particle swarm (PSO) and genetic algorithms. Given that Symbiotic algorithm has no specific adjusting parameters, the convergence rate increases and a more appropriate answer is obtained.

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