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Abstract:Energy storage systems (ESSs) are enabling technologies for well-established and new applications such as power peak shaving, electric vehicles, integration of renewable energies, etc. With the increasing penetration of wind power into electric power grids, energy storage devices will be required to dynamically match the intermittency of wind energy. Energy-storage devices charge during low power demands and discharge during high power demands, acting as catalysts to provide energy boost. Batteries are the primary energy-storage devices in ground vehicles. Increasing the all-electric range of vehicles by 15% almost doubles the incremental cost of the energy-storage system. Due to the variable characteristics of renewable generation, batteries used in renewable-power systems can undergo many irregular, partial charge/discharge cycles. In turn, this can also have a detrimental effect on battery lifetime. Energy storage system in wind power system is required to deal with the difference of power between generator side and load side.

In this paper a natural habitat inspired metaheuristic Bird Swarm Optimization algorithm is implemented with improvisations made for the development of solution for the optimal allocations and optimal size prediction problem of Dispersed generation/ Distributed Generator in a radial power system distribution system in consideration of the drawbacks in the previous algorithms both in the context of convergence time and the optimal sizing with respect to the cost analysis for operation of the system with different number of DG’s installed in such a way that the optimal locations and sizes of DG’s installed is finalised with highest priority to the economical operation along with the immediate priority given to the network losses along with voltage deviations. To avoid the draw backs in previous optimisation algorithm regarding accuracy and run time. Along with the Cognitive component Weighted factor Bird Swarm optimisation (CWFBSO) algorithm a new concept is introduced called DG Size tuner Such that cost effective economical installation is possible as by the size tuner it is possible to compare the losses and voltage profile within the mean difference of the optimal sizes of final allocation determined by the main algorithm i.e., CWFBSO. Obtained results using CWFBSO in determining optimal locations and sizes of DG’s is capable showing good performance with less run time and convergence time and by using size tuner the optimal size selected economically with respect to less voltage deviation and minimal losses.