Impacts of Renewable Energy Sources by Battery Forecasting on Smart Power Systems

In this work the impacts of lead acid batteries by considering renewable sources (i.e., solar and wind energies) on power system is presented. First of all, we modeled the power system by lead-acid battery in stand-alone synthetic solar and wind production model and then the suggested forecasting model will be applied on wind and solar to estimate the available output power of each units. After that, the prediction subject will be calculated that is taken as constraint status based state of charge (SOC) of the batteries. The proposed solution includes of filtering the candidate inputs, synthetic prediction model based honey bee mating optimization (HBMO). By this method, the SOC of batteries will be in appropriate range and the on-or-off switching number of wind turbines and PV modules will be reduced. The suggested model is compared with methods to show the validity of suggested strategy.

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