Abstract
This study deals with the optimization of battery energy storage system (BESS) data in terms of significant characteristics of life and efficiency, and their positive impacts on power system efficiency in the presence of wind power plants in a microgrid. To this end, a permanent magnet synchronous generator (PMSG) is used to convert the wind energy by connecting a three-phase dynamic load to the grid. The main novelty of the proposed method is designing a smart backup battery branch to improve the efficiency of the wind farm by maintaining the operating constraints even during the occurrence of harsh faults in the generation section. Additionally, for the first time, the characteristics of the BESS are optimized using nine evolutionary algorithms, including the genetic algorithm (GA), teaching–learning-based optimization (TLBO), particle swarm optimization (PSO), gravitational search algorithm (GSA), artificial bee colony (ABC), differential evolution (DE), grey wolf optimizer (GWO), moth–flame optimization algorithm (MFO), and sine cosine algorithm (SCA), and the results are compared with each other. The simulation results of a case study confirm the robustness of the proposed control strategy for the BESS.
Highlights
Nowadays, there is a positive correlation between increasing the world population and using electricity as a reliable and clean source of energy
As energy storage systems are used to adjust the deviations of the produced power, a methodology to control the imbalances occurring in the wind farm due to the variability of the wind power was proposed by Michiorri et al [17]
A battery energy storage system (BESS) model was proposed to be applied to a permanent magnet synchronous generator (PMSG) wind turbine in the grid-connected mode
Summary
There is a positive correlation between increasing the world population and using electricity as a reliable and clean source of energy. As energy storage systems are used to adjust the deviations of the produced power, a methodology to control the imbalances occurring in the wind farm due to the variability of the wind power was proposed by Michiorri et al [17] This method can suitably size the storage system to obtain an acceptable level of controllability. A two-step simulation was considered, including the effectiveness of the BESS, which was connected to the smart grid (SG) under fault conditions, and the active SG using LPC (loop power flow controller) was proposed by applying the PSO algorithm to optimize the relevant objectives. The literature review confirmed that there are few studies related to the optimization of the practical chrematistics of the BESS, especially the state of charge (SOC) and the operation time of the battery These two parameters are crucial for designing relevant storage systems. Comparing the results of the optimization process of the BESS with the results without the optimization procedure
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