Leveraging PSO algorithms to achieve optimal stand-alone microgrid performance with a focus on battery lifetime

Vicky Andria Kusuma, Aji Akbar Firdaus, Sena Sukmananda Suprapto, Dimas Fajar Uman Putra, Yuli Prasetyo, Firillia Filliana


This research endeavors to increase the lifespan of a battery utilized in a standalone microgrid system, a self-sufficient electrical system that consists of multiple generators that are not connected to the main power grid. This type of system is ideal for use in remote locations or areas where the grid connection is not possible. The sources of energy for this system include photovoltaic panels, wind turbines, diesel generators, and batteries. The state of charge (SOC) of the battery is used to determine the amount of energy stored in it. The particle swarm optimization (PSO) method is applied to minimize energy generation costs and maximize battery life. The results show that battery optimization can decrease energy generation costs from Rp 5,271,523.03 ($338.64 in USD) to Rp 13,064,979.20 ($839.30 in USD) while increasing the battery's lifespan by 0.42%, with losses of 7.22 kW and 433.29 kVAR, and also a life loss cost of Rp 5,499/$0.35.


battery management; cost-effectiveness; lifetime; optimization; PSO algorithm

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DOI: http://doi.org/10.11591/ijape.v12.i3.pp293-299


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International Journal of Applied Power Engineering (IJAPE)
p-ISSN 2252-8792, e-ISSN 2722-2624

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