Indonesian Journal of Energy
Vol 3 No 2 (2020): Indonesian Journal of Energy

Performance Enhancement of Solar Panels Using Adaptive Velocity-Particle Swarm Optimization (AVPSO) Algorithm for Charging Station as an Effort for Energy Security

Luthfansyah Mohammad (Institut Teknologi Sepuluh Nopember)
Muhammad K. Asy’ari (Institut Teknologi Sepuluh Nopember)
Mokhammad F. Izdiharrudin (Institut Teknologi Sepuluh Nopember)
Suyanto (Institut Teknologi Sepuluh Nopember)



Article Info

Publish Date
31 Aug 2020

Abstract

The growth of public awareness of the environment is directly proportional to the development of the use of electric cars. Electric cars operate by consuming electrical energy from battery storage, which must be recharged periodically at the charging station. Solar panels are one source of energy that is environmentally friendly and has the potential to be applied to charging stations. The use of solar panels causes the charging station to no longer depend on conventional electricity networks, which the majority of it still use fossil fuel power plants. Solar panels have a problem that is not optimal electrical power output so that it has the potential to affect the charging parameters of the battery charging station. Adaptive Velocity-Particle Swarm Optimization (AV-PSO) is an artificial intelligence type MPPT optimization algorithm that can solve the problem of solar panel power optimization. This study also uses the Coulomb Counting method as a battery capacity estimator. The results showed that the average sensor accuracy is more than 91% with a DC-DC SEPIC converter which has an efficiency of 69.54%. In general, the proposed charging station system has been proven capable to enhance the energy security by optimizing the output power of solar panels up to 22.30% more than using conventional systems.

Copyrights © 2020






Journal Info

Abbrev

IJE

Publisher

Subject

Energy

Description

The journal covers research with a strong focus on energy economics, energy analysis, energy modeling, and prediction, integrated energy systems, energy planning, and energy management. The journal also welcomes papers on related topics such as energy conservation, energy efficiency, energy ...