The Scheduling Based Regenerative Braking Energy Optimization for Performance Efficiency of Tangerang-Duri Corridor Electric Rail Train with Genetic Algorithm Method
DOI:
https://doi.org/10.37367/jpi.v10i1.429Keywords:
Scheduling, Regenerative Braking, optimizationAbstract
The transportation paradigm shift towards electric vehicles is an important step in achieving carbon neutrality and limiting global temperature rise to below 1.5°C by 2050, as reported by the International Energy Agency (IEA) in 2021. Urban electric trains are one of the main solutions to reduce greenhouse gas emissions. KRL, which is known to be energy efficient, still has a large electricity consumption when accumulated in one year. One corridor that has received attention is the Tangerang-Duri corridor with annual traction energy consumption reaching 7,199,044 kWh or around Rp 3,477,138,224 per year. This study aims to optimize KRL operational scheduling in the Tangerang-Duri corridor to maximize the utilization of regenerative braking energy using the Genetic Algorithm (GA) optimization method. The results showed that the regenerative braking utilization modeling was successful with a relatively small difference of 2.88% compared to the actual data. The optimization results show that Scenario 2 is the best and most relevant Scenario for the current application with a reduction in traction energy of 6.25% or 1391.36 kWh/day or an increase in regenerative braking energy utilization to 14.89%.
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