REGENERATIVE BRAKING ENERGY OPTIMIZATION ON ELECTRIC MULTIPLE UNITS ON THE JATINEGARA-BEKASI LINE WITH TIMETABLING BASED ON PARTICLE SWARM OPTIMIZATION AND GENETIC ALGORITHM

Energy consumption in rail transportation increases with fleet expansion and travel frequency. NZE2050 projections predict that more than 60% of motorized vehicles will switch to electric vehicles by 2030, with electric energy consumption accounting for nearly half of total energy consumption in...

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Main Author: Ridlo Istriantono, Duli
Format: Theses
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/83046
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:83046
spelling id-itb.:830462024-07-31T11:36:35ZREGENERATIVE BRAKING ENERGY OPTIMIZATION ON ELECTRIC MULTIPLE UNITS ON THE JATINEGARA-BEKASI LINE WITH TIMETABLING BASED ON PARTICLE SWARM OPTIMIZATION AND GENETIC ALGORITHM Ridlo Istriantono, Duli Indonesia Theses regenerative braking, electric multiple units, timetabling, optimization, energy efficiency. INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/83046 Energy consumption in rail transportation increases with fleet expansion and travel frequency. NZE2050 projections predict that more than 60% of motorized vehicles will switch to electric vehicles by 2030, with electric energy consumption accounting for nearly half of total energy consumption in 2050. The Jatinegara- Bekasi Electric Multiple Units (EMU) line, with its high travel frequency, has great potential to utilize regenerative braking energy, with traction energy consumption can reach 27 GWh per year. This research aims to optimize the utilization of regenerative braking energy on the Jatinegara-Bekasi EMU operational scheduling using Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) algorithms. An energy consumption model based on EMU operational timetabling is developed and validated by comparing the results of energy consumption calculations against actual data. Furthermore, this model is used to optimize energy consumption with PSO and GA algorithms. Optimization is done with several schemes, considering dwelling and headway times. By including on-peak and off-peak times as decision-making variables, the optimization results show an increase in energy efficiency of 8.49%. In cases with high travel frequency, the headway time variable proved to have great potential in improving energy efficiency. The optimization results also showed a cost efficiency of Rp 1,109,123,014 per year. This research provides important insights into regenerative energy utilization and sustainable transportation strategies for EMU operations in Indonesia. text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description Energy consumption in rail transportation increases with fleet expansion and travel frequency. NZE2050 projections predict that more than 60% of motorized vehicles will switch to electric vehicles by 2030, with electric energy consumption accounting for nearly half of total energy consumption in 2050. The Jatinegara- Bekasi Electric Multiple Units (EMU) line, with its high travel frequency, has great potential to utilize regenerative braking energy, with traction energy consumption can reach 27 GWh per year. This research aims to optimize the utilization of regenerative braking energy on the Jatinegara-Bekasi EMU operational scheduling using Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) algorithms. An energy consumption model based on EMU operational timetabling is developed and validated by comparing the results of energy consumption calculations against actual data. Furthermore, this model is used to optimize energy consumption with PSO and GA algorithms. Optimization is done with several schemes, considering dwelling and headway times. By including on-peak and off-peak times as decision-making variables, the optimization results show an increase in energy efficiency of 8.49%. In cases with high travel frequency, the headway time variable proved to have great potential in improving energy efficiency. The optimization results also showed a cost efficiency of Rp 1,109,123,014 per year. This research provides important insights into regenerative energy utilization and sustainable transportation strategies for EMU operations in Indonesia.
format Theses
author Ridlo Istriantono, Duli
spellingShingle Ridlo Istriantono, Duli
REGENERATIVE BRAKING ENERGY OPTIMIZATION ON ELECTRIC MULTIPLE UNITS ON THE JATINEGARA-BEKASI LINE WITH TIMETABLING BASED ON PARTICLE SWARM OPTIMIZATION AND GENETIC ALGORITHM
author_facet Ridlo Istriantono, Duli
author_sort Ridlo Istriantono, Duli
title REGENERATIVE BRAKING ENERGY OPTIMIZATION ON ELECTRIC MULTIPLE UNITS ON THE JATINEGARA-BEKASI LINE WITH TIMETABLING BASED ON PARTICLE SWARM OPTIMIZATION AND GENETIC ALGORITHM
title_short REGENERATIVE BRAKING ENERGY OPTIMIZATION ON ELECTRIC MULTIPLE UNITS ON THE JATINEGARA-BEKASI LINE WITH TIMETABLING BASED ON PARTICLE SWARM OPTIMIZATION AND GENETIC ALGORITHM
title_full REGENERATIVE BRAKING ENERGY OPTIMIZATION ON ELECTRIC MULTIPLE UNITS ON THE JATINEGARA-BEKASI LINE WITH TIMETABLING BASED ON PARTICLE SWARM OPTIMIZATION AND GENETIC ALGORITHM
title_fullStr REGENERATIVE BRAKING ENERGY OPTIMIZATION ON ELECTRIC MULTIPLE UNITS ON THE JATINEGARA-BEKASI LINE WITH TIMETABLING BASED ON PARTICLE SWARM OPTIMIZATION AND GENETIC ALGORITHM
title_full_unstemmed REGENERATIVE BRAKING ENERGY OPTIMIZATION ON ELECTRIC MULTIPLE UNITS ON THE JATINEGARA-BEKASI LINE WITH TIMETABLING BASED ON PARTICLE SWARM OPTIMIZATION AND GENETIC ALGORITHM
title_sort regenerative braking energy optimization on electric multiple units on the jatinegara-bekasi line with timetabling based on particle swarm optimization and genetic algorithm
url https://digilib.itb.ac.id/gdl/view/83046
_version_ 1822997933884178432