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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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 |
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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 |