TY - JOUR
T1 - Optimizing Locations of Energy Storage Devices and Speed Profiles for Sustainable Urban Rail Transit
AU - Allen, Leon
AU - Chien, Steven
N1 - Publisher Copyright:
© 2023 American Society of Civil Engineers.
PY - 2023/3/1
Y1 - 2023/3/1
N2 - Urban growth and the resulting highway congestion is driving up demand for rail transit. Rail, a significant component of transportation infrastructure, is critical to economic efficiency and is one of the least energy-intensive modes. However, the scale of operations results in high energy consumption, atmospheric pollution, and operating costs. Fortunately, some of the braking energy can be harvested and either used to power a simultaneously accelerating train or stored to power subsequent accelerations. The objective of this research was to optimize the number of locations of the energy storage devices and speed profiles. First, kinematic equations were applied to simulate energy consumption. Then, a genetic algorithm (GA) was developed to optimize the speed profiles that minimize the energy consumption with and without a wayside energy storage unit (WESS) for a rail transit line. Finally, a model was developed to optimize the WESS locations that maximized the net benefit. A case study was conducted to examine the model in a real-world setting and to demonstrate its effectiveness. The results indicate that about 980 MWh of electrical energy, or an additional 5%, could be saved by optimizing the WESS locations over only applying speed profile optimization. In addition to significant energy savings, environmental emissions could be mitigated using these methods.
AB - Urban growth and the resulting highway congestion is driving up demand for rail transit. Rail, a significant component of transportation infrastructure, is critical to economic efficiency and is one of the least energy-intensive modes. However, the scale of operations results in high energy consumption, atmospheric pollution, and operating costs. Fortunately, some of the braking energy can be harvested and either used to power a simultaneously accelerating train or stored to power subsequent accelerations. The objective of this research was to optimize the number of locations of the energy storage devices and speed profiles. First, kinematic equations were applied to simulate energy consumption. Then, a genetic algorithm (GA) was developed to optimize the speed profiles that minimize the energy consumption with and without a wayside energy storage unit (WESS) for a rail transit line. Finally, a model was developed to optimize the WESS locations that maximized the net benefit. A case study was conducted to examine the model in a real-world setting and to demonstrate its effectiveness. The results indicate that about 980 MWh of electrical energy, or an additional 5%, could be saved by optimizing the WESS locations over only applying speed profile optimization. In addition to significant energy savings, environmental emissions could be mitigated using these methods.
KW - Energy storage
KW - Infrastructure
KW - Rail
KW - Regenerative braking
KW - Simulation
KW - Speed profile
UR - http://www.scopus.com/inward/record.url?scp=85146095365&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85146095365&partnerID=8YFLogxK
U2 - 10.1061/JITSE4.ISENG-2164
DO - 10.1061/JITSE4.ISENG-2164
M3 - Article
AN - SCOPUS:85146095365
SN - 1076-0342
VL - 29
JO - Journal of Infrastructure Systems
JF - Journal of Infrastructure Systems
IS - 1
M1 - 04023003
ER -