Abstract
| Original language | English |
|---|---|
| Pages (from-to) | 129-142 |
| Number of pages | 14 |
| Journal | Computers & Industrial Engineering |
| Volume | 127 |
| DOIs | |
| Publication status | Published - 1 Jan 2019 |
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Keywords
- Energy consumption
- Quadratic programming
- Stop-skipping pattern
- Timetable optimization
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Analysis of energy consumption reduction in metro systems using rollingstop-skipping patterns. / Yang, S.; Wu, Jianjun (Corresponding author); Yang, Xin ; Liao, F.; Li, Daqing ; Wei, Yun.
In: Computers & Industrial Engineering, Vol. 127, 01.01.2019, p. 129-142.Research output: Contribution to journal › Article › Academic › peer-review
TY - JOUR
T1 - Analysis of energy consumption reduction in metro systems using rollingstop-skipping patterns
AU - Yang, S.
AU - Wu, Jianjun
AU - Yang, Xin
AU - Liao, F.
AU - Li, Daqing
AU - Wei, Yun
PY - 2019/1/1
Y1 - 2019/1/1
N2 - Energy-efficient operations optimization has attracted much attention recently to reduce the energy consumption and the associated costs of metro systems. Compared with all-stop patterns, stop-skipping patterns potentially lead to decreasing energy consumption and increasing train loading utilization. This paper develops an optimization-based approach to design energy-efficient metro timetables and speed profiles with a stop-skipping pattern based on passenger smart-card data. First, we develop an algorithm to generate: a set of likely to be skipped stations is identified according to historical travel records, and a heuristic rule is adopted to select the specific skipped station. Second, we reformulate the energy-efficient timetabling optimization problem as a convex quadratic programming problem and develop a solution algorithm to determine the optimized timetables and speed profiles. A numerical example is conducted using the real-world passenger data and the train operational data of a metro line in Beijing. The results show that the developed approach reduces energy consumption by 15.39% and increases the loading volume per train by 3.56 person/min in comparison with the current timetable.
AB - Energy-efficient operations optimization has attracted much attention recently to reduce the energy consumption and the associated costs of metro systems. Compared with all-stop patterns, stop-skipping patterns potentially lead to decreasing energy consumption and increasing train loading utilization. This paper develops an optimization-based approach to design energy-efficient metro timetables and speed profiles with a stop-skipping pattern based on passenger smart-card data. First, we develop an algorithm to generate: a set of likely to be skipped stations is identified according to historical travel records, and a heuristic rule is adopted to select the specific skipped station. Second, we reformulate the energy-efficient timetabling optimization problem as a convex quadratic programming problem and develop a solution algorithm to determine the optimized timetables and speed profiles. A numerical example is conducted using the real-world passenger data and the train operational data of a metro line in Beijing. The results show that the developed approach reduces energy consumption by 15.39% and increases the loading volume per train by 3.56 person/min in comparison with the current timetable.
KW - Energy consumption
KW - Quadratic programming
KW - Stop-skipping pattern
KW - Timetable optimization
UR - http://www.scopus.com/inward/record.url?scp=85057577093&partnerID=8YFLogxK
U2 - 10.1016/j.cie.2018.11.048
DO - 10.1016/j.cie.2018.11.048
M3 - Article
VL - 127
SP - 129
EP - 142
JO - Computers & Industrial Engineering
JF - Computers & Industrial Engineering
SN - 0360-8352
ER -