A Dual-Objective Substation Energy Consumption Optimization Problem in Subway Systems

Hongjie Liu, Tao Tang, Jidong Lv and Ming Chai
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Hongjie Liu: School of Electronics and Information Engineering, Beijing Jiaotong University, Beijing 100044, China
Tao Tang: School of Electronics and Information Engineering, Beijing Jiaotong University, Beijing 100044, China
Jidong Lv: School of Electronics and Information Engineering, Beijing Jiaotong University, Beijing 100044, China
Ming Chai: School of Electronics and Information Engineering, Beijing Jiaotong University, Beijing 100044, China

Energies, 2019, vol. 12, issue 10, 1-28

Abstract: Maximizing regenerative energy utilization is an important way to reduce substation energy consumption in subway systems. Timetable optimization and energy storage systems are two main ways to improve improve regenerative energy utilization, but they were studied separately in the past. To further improve energy conservation while maintaining a low cost, this paper presents a strategy to improve regenerative energy utilization by an integration of them, which determines the capacity of each Wayside Energy Storage System (WESS) and correspondingly optimizes the timetable at the same time. We first propose a dual-objective optimization problem to simultaneously minimize substation energy consumption and the total cost of WESS. Then, a mathematical model is formulated with the decision variables as the configuration of WESS and timetable. Afterwards, we design an ? -constraint method to transform the dual-objective optimization problem into several single-objective optimization problems, and accordingly design an improved artificial bee colony algorithm to solve them sequentially. Finally, numerical examples based on the actual data from a subway system in China are conducted to show the effectiveness of the proposed method. Experimental results indicate that substation energy consumption is effectively reduced by using WESS together with a correspondingly optimized timetable. Note that substation energy consumption becomes lower when the total size of WESS is larger, and timetable optimization further reduces it. A set of Pareto optimal solutions is obtained for the experimental subway line—based on which, decision makers can make a sensible trade-off between energy conservation and WESS investment accordingly to their preferences.

Keywords: regenerative energy; timetable optimization; energy storage system; ? -constraint method; improved artificial bee colony (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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