Abstract
Maximizing regenerative energy utilization is an important way to reduce energy consumption in subway systems. Regenerative energy can be immediately utilized by traction trains, or be stored in energy storage systems and reused later. This paper adopts a combination of both methods, and proposes a dual-objective integrated optimization problem to simultaneously minimize the total net traction energy consumption and the investment of energy storage systems. Both timetable and configuration of energy storage systems are controlled in the optimization problem. A mathematical model of the dual-objective optimization problem is first formulated. Then to solve it, an c-constraint method is designed to transform the dual-objective optimization problem into several single-objective optimization problems, and an improved artificial bee colony algorithm is designed to solve them sequentially. Finally, numerical examples based on the actual data from a subway system in China are performed to show the effectiveness of the proposed method. Experimental results indicate that net traction energy consumption is effectively reduced by applying the proposed method, and it reduces to different degrees when using different size of energy storage systems, with an correspondingly optimized timetable. A set of Pareto optimal solutions is obtained for the experimental subway system, which is helpful for decision makers.
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