Reduction on the traction energy and increasing of the reused regenerative energy are two main ways for saving energy in metro systems, which are related to the driving strategy as well as the train timetable. To mini...
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Reduction on the traction energy and increasing of the reused regenerative energy are two main ways for saving energy in metro systems, which are related to the driving strategy as well as the train timetable. To minimize the systematic energy, this paper proposes an integrated energy-efficient train operation method in which the driving strategy and the train timetable are jointly optimized. Firstly, the models of calculating the traction energy and the reuse of the regenerate energy are introduced with the constraints of the train operation. Then, the systematical optimization model is formulated by taking the net energy (i.e., the difference between the traction energy and the reused regenerate energy) as the objective function. Based on the Space-Time-Speed network methodology, the optimization model is transformed into a discrete decision problem. Next, two algorithms are used to solve the problem. The dynamicprogramming algorithm is used to obtain the global optimal solution, and the discrete differential dynamic programming algorithm is applied to get the approximate optimal solution to reduce the computing time. Finally, two numeral examples are conducted to illustrate the effectiveness of the proposed method on energy saving. The method can reduce the net energy consumption by up to 25.0% compared to the result without optimization and by up to 8.7% compared to the result by using the two-stage method.
Water resources are very important to support the socio-economic development and maintain environmental health, which is a typical issue in water resources management. In this study, we developed an optimal allocation...
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Water resources are very important to support the socio-economic development and maintain environmental health, which is a typical issue in water resources management. In this study, we developed an optimal allocation model for a large complex system of water resources by considering both water supply and river ecological benefits. The water supply benefit is defined as the minimum water deficit for different water users, while the ecological benefit involves making the reservoir release as close as possible to the natural streamflow. To solve this problem, the combination of decomposition-coordination (DC) and discrete differential dynamic programming (DDDP) methods were proposed. The proposed methods first decomposed a large system with multi-objective programming into subsystems, and the optimal solution of each subsystem was accomplished by the DDDP method to solve the system efficiently. Then the subsystems' solutions were coordinated to figure out the near global optimal solution. The proposed models were tested in the Lingui and Yongfu County, Guilin City in China. Results show that the optimal reservoir release is close to the natural flow regime and there is a slight water deficit ratio in both level years. The water supply objective is more sensitive to the system model compared with the ecological objective, and the result of water allocation is optimized when the reservoir release is as close as possible to the natural flow based on the minimum water deficit. The proposed system model could facilitate sustainable water use and provide technical support for water resources management in economic development.
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