Energy Optimization for Train Operation Based on an Improved Ant Colony Optimization Methodology

More and more lines are using the Communication Based Train Control (CBTC) systems in urban rail transit. Trains are operated by tracking a pre-determined target speed curve in the CBTC system, so one of the most effective ways of reducing energy consumption is to fully understand the optimum curves that should prevail under varying operating conditions. Additionally, target speed curves need to be calculated with optimum real-time performance in order to cope with changed interstation planning running time. Therefore, this paper proposes a fast and effective algorithm for optimization, based on a two-stage method to find the optimal curve using a max-min ant colony optimization system, using approximate calculations of a discrete combination optimization model. The first stage unequally discretizes the line based on static gradient and speed limit in low-density and it could conduct a comprehensive search for viable energy saving target speed curves. The second stage unequally discretizes the line based on first stage discretion results, it makes full use of first-stage optimization information as pheromone, quickly optimizing the results to satisfy real-time demands. The algorithm is improved through consideration of the experience of train drivers. Finally, the paper presents some examples based on the operation data of Beijing Changping Subway Line, which is using CBTC system. The simulation results show that the proposed approach presents good energy-efficient and real-time performance.

[1]  Lei Chen,et al.  Energy-efficient train control in urban rail transit systems , 2015 .

[2]  Haidong Liu,et al.  A Two-level Optimization Model and Algorithm for Energy-Efficient Urban Train Operation , 2011 .

[3]  Antonio Fernández-Cardador,et al.  Real time regulation of efficient driving of high speed trains based on a genetic algorithm and a fuzzy model of manual driving , 2014, Eng. Appl. Artif. Intell..

[4]  Xiao Ma,et al.  Optimization of Train Operation in Multiple Interstations with Multi-Population Genetic Algorithm , 2015 .

[5]  Chun-Liang Lin,et al.  Optimization of train-speed trajectory and control for mass rapid transit systems , 2011 .

[6]  Tad Gonsalves,et al.  Multi objective particle swarm optimization algorithm for the design of efficient ATO speed profiles in metro lines , 2014, Eng. Appl. Artif. Intell..

[7]  Zhang Xin.  An Algorithm for Energy-Efficient Train Operation Simulation With Fixed Running Time , 2004 .

[8]  Masafumi Miyatake,et al.  Optimization of Train Speed Profile for Minimum Energy Consumption , 2010 .

[9]  Dewang Chen,et al.  Intelligent Train Operation Algorithms for Subway by Expert System and Reinforcement Learning , 2014, IEEE Transactions on Intelligent Transportation Systems.

[10]  Wang Tie-cheng.  Study on Train Movement Simulation for Saving Energy , 2004 .

[11]  Clive Roberts,et al.  A Multiple Train Trajectory Optimization to Minimize Energy Consumption and Delay , 2015, IEEE Transactions on Intelligent Transportation Systems.

[12]  Hui Wang,et al.  Optimizing Power for Train Operation Based on ACO , 2016 .

[13]  Chun-Liang Lin,et al.  Block-Layout Design Using MAX–MIN Ant System for Saving Energy on Mass Rapid Transit Systems , 2009, IEEE Transactions on Intelligent Transportation Systems.

[14]  Thomas Stützle,et al.  Ant colony optimization: artificial ants as a computational intelligence technique , 2006 .

[15]  Phil Howlett,et al.  Optimal strategies for the control of a train , 1996, Autom..

[16]  Li Ke-ping.  Optimal Method of Train Saving Energy Operation , 2009 .

[17]  P. Howlett,et al.  A note on the calculation of optimal strategies for the minimization of fuel consumption in the control of trains , 1993, IEEE Trans. Autom. Control..

[18]  Phil Howlett,et al.  Energy-efficient train control , 1994 .

[19]  Baohua Mao,et al.  Train Energy-saving Scheme with Evaluation in Urban Mass Transit Systems , 2007 .

[20]  Paul Batty,et al.  A systems approach to reduce urban rail energy consumption , 2014 .

[21]  Xiang Li,et al.  A Subway Train Timetable Optimization Approach Based on Energy-Efficient Operation Strategy , 2012 .

[22]  Liu Hai.  Arithmetic and Application Technology of Train Energy-Economizing Movement , 2002 .

[23]  Phil G. Howlett,et al.  Local energy minimization in optimal train control , 2009, Autom..

[24]  Eugene Khmelnitsky,et al.  On an optimal control problem of train operation , 2000, IEEE Trans. Autom. Control..

[25]  Rongfang Rachel Liu,et al.  Energy-efficient operation of rail vehicles , 2003 .

[26]  Xiang Li,et al.  A Survey on Energy-Efficient Train Operation for Urban Rail Transit , 2016, IEEE Transactions on Intelligent Transportation Systems.

[27]  Xiang Li,et al.  Optimization of Multitrain Operations in a Subway System , 2014, IEEE Transactions on Intelligent Transportation Systems.

[28]  K. Ichikawa.  Application of Optimization Theory for Bounded State Variable Problems to the Operation of Train , 1968 .

[29]  Chun-Liang Lin,et al.  Optimisation of train energy-efficient operation for mass rapid transit systems , 2012 .

[30]  Tao Tang,et al.  Energy-Efficient Train Tracking Operation Based on Multiple Optimization Models , 2016, IEEE Transactions on Intelligent Transportation Systems.