考虑追踪安全的地铁快慢车协同操纵节能优化

研究考虑追踪间隔要求和再生能利用的快慢车线路地铁列车协同操纵节能优化问题.首先，基于滚动优化思想将列车协同操纵全局优化问题分解为一系列的子问题，即每一列车进入下一区间前由中央控制器根据同一供电分区内其他列车的操纵方案和列车重量等实时运营信息，计算出站列车在下一区间的操纵方案.为延长牵引制动重叠时间、提高再生能利用，各列车尤其是快车允许途中二次牵引加速以配合其他列车进站制动.基于上述研究思路，本文以列车净能耗为目标构建了快慢车线路列车协同操纵节能优化模型，并设计了混合遗传算法进行求解.案例分析结果表明，与不考虑其他列车操纵的个体最优节能操纵方法相比，本文提出的协同操纵方法可节能3%以上，算法满足实时优化对计算效率的要求.

Cooperative Control of Express/Local Metro Trains for Energy Saving Considering the Safe Headway

This study explores the cooperative control of metro trains under the skip- stop pattern, taking into account the constraint on the minimal headway for safety and the utilization of regenerative energy for energy saving. The overall optimization of cooperative control on multiple trains is decomposed into a series of local optimizations based on the rolling optimization framework. The local optimization is triggered whenever a train departs from the station. For each local optimization, the central train control center devises the energy-efficient trajectory of the departing train in the next inter-station run, considering the real-time information including the weight of the departing train and trajectories of the other trains in their current inter-station runs in the same power system interval. To synchronize the motoring and braking trains for better utilization of regenerative energy, the motoring operation mode is allowed more than once in each inter- station run especially for the express trains skipping a series of stations. A cooperative control model for express/local trains is proposed to minimize the net energy consumption of skip-stop metro line, and a hybrid genetic algorithm is developed to solve the proposed model. Case studies show that the developed algorithm satisfies the requirement of real-time computing efficiency and the proposed cooperative control saves more than 3% of net energy consumption in comparison with the optimal control of a single train for energy saving.