This paper proposes an approach for the optimal operation of electrified railways by balancing energy flows among energy exchange with the traditional electrical grid, energy consumption by accelerating trains, energy production from decelerating trains, energy from renewable energy resources (RERs) such as wind and solar photovoltaic (PV) energy systems, and energy storage systems. The objective function considered in this work is the minimization of total operating cost of electrified railway system consisting of cost of power generation from the external power system, cost of power obtained from RERs such as wind and solar PV sources, cost of power from storage systems such as battery storage and supercapacitors, and the income obtained by selling excess power back to the main electrical grid. This problem is formulated as an AC optimal power flow problem subjected to various equality and inequality constraints. In this work, the probability distribution functions (PDFs) are used to the uncertainties related to wind and solar PV powers. The proposed optimization problem is solved by using CONOPT solver of generalized algebraic modeling system (GAMS) software, which is a powerful and efficient optimization tool. The simulation results obtained with GAMS/CONOPT solver are also compared with meta-heuristic based differential evolution algorithm (DEA).

中文翻译：

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具有可再生能源和存储的电气化铁路的优化运行

本文提出了一种通过平衡与传统电网的能量交换、加速列车的能源消耗、减速列车的能源生产、风能和太阳能等可再生能源 (RER) 能源之间的能量流动来优化电气化铁路运营的方法。光伏 (PV) 能源系统和储能系统。在这项工作中考虑的目标函数是最小化电气化铁路系统的总运营成本，包括外部电力系统的发电成本、从风能和太阳能光伏电源等 RER 获得的电力成本、存储系统的电力成本例如电池存储和超级电容器，以及通过将多余的电力卖回主电网获得的收入。该问题被表述为受各种等式和不等式约束的交流最优潮流问题。在这项工作中，概率分布函数 (PDF) 用于与风能和太阳能光伏发电相关的不确定性。所提出的优化问题是通过使用广义代数建模系统 (GAMS) 软件的 CONOPT 求解器来解决的，这是一种强大而高效的优化工具。使用 GAMS/CONOPT 求解器获得的仿真结果也与基于元启发式的差分进化算法 (DEA) 进行了比较。所提出的优化问题是通过使用广义代数建模系统 (GAMS) 软件的 CONOPT 求解器来解决的，这是一种强大而高效的优化工具。使用 GAMS/CONOPT 求解器获得的仿真结果也与基于元启发式的差分进化算法 (DEA) 进行了比较。所提出的优化问题是通过使用广义代数建模系统 (GAMS) 软件的 CONOPT 求解器来解决的，这是一种强大而高效的优化工具。使用 GAMS/CONOPT 求解器获得的仿真结果也与基于元启发式的差分进化算法 (DEA) 进行了比较。