动态电船充电问题

Camilo Vélez, Alejandro Montoya
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引用次数: 0

摘要

本文提出了一种新的优化问题——动态电动船充电问题(DEBCP)。该问题动态地确定了在光伏充电站(pvcs)中执行的电动船(EB)的速度和充电决策。研究方法以充电和电池退化成本最小为目标函数。考虑到EB的能量消耗和pvcs的太阳辐照度是不确定的,由于外部因素的操作,DEBCP的动态组件重新计算问题的解决方案,因为与这些变量相关的新信息是已知的。为了解决这一问题,我们提出了一种滚动视界遗传算法。该方法不断地重新评估操作的速度和收费决策。这些决定是由遗传算法做出的。我们的研究结果表明,重新计算既有助于在可能的情况下降低解决方案的成本,也有助于在需要时纠正操作。为了评估我们的解决方法,我们基于将在哥伦比亚实施的EB未来河流输送作业建立了一些测试实例。我们通过比较DBECP问题的结果与静态解决方案之后的场景来评估动态重新计算的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The dynamic electric boat charging problem
Paper aims This paper proposes a new optimization problem named the dynamic electric boat charging problem (DEBCP). Originality The problem dynamically determines the speed and charging decisions of an electric boat (EB) to be performed in photovoltaic charging stations (PVCSs). Research method The objective function is to minimize the charging plus the battery degradation costs. Considering that the energy consumption of the EB and the solar irradiance for the PVCSs are uncertain due to factors external to the operation, the dynamic component of the DEBCP recalculates the solution to the problem as new information related to these variables is known. To solve the problem, we propose a rolling horizon genetic algorithm. This method constantly reevaluates the speed and charging decisions of the operation. Such decisions are made with a genetic algorithm. Main findings Our results show that the recalculations help either reducing the cost of the solution when possible or correcting the operation when needed. Implications for theory and practice To evaluate our solution method, we built some test instances based on a future fluvial transport operation with an EB that will be implemented in Colombia. We assess the impact of the dynamic recalculations by comparing the results of the DBECP problem to a scenario following a static solution.
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