论文标题
使用先进的离散选择模型优化电动汽车充电站放置
Optimising Electric Vehicle Charging Station Placement using Advanced Discrete Choice Models
论文作者
论文摘要
我们提出了一种新模型，用于在多周期内找到电动汽车充电站的最佳位置，以最大程度地采用电动汽车。通过使用高级离散选择模型和用户类，这项工作允许对用户属性及其在充电站特性方面的偏好进行颗粒状建模。我们没有在公式中嵌入分析概率模型，而是为给定数量的方案采用模拟方法和预报错误项。但是，除了最简单的实例以外，这都会产生一个双重优化模型。使用预计的错误项来计算每个充电站覆盖的用户允许最大覆盖模型，为此，可以发现解决方案的效率比双层配方更有效。在某些情况下，最大覆盖配方仍然很棘手，因此我们提出滚动范围，贪婪和掌握启发式方法，以更有效地获得高质量的解决方案。提供了广泛的计算结果，以将最大覆盖率配方与当前的最新制度进行比较，包括精确的解决方案和启发式方法。 关键字：电动汽车充电站，设施位置，整数编程，离散选择型号，最大覆盖率
We present a new model for finding the optimal placement of electric vehicle charging stations across a multi-period time frame so as to maximise electric vehicle adoption. Via the use of advanced discrete choice models and user classes, this work allows for a granular modelling of user attributes and their preferences in regard to charging station characteristics. Instead of embedding an analytical probability model in the formulation, we adopt a simulation approach and pre-compute error terms for each option available to users for a given number of scenarios. This results in a bilevel optimisation model that is, however, intractable for all but the simplest instances. Using the pre-computed error terms to calculate the users covered by each charging station allows for a maximum covering model, for which solutions can be found more efficiently than for the bilevel formulation. The maximum covering formulation remains intractable in some instances, so we propose rolling horizon, greedy, and GRASP heuristics to obtain good quality solutions more efficiently. Extensive computational results are provided, which compare the maximum covering formulation with the current state-of-the-art, both for exact solutions and the heuristic methods. Keywords: Electric vehicle charging stations, facility location, integer programming, discrete choice models, maximum covering
