Optimising Electric Vehicle Charging Station Placement using Advanced Discrete Choice Models

TL;DR

This paper introduces a novel approach for optimally placing electric vehicle charging stations using advanced discrete choice models and simulation-based optimization, improving solution efficiency with heuristics and providing extensive computational validation.

Contribution

It develops a new bilevel and maximum covering optimization framework incorporating granular user preferences via discrete choice models, with heuristics for large instances.

Findings

Maximum covering model outperforms bilevel in computational efficiency.

Heuristics yield high-quality solutions faster than exact methods.

Extensive computational results validate the proposed approach.

Abstract

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