自動運転EVフリート運用と充電ステーション配置の同時最適化
Joint Optimization of Autonomous Electric Vehicle Fleet Operations and Charging Station Siting
電力網と交通網をつなぐ充電インフラの配置と、自動運転EVフリートの経路・充電計画を線形計画法で同時に最適化し、サンフランシスコでのケーススタディでコスト効率の良い車両と充電ステーション配置を示した論文。
著者: Justin Luke, Mauro Salazar, Ram Rajagopal, Marco Pavone
分類: eess.SY, cs.MA, cs.RO, cs.SY
原文アブストラクト
Charging infrastructure is the coupling link between power and transportation networks, thus determining charging station siting is necessary for planning of power and transportation systems. While previous works have either optimized for charging station siting given historic travel behavior, or optimized fleet routing and charging given an assumed placement of the stations, this paper introduces a linear program that optimizes for station siting and macroscopic fleet operations in a joint fashion. Given an electricity retail rate and a set of travel demand requests, the optimization minimizes total cost for an autonomous EV fleet comprising of travel costs, station procurement costs, fleet procurement costs, and electricity costs, including demand charges. Specifically, the optimization returns the number of charging plugs for each charging rate (e.g., Level 2, DC fast charging) at each candidate location, as well as the optimal routing and charging of the fleet. From a case-study of an electric vehicle fleet operating in San Francisco, our results show that, albeit with range limitations, small EVs with low procurement costs and high energy efficiencies are the most cost-effective in terms of total ownership costs. Furthermore, the optimal siting of charging stations is more spatially distributed than the current siting of stations, consisting mainly of high-power Level 2 AC stations (16.8 kW) with a small share of DC fast charging stations and no standard 7.7kW Level 2 stations. Optimal siting reduces the total costs, empty vehicle travel, and peak charging load by up to 10%.
