Conference Agenda

To model the mobility of people in a city, it is necessary to construct realistic schedules for in-

dividuals that consider the constraints that they have when planning their daily schedules. This

study introduces a dynamic programming framework to generate optimal schedules of daily activ-

ities in an activity-based model. We model the daily activity choices of individuals as a resource

constrained shortest path problem, where individuals try to maximize the combined utility of the

set of activities completed in a day. Activities belong to groups of mutually exclusive activities

(e.g., leisure, education, work, lunch) where at most one activity in the group is completed. Every

activity has a utility; however, the location of activities makes it expensive and time consuming to

travel from one activity to the next. Time windows for each activity and other realistic constraints

are considered. We apply dynamic programming to solve this problem and use decremental state

space relaxations (DSSR) to gradually eliminate infeasible cycles between mutually exclusive ac-

tivities. Our results show that it is feasible to find the optimal schedule quickly (i.e., in less than a

second per individual) showing the potential to apply our framework to populations with millions

of inhabitants.

The rapid expansion of the electric vehicle (EV) market necessitates growth in public charging infrastructure. Yet, this growth is hampered by significant uncertainties in planning and operational costs, primarily due to variable grid connection expenses. These costs, influenced by local distribution system operators (DSOs), are often unpredictable and costly to calculate. Such uncertainties pose considerable challenges for Charging Station Operators (CSOs) in their strategic decision-making. Our study introduces a novel Multi-period Mixed-integer Stochastic Programming (MPSP) framework to manage these uncertainties and identify economically viable sites for new charging stations.

The MPSP framework introduces an enhanced charging capacity estimation method integrating EV arrival frequencies, parking durations, and active charging sessions to provide insights into station utilization rates and aid optimal CS placement. MPSP addresses grid connection and peak load operation costs across three periods: normal, peak, and night. It integrates an advanced scenario generation algorithm to simulate grid connection scenarios and facilitate Sample Average Approximation. A case study in a German town using synthetic grid data is conducted to validate MPSP. This study involved 158 points of interest, 12 candidate CS planning locations, and 15 substations for grid connections. Findings reveal that planning with complete grid data could enhance profitability by up to 50% compared to planning under uncertain grid connections, emphasizing the need for robust partnerships between CSOs and DSOs.

Utilizing real location data and synthetic charging statistics, this study underscores the importance of comprehensive data integration and collaborative planning, paving the way for cost-effective and grid-compatible EV infrastructure development.

Electrifying road-based long-haul transportation is an intricate task. Given the current state of battery technology, either the driving ranges of electric commercial vehicles (ECVs) are too short or high-capacity batteries are costly and so heavy that payloads are limited. An old, yet recently revitalized, charging infrastructure currently evaluated on multiple test tracks around the globe alternatively suggests charging of electric trucks while driving. Analogously to trams, trolley buses, or trains, ECVs are powered by an electric motor connected to overhead wires via a movable contact arm and supported by a battery or an extra conventional drive, which steps in on non-electrified road segments. In this presentation, we will first examine the strategic question of minimizing the installation costs for electrified highway kilometers while still providing sufficient energy for a given set of representative tours of electric vehicles. Afterwards, the second part of the presentation is dedicated to the operational planning task of how to route a single ECV executing full-truckload point-to-point deliveries along a highway main line where charge-while-drive infrastructure is fixedly installed along some but not all parts of the road.