Simulating individual charging behaviour in MATSim

Sebastian Hörl

13 June 2025

MATSim User Meeting 2025

  • Electric vehicles become more and more prevalent
  • Various studies on infrastructure placement exist
     
  • But behavior plays a crucial role
    • Charging at home, at work, using public chargers?
    • Only last component is covered in most studies
       
  • Goal: Let agents intelligently choose chargers in MATSim so that they optimize their daily score, like in a standard simulation
     
  • Additional features: fallback behavior if a station is taken, ...

Introduction

  • Electric vehicles (ev) contrib simulates decharging and charging of vehicles, provides the data and code infrastructure for charging stations, ...
     
  • EV charging in DRT
    • Send vehicle to charging stations when idle
    • Decide when to stop charging
       
  • UrbanEv package by TU Berlin
    • Insert charging activities based on plan structure
    • Charging inserted along the way
    • Based on SoC thresholds
       
  • Last package is used by for optimizing charging service provision (Montreal)

Existing work

Concept

  • Each standard plan of MATSim obtains a new attribute that is a container for charging plans
     
  • Always one charging plan is selected while the others are there for memory
     
  • A charging plan indicates when an agent wants to charge during the day. The relevant information is saved in a ChargingActivity
     
    • During an activity (start activity index, end activity index, charger)
       
    • Along a leg (leg index, start/end time, charger)

Concept

  • While running the simulation, we obtain charging plan score:
    • Large penalty for reaching SoC = 0
    • Penalty for falling below a configurable SoC
    • Penalty for performing a detour to get to a charger
    • ...
       
  • A new replanning strategy for startegic charging is introduced:
    • In X% of the cases, a new charging plan is proposed
    • In (1 - X)%, an existing charging plan is selected from the charging plan memory, according to the charging score
       
  • Fully integrated with other replanning strategies: A plan that is duplicated for mode choice / time mutation / ... keeps its attributes and thus the charging plan memory

Components

Two new major components:


Within-day electric vehicle charging (WEVC)

  • Computational infrastructure for implementing charging activities during a day
  • Provides interfaces that return a list of planned charging activities at the beginning of the day and implements them at time step 0
  • Provides interfaces for online decision-making if desired

 

Strategic electric vehicle charging (SEVC)

  • A standard implementation of the interfaces of WEVC
  • Reads the planned charging activities from the plan attribute and lets WEVC implement them
  • Provides standard routines for online decision-making
  • Provides comprehensive scoring with charger types, tariffs, subscriptions, ...

Within-day electric vehicle charging

  • Handles the insertion of new plug and unplug activities:
    • Useful for analysis
    • Act as triggers in the modeling chain ("when a plug activity starts, do this ...")
       
  • Charging slots describe when the respective activities should be inserted (around a chain of activities, or along a leg)

Within-day electric vehicle charging

  • Handles the insertion of new plug and unplug activities:
    • Useful for analysis
    • Act as triggers in the modeling chain ("when a plug activity starts, do this ...")
       
  • Charging slots describe when the respective activities should be inserted (around a chain of activities, or along a leg)
     
  • Charging alternatives describe what the agent does when a planned charger is not available anymore

Within-day electric vehicle charging

Within-day electric vehicle charging

En-route alternatives

  • When an agent goes on a leg that leads to a planned plug activity, we can call the alternative provides
     
  • Allows the agent to check whether the plug is currently taken; allows us to implement short-term reservation systems
     

Proactive charging

  • Send an agent to a charger at any time while a leg is ongoing
  • Allows to implement spontaneous charging decisions
  • With computational impact!

Strategic electric vehicle charging

  • Streamlined interfaces that are implementing the WEVC functionality
     
  • Replanning strategy for MATSim

Selection

Innovation

  • Choose among the existing charging plans based on the charging score
  • Find all possible activity-based charging slots
  • Find all possible leg-based charging slots
  • Randomly activate/deactivate each activity-based slot
  • Remove all incompatible leg-based slots
  • Randomly activate/deactivate each leg-based slot
  • Randomly select a charger for each retained slot

LH

LH

Charging infrastructure

  • Define different classes of chargers that ease the charger innovation process
     

Person-based chargers (e.g. household chargers)

  • Added to the choice set by person identifier
  • Per-charger attribute sevc:facilities (comma-separated)
     

Facility-based chargers (e.g. workplace chargers)

  • Added to the choice set by the facility identifier of the first activity along a charging slot
  • Per-charger attribute sevc:persons (comma-separated)
     

Public chargers

  • Searched within a radius of (configurable) meters
  • Per-charger attribute sevc:public = true

Charging infrastructure

Subscriptions

  • Person attribute sevc:subscriptions contains the subscriptions that an agent possesses
  • Charger attributes sevc:subscriptions indicates which subscriptions are necessary to use a charger
  • Only chargers without subscriptions or compatible ones are selected

 

Charging scoring

  • Various dimensions that are already included

Charging tariffs

  • Different configurable cost structures
     

Global for all chargers



 

 

Individually per charger

  • Using charger attributes
     

Tariff-based

  • All tariffs are configured by name in configuration
  • Chargers can have sevc:tariffs charger attribute
  • Tariffs can be accessible conditional on the possession of subscriptions
  • Agents choose the cheapest tariff that is available to them

Usage

  • Activate the relevant modules in the run script



     
  • Otherwise, everything encoded in
    • Configuration
    • Population (subscriptions, desired SoCs, ...)
      • Activate functionality by setting wevc:active = true !!!
    • Chargers (types, ...)
       
  • Considerable work of setting everything up coherently and in a realistic way.
  • Plan is to provide a bootstrap script that sets up a basic configuration from scratch.
     
  • Next step: set up a fully parameterized realistic scenario!

Usage

 

 

 

 

 

 

Full MATSim loop

  • Use SEVC together with other replanning strategies
  • ChargingSlot activation works such that a slot is only implemented if it is still compatible with the current standard plan configuration

Standalone charging simulation

  • Disable all other replanning strategies
  • Agents will try to find the optimal charging plan for a fixed standard plan from a baseline simulation
  • Allows to adapt the infrastructure according to the driving needs of the population
  • Allows to explore the optimal charging decisions given current mobility patters

 

Output

  • Detailed trace for all
    • charging processes (from first attempt to finishing or giving up)
    • charging attempts










       
  • Detailed tracking of all scoring events
    • When, where, who, how much (cost, travel time, ...), and how much score

Example

  • Tests based on an existing simulation scenario

Example

  • Tests based on an existing simulation scenario

Example

  • Tests based on an existing simulation scenario

Example

  • Tests based on an existing simulation scenario

Questions?

https://slides.com/sebastianhorl/mum25-charging

sebastian.horl@irt-systemx.fr