Agent-Based Computer Simulation Models of Sustainable Mobility Systems

07-12-2017

Insight into the energy and mobility transition by means of simulation models

Author: Peter Hogeveen

There is a lot of uncertainty about the impact of the energy mobility transition on our society, especially at local level. Will technologies such as electric mobility, autonomous transport, smart charging and sustainable energy upset or strengthen our current energy system? How could governments and network operators prepare for this? To answer these issues, complex systems from multiple fields have to be described. Systems where the interaction between social, technological and economic subsystems plays an important role.

Transition scenarios at neighborhood level

A multidisciplinary expert team (consisting of academics, network operators, car manufacturers and consultancy firms) has started to map scenarios of the transition at local level. These scenarios were subsequently put into a simulation model (SparkCity) that was developed by researchers from TU Eindhoven and Peter Hogeveen from EVConsult. The simulation enables us to quantify and visualize the impacts of transition scenarios at neighborhood level.

What does Sparkcity do?

  • A broad-based growth scenario for the adoption of electric passenger transport in the Netherlands: approximately 42% marketshare for EVs in 2025.
  • Quantification of the impact of autonomous transport: more kilometers and journeys, fewer cars and energy needed.
  • Insight into the net impact of electric vehicles and smart charging at residential area level: the use of smart charging can protect most low-voltage networks of overload with low impact for e-drivers.

EVConsult also developed an agent-based model that simulates electricity balance in a grid-isolated ‘Car as Power Plant & neighbourhood. Car as Power Plant is a concept that applies to a local renewable energy system where surpluses of energy are stored as hydrogen and where hydrogen vehicles provide mobility as well as power to the neighbourhood. The model included driving behaviour, household electricity demand patterns and renewable energy resources, all based on Dutch data and statistics. Frequencies of electricity shortages and required energy production of individual hydrogen vehicles were assessed in a wide variety of scenario’s. The used software was Netlogo.

EVConsult played a major role in the development team of a model of buying, charging and driving of electric vehicles in real neighborhoods. The software GAMA and QGIS are used to implement GIS data of Dutch cities with their corresponding characteristics in the agent-based simulation of EV developments. The multi-layer model included a variety of modules such as: buying of EVs, EV cost developments, mobility & charging behavior, and the electricity grid. The model was used to asses business cases of charging infrastructure, the value of smart-charging for DSOs, EV policies for cities, and dutch EV prospects.

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