Planning the Energy and Mobility Transition with Modelling on Demand



Planning the Energy and Mobility Transition with Modelling on Demand

Nominated for The Planning for Sustainable Land Use and Transport Award

Authors

Benno Bock, Innovation Centre of Mobility and Sociatal Change (InnoZ), Daniel Hosse, Innovation Centre of Mobility and Sociatal Change (InnoZ), Anna Breymaier, Innovation Centre of Mobility and Sociatal Change (InnoZ)

Description

Planning for the energy and mobility sectors has been conducted mainly individually. Charging facilities for electric vehicles have created a need for integrated planning methods. The authors aim to present the implementation of such a tool.

Abstract

The energy transition from fossil fuels to intelligently managed renewables has a German name: ‘die Energiewende’. The word is also being used internationally and has now been adopted to the mobility and transport sector. The similarly coined word ‘Verkehrswende’ – best translated to ‘mobility transition’ – relates to the changing mobility behaviour as well as evolving services. Similar to the energy transition the change is meant as a change towards a more sustainable system avoiding carbon emissions.
Traditionally the planning for both transitions have been segregated in separate steps – an understandable attempt to decrease the complexity of the topic. But the need for a stronger integrated planning approach is becoming more obvious. With an increased usage of electric vehicles a frequent planning request is an optimised spatial deployment of charging infrastructure. This usually involves a process not only estimating the demand for recharging but also the type of renewables locally installed and the typical level of network load on the local grid.
These kind of planning request might be just the beginning of a stronger integrated process in need of new and innovative methods. The development and deployment of such a tool is part of the current research project ‘ENavi’ which is funded as part of the ‘Copernicus Projects’ by the German Federal Ministry of Education and Research. The authors are in this context developing and testing a planning tool for the project addressing the efficiency of combined energy and mobility measures.
The concept and current programming include passively generated mobility and energy data, an agent-based transport modelling software (MATSim) as base of an automated modelling technology (‘transport modelling on demand’) and an interactive website for the adjustment of planning parameters as well as the visualisation of the modelling results.
Past and current research projects like ‘e-GAP intermodal’ and ‘3connect’ have shown that agent-based modelling can be used to derive key performance indicators of innovative mobility services. In other research, agent-based models have been used to estimate private energy consumption. The use of interactive web-applications as dashboards are increasingly popular for the mobility and energy sector. The described development also benefits from an increasing availability of mobility and energy data in form of open data or as proprietary data accessible through standardised APIs.
The authors are aiming to present a first proof of concept at the European Transport Conference 2017 by presenting a case study in Germany.

Publisher

Association for European Transport