---
title: How digital solutions and data are driving energy transition within mobility
url: "https://www.systra.com/en/expert_insights/how-digital-solutions-and-data-are-driving-energy-transition-within-mobility/"
type: expert_insights
date_published: 2023-12-01
date_modified: 2024-04-04
schema:
  @type: WebPage
language: en-US
word_count: 2175
reading_time: 11 min
canonical: "https://www.systra.com/en/expert_insights/how-digital-solutions-and-data-are-driving-energy-transition-within-mobility/"
featured_image: "https://www.systra.com/wp-content/uploads/2023/11/gettyimages-472309057-scaled.jpg"
type-insight:
  - Energy transition
---

# How digital solutions and data are driving energy transition within mobility

![How digital solutions and data are driving energy transition within mobility](https://www.systra.com/wp-content/uploads/2023/11/gettyimages-472309057-scaled.jpg)

A vital element in the decarbonisation of mobility, energy transition can be a
long and swinding road for public transport operators. However, the path to net
zero carbon is neither straight nor easy, with multiple possibilities to
consider at each stage.
**This is why an expert and holistic vision is essential.**

**Digital solutions provide invaluable assistance in taking into consideration the various possible scenarios**
. These include advanced simulations that provide projections of system
evolutions, artificial intelligence (AI) trained to examine multiple iterations,
and digital twins that capture data from systems in operation to help model
future projects.

In our series of articles on energy transition, we first looked at how the
energy transition fits in with the other pieces of the decarbonisation jigsaw (
[**Driving energy transition: a systemic approach for mobility**)](https://www.systra.com/en/expert_insights/driving-energy-transition-a-systemic-approach-for-mobility/)
, then explained how public authorities can act as a catalyst for wider energy
transition in mobility (
[**Energy transition: public transport leads the way**)](https://www.systra.com/en/expert_insights/energy-transition-public-transport-leads-the-way/)
. This third article analyses how digital solutions contribute to energy
transition throughout the lifecycle of a transport network.

### Mobility and digital already go together

Advances in digital solutions and technology have already enabled big leaps
forward in the mobility sector. Building Information Modelling (BIM) allows
infrastructure to be modelled and ‘built’ virtually in 3D, reducing interface
problems and improving certainty of outputs. Mobility as a Service (MaaS) has
the ability to change behaviours and use of public and private transport while
smart grids in energy networks can optimise power distribution, enabling wider
use of renewable energy.

Digital solutions are already helping to plan and deliver energy transitions, as
the examples below demonstrate. However, a note of caution. As with any
software, inputs and assumptions must be robustly challenged to get valuable
outputs. And,
**since any transition brings with it a multitude of challenges – political, social and economic – these too must be understood and factored in by anyone designing a system**
.

### Planning to cut greenhouse gas (GHG) emissions and improve air quality using digital solutions

When thinking and reworking city centre transport strategies, local authorities
have many complex problems to solve. They must reduce congestion, improve air
quality and lower carbon emissions while maintaining accessibility for all and
allowing the city to flourish economically.

In the UK, where national legislation on air pollution is particularly
stringent, local authorities must get people to change their local travel
practices in city centres. Many of them are opting for Low Emission Zones
(LEZs), which prevent or discourage the circulation of highly polluting vehicles
in a designated area by banning non-compliant vehicles or by introducing a toll
at the entrance to the zone, which is obviously politically sensitive.

**How can digital solutions help local decision-makers wishing to introduce LEZs?**
Take advanced traffic modelling: it can help planning these zones and
optimisinge their use by testing different hypotheses and scenarios. These can
take into account the likely behaviour of road users, incentives for change,
issues of equity of access, and the adoption over time of new energy
technologies. Above all, however, they must be based on a thorough understanding
of the issues surrounding travel within a city. Human expertise and experience
will remain essential, even if, in the future, increase of computation
capabilities and data will improve model precision.

In Scotland, SYSTRA is working with three cities on the creation of their LEZ:
Glasgow, Dundee and Aberdeen.

### Case Study #1: improve air quality in Aberdeen, Scotland

In Aberdeen, the implementation of the LEZ has been integrated into a city
masterplan which aims to reduce non-essential traffic and improve the
liveability and the economy of the city.

![aberdeen_2-1](https://www.systra.com/wp-content/uploads/2023/11/aberdeen_2-1-1024x963.png)

**After having identified eight points within the city centre where the levels of nitrogen dioxide (NO^(_(2))) were exceeding legal limits**
, SYSTRA carried out an initial high-level assessment providing 40 options to
tackle the problem. These encompassed various boundary positions, which type of
vehicles should be restricted, issues of practicality and the impacts on those
living and visiting the city centre, as well as the most dangerous air pollution
levels. This initial phase identified that although emissions from cars impacted
overall air pollution within the city centre, it was emissions from buses that
were leading to dangerous levels at the eight locations identified.

From here, **SYSTRA engineers **narrowed the field to five possible scenarios
which, they then **modelled using an extensive traffic model** of both the city
centre and surrounding areas. One of the requirements was that all car parks
around the city centre should be accessible without entering the LEZ. The model,
which covers a zone of 5km by 4km, was created with
[**PARAMICS**](https://www.systra.com/digital/solutions/transport-planning/paramics/)
, **an in-house SYSTRA solution.**

SYSTRA used a multicriteria analysis to propose the best of the five options.
However, even for this best option, NO^(_(2)) emissions were still too high at
two points. To address this, SYSTRA proposed additional restrictions to
implement,
**resulting in an optimised best option with no NO^(_(2)) exceedance point left.**
The council’s aim is for the LEZ to be in operation from May 2024. SYSTRA is
assisting in its implementation.

### Integrating new energy technologies at the design phase using digital solutions

During the design of an electric bus network, one of the biggest challenges is
how to balance the charging strategy and infrastructure with the demands of the
various routes.

If we take the trolleybus as an example, new models combining on-board batteries
with charging from overhead lines (OHL) can provide a flexible approach,
suitable for cities where there is limited space within existing streetscapes,
challenging topographies, or where architectural constraints and distinct
cultural heritage features, in certain places, means that OHL are not always
desirable.

In designing the optimum system, multiple factors must be considered: which
sections should run on battery and which on OHL; the operation requirements of
the network; how best to use the power from regenerative braking; and how to
build in resilience, should parts of the charging infrastructure be compromised.

**A digital model can help analyse and test different operational and charging scenarios, with expert input on potential operation strategies and electrical technology.**
Specialist models – such as
**SYSTRA’s **[**TESS**](https://www.systra.com/en/markets/digital-solutions/tess/)
(
[**Energy transition: public transport leads the way**](https://www.systra.com/en/expert_insights/energy-transition-public-transport-leads-the-way/)
) which helps optimise charging infrastructure at depots – can also be deployed.
Future developments will see more direct flows of information, whether from
other software into the simulation model or directly from the field, for
instance with information captured on buses, that are already in operation, fed
directly into the model.

In France, laws to stimulate low carbon mobility (LTECV^(1) then LOM^(2)) are
driving transitions to electric bus fleets, particularly for urban areas with
over 250,000 inhabitants.

^(1) Energy transition law for green growth

^(2) Mobility policy law

### Case Study #2: Assist the design of trolleybus lines in the city of Lyon, France

In the Lyon metropolitan area, with its 1.4 million inhabitants, there are plans
to add six more trolleybus lines to its existing network of nine.

![](https://www.systra.com/wp-content/uploads/2023/11/gettyimages-bus-tcl-lyon-1024x683.jpg)

For three of the six additional lines, which are due to be in operation in 2025
and 2026, SYSTRA is deploying the RATP Marcadet solution to help map out which
parts of the line could be battery powered and which should use OHL. To do that
it must consider factors including existing equipment, urban density, political
will, technical feasibility and the ratio between battery and OHL sections.
Additional charging at terminals and at the depot must also be envisaged.

**One of the important questions for the city’s transport authority and the bus operator was whether the network would still operate, should one of the substations providing electricity shut down or should one OHL section not be accessible (traffic accident, demonstration…). Simulating such scenarios through the model, SYSTRA could ensure that the operation of the network was resilient.**

For a network as complex as that of the Lyon agglomeration, it is essential that
all the methods for supplying the model are developed in line with the local
context and data. WiIthout forgetting the contributions of SYSTRA experts, the
bus industry, and the client, all of whom have contributed to enriching the
MARCADET solution used.

### Data analysis of energy use with machine learning optimises operation

Although public transport systems consume less energy per head than private
modes such as cars or planes, they are still heavy users of energy.

Ongoing global events affecting the supply and price of energy have only
underlined our dependency on energy markets. This comes in addition to our
urgent need for transition to greener and more independent energy sources, to
limit climate change impacts.

Yet, the data we collect today from electric transport systems is still rather
limited, generally focused on monitoring for safety purposes, instead of
providing an accurate breakdown of electricity consumption and what affects it.
**Consumption is a complex affair affected by a whole raft of factors: weather, air conditioning and heating use, routes, traffic, passenger numbers, speed and operation plans.**

Because contracts to date have not generally required for this type of data to
be supplied to the operator or client once a system is in use, it is difficult
to come by. And the lack of such data can lead to overdesign of a network, or
under design for some extreme worst-case scenarios.

### Case Study #3: optimise the electric bus fleet and its need for charging power requirements in Laval, Canada

In order to encourage cities to decarbonise mobility, the Canadian government is
subsidising zero emission bus fleets.

![](https://www.systra.com/wp-content/uploads/2023/11/gettyimages-recharge-bus-electrique-1024x768.jpg)

Like many cities in Canada, Laval, which lies North of Montreal, is looking to
move fast from diesel fuel to electric power regarding its bus fleet. However,
with a host of different vehicles and technologies to choose from, operating
conditions that vary from region to region and scarce data, mean that making
informed decisions about future fleets is difficult.

**Working with AI and live data acquisition specialists, SYSTRA has developed its own in-house digital solution series: [HERON](https://www.systra.com/canada/solutions/digital-solutions/heron/) – [WILD TURKEY](https://www.systra.com/canada/solutions/digital-solutions/wild-turkey/) – [TESS](https://www.systra.com/en/markets/digital-solutions/tess/). HERON uses AI machine learning to process and analyse data so that it can identify trends and work out which parameters have the biggest impacts on energy consumption in order to predict future consumptions.**
In the case of Laval, the analysis was carried out based nine buses of a pilot
fleet.

Plugged to HERON predictive analysis, WILD TURKEY efficiently integrates
charging sessions in the bus daily activities where TESS is used to model the
required charging characteristics (time, power) at the depot depending on the
operation plan.

After 12 months of data acquisition from the nine buses, one of the most
striking findings was the huge difference (1-3 times) in energy consumption per
kilometre between the different bus routes and for a same route on different
periods.

That information will help inform the re-planning of routes so that energy use
is optimised, and time spent driving to and from the depot for charging is
minimised. Our inhouse digital solution series HERON – WILD TURKEY – TESS should
**optimise the number of buses required, reducing it by 2% on a fleet of 219 buses and reduce the peak depot power requirement by 17% from 10.4MW in the Laval use case scenario.**

In the future, digital solutions will be even more powerful as engineers and
data scientists make the algorithms for the AI better and faster. The input of
more and more data will also increase the accuracy of the AI and allow its
broader application in different scenarios.

### A quiet revolution

Digital solutions are already playing a core role in the planning, design and
operation of new energy systems and technologies, aiding the transition of
public transport networks to low carbon energy sources.

By providing the ability to run multiple scenarios, to break down energy
consumption data and to analyse the impacts of different parameters and
alternative future scenarios, they aid communication between engineers,
transport authorities and operators and significantly inform decision-making.

In the future, we will see more and more automation of the interfaces between
software on the one hand and the integration of various data sources on the
other, which will allow a wider use of AI as algorithms and machine learning
progress.

**At SYSTRA, we anticipate that better data flows from operations to planning and design will help to increase the efficiency and sustainability of tomorrow’s public transport systems. Nevertheless, the expertise required to define the technical and human (governance, behaviour) structuring assumptions will be all the more necessary to use and guide these tools properly.**