SparkCity: a realistic model for growth of electric transport Urban planning with real data

'This model is bottom-up and more realistic'

SparkCity is not a real city, but it is a realistic one. It forms the basis of a model that allows you to choose what developments can be expected for electric transport given certain parameters. This will enable authorities, grid operators and market parties to acquire a reliable picture of what they will need to fine-tune their policy and strategy to.

Look, there’s the family number 94: two working adults with one child in daycare. Mum has a job outside of the city. The family has noticed that the price of an electric car has fallen over the past couple of years and that you can now drive 400 km on a single charge. They head to the dealer to trade in their petrol car.

There are another couple of thousand households like family number 94, each with their own composition, needs and considerations. Together they form SparkCity – an imaginary city full of realistic households. It forms the basis of a model that Auke Hoekstra from Eindhoven University of Technology has been working on for two years. This model enables governments, businesses and other parties to look at the effect on people’s behaviour based on numerous parameters. A variety of factors is considered, such as income, energy price, presence of charging facilities, and so on. Thus enabling them to estimate what kind of charging infrastructure for electric vehicles is required in a neighbourhood or what the effect of electric charging will be on the grid.

Own calculations

It is a unique model: agent-based. In contrast to a mathematical model, which will endeavour to calculate a general optimum using the general data input, SparkCity comprises thousands of objects each performing their own calculations on the basis of their individual parameters. They weigh things up and make decisions almost like real people. ‘The advantage of this model is that it is less abstract than mathematical models. We work with recognisable objects: families, cars, charging stations, substation, et cetera’, says Hoekstra. ‘An agent-based model is bottom-up and more realistic. We work with real families. You can zoom in on a “family”, an object, enabling you to examine whether a follow-up step is logical. All follow-up steps collectively determine what is done overall.’ He continues: ‘Such models used to be far too laborious. However, today's fast computers will take care of all the calculation for you, meaning that reality can be approximated much more closely’.

Auke Hoekstra: 'We can expand this basic model.'

Logical route

‘Rather than calculating towards a desired point, an agent-based model entails looking at what the logical route is according to a number of steps which follow from a series of assumptions. It’s im-portant to realise that a system will not achieve a state of equilibrium of its own accord. Sometimes interests or practical problems will have an effect and having an understanding of these is very useful. If family number 94 does end up deciding to buy the electric car in the event of a given fall in price, and there are more families like number 94, then as a local authority, energy supplier or charging station operator you’ll need to capitalise on this to perpetuate the trend.’

It took Hoekstra two years to build this model. Due to the fact that the principle is still a new one, it was often a case of pioneering work, and the whole thing was created through a process of trial and error. Hoekstra: ‘The model is far from being finished. We’ve got a solid foundation now, but we’re keen to develop this further in harmony with experts. For example, we’d like to factor in driverless cars, electric buses and electric HGVs’.

In the future Hoekstra dreams of, he will not be the only one working on the model. In due course, parties will be able to add their data to the open-source model in order to explore possible future scenarios for themselves. There are even plans afoot to expand the model globally: SparkCity is to be presented in India in January.

Check here for more information about SparkCity.

Community of Arnhem |

From SparkCity to SparkArnhem

The municipality of Arnhem is already at the stage of proceeding with SparkCity for the entire city. The Council would like to know for each district how many electric vehicles there will be in a decade’s time. The entire city needs to be captured in the model, as the municipal authority wants customised solutions and is keen to minimise the number of charging stations per district, says management consultant Peter Swart.

Peter Swart: 'Breaking things down by district is hugely important.'

'We already want to be thinking about solutions for the long term. Ultimately we’ll grow towards a tipping point at which we’ll be installing charging facilities without requests being submitted. As things stand at present, we’re only acting on demand, but that will be too late in the future – particularly if the market’s growth starts accelerating. That’s not what we want. Neither do we want to have to be reserving parking spaces for electric vehicles any more.

SparkCity can help us in this regard. We’d like to have a map of the city that shows future expectations for each district. This will enable us to adapt our plans and decide where to place charging facilities. We ourselves don’t need to understand how the model works.

Breaking things down by district is hugely important. Each neighbourhood is different. The solution needs to fit the environment and that requires creativity. We’re considering charging stations in things such as lamp posts, the poles for the trolleybus network, benches and compactors’.

ElaadNL |

Charting local differences

Charting the local differences will give ElaadNL, the grid operators’ knowledge and innovation centre, plenty of new information to go on, according to Manager Innovation Arjan Wargers.

Arjan Wargers: 'We’d like to factor in more realistic wind and solar data to the model.'

‘The impact of electric vehicles on the grid could vary from place to place. The model will enable us to form a picture of this variation for all those different locations and in different scenarios and show us where bottlenecks could arise, as well as the effect of measures such as Smart Charging. If smart technologies allow cars to primarily charge on the grid at off-peak times, then we’ll be able to prevent the need for extra cables or even a transformer station to be installed.

We’ve also got a fair few other wishes with regard to the model. For example, we’d like to factor in more realistic wind and solar data so as to chart the effect of charging if there is a lot of electricity coming from solar or wind. And at present the grids included don’t yet correspond to the actual situation. Finally, we’d also like to look at power quality. What that means is not just having to ensure that fuses aren’t blown but also that you’ve got the right voltage in the home, otherwise your appli-ances might suddenly no longer work properly if your electric car is charging. SparkCity will have to calculate how significant the probability of this is and how we can avoid it’.


Opportunities for the practical situation

The Netherlands Knowledge Platform for Public Charging Infrastructure (NKL) has contributed to making SparkCity practically viable. Programma Coordinator Roland Ferwerda suggests the model presents opportunities for authorities, grid operators and businesses, enabling them to have the most varied array of scenarios calculated for electric transport.

Roland Ferwerda: 'SparkCity generates more reliable insights.'

‘This model finally makes it possible for us to capture the complex world of electric driving – buying, driving and charging – in a realistic model. It generates more reliable insights, as to date many predictions from the past on such things as the growth of electric transport have ultimately turned out to be incorrect. Furthermore, the model will help increase the speed with which insights are generated. For example, whether CO2 targets are being met and whether electric transport will result in parking problems. It also enables simulations to be run which will calculate the impact of different forms of subsidisation. The model focuses primarily on describing complex scenarios and continuous improvement will be imperative. At the end of the day, it will need to be possible to enter as many parameters and as much practical data as required to enable us to reliably calculate all complex interactions between the objects involved.

Anticipating future developments is important but difficult. Particularly when it comes to a so-called disruptive development like the electric car. That is why NKL contributed to making the SparkCity model developed by Eindhoven University of Technology and sponsored by ElaadNL practically viable. Collective use of this simulation model - on the part of the market, authorities and grid operators - will help to expedite the rollout of the requisite public charging infrastructure for electric transport in the Netherlands'.

Alliander |

From electric vehicle to heat pump

Interaction within districts is an exceedingly complex scenario. This prompted Alliander to want to use SparkCity, says Consultant Gijs van der Poel.

Gijs van der Poel: 'Those complexe situations are what interest me.'

‘The model is perfect for charting the interaction within different districts. There’s no other model capable of doing so. People intending to start driving electric vehicles will often go on to purchase solar panels and sometimes even a heat pump. An electric vehicle by itself is nothing exciting, but all those changes together will demand a great deal from our grids and necessitate investment. But that’s how it goes in practice. These situations, preferably as complex as possible, are what interest me’.

GreenFlux |

So how?

Not everyone has a clear sense yet of what they can achieve using SparkCity. Manager Innovation Lennart Verheijen from GreenFlux tells the benefits and questions.

Lennart Verheijen: 'I’m really curious about the ultimate predictive value of this model.'

‘SparkCity is an interesting initiative, for sure. Ascertaining the value of Smart Charging on the spot market will be extremely useful when it comes to making investment decisions in terms of the technologies that enable it. In other areas there’s still a gap between theory and practice. For instance, it’s great that the model charts the value of Smart Charging, but the business community will only be able to set to work with it once it’s been translated into financial incentives. At present, those incentives aren’t allowed by law. SparkCity is an ambitious, large-scale project which can play pioneering role to obtain these kind of insights. I’m really curious about what the ultimate predictive value of the model as a whole will be. We’ll definitely be keeping a close eye on things at GreenFlux’.

TU Eindhoven |

At the beginning

SparkCity is still at the beginning of countless possibilities. Professor Maarten Steinbuch from Eindhoven University of Technology sees ample opportunities.

Maarten Steinbuch: 'SparkCity will become increasingly interesting to a growing number of parties.'

‘The great thing about this open-source model is that it can be endlessly expanded and developed further. As it stands, a variety of research institutes have contributed already, and this will be much more common in the future. We need social researchers, for instance. Apart from new areas, Eindhoven University of Technology will be adding new scenarios itself. For example, we will be carrying out research into autonomous driving and fully electric trucks. And these are just a few examples. If we get things properly organised, then this model will become increasingly interesting to a growing number of parties. Just you watch!’

The SparkCity model has been made possible by: Eindhoven University of Technology, ElaadNL and NKL. Text: NKL Nederland (René Lamers and Claudie Bolster). Photos: ElaadNL (Kevin Hagens) and NKL Nederland (Sanneke Fisser).

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