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Ward Vleugels Q-Park Thesis Award 2016

The Erasmus University and Q-Park have organised the Ward Vleugels Q-Park Thesis Award: a competition for the best master's thesis from students at universities in the Netherlands and Flanders about parking in the broadest sense of the word.

This year, eight theses were submitted from four universities: Delft, Rotterdam and Hasselt. A jury of academics from various universities selected three finalists from all the entries based on the economics of the submissions:

  • Lessons learnt from policy implementation and how to move forward by Ines Eline Ferrier (Erasmus University Rotterdam).

  • Providing information to influence dynamic parking choice behaviour in urban areas by Barbara Jepma (Rotterdam School of Management).

  • Advancing sustainable transportation by charging EVs with PV power at the workplace - An optimal charging strategy by Dennis van der Meer (Delft University of Technology).

And the winner is…

Based on the originality of the topic and the depth of the analysis, a panel of parking experts from the industry has selected Barbara Jepma to be the winner. The cheques for the winner and the runners-up (Dennis van der Meer and Ines Eline Ferrier) were presented by Frank De Moor, CEO of Q-Park, at a meeting at the Erasmus University Rotterdam on Thursday 9 February 2017.

Summary of the theses;

Lessons learnt from policy implementation and how to move forward

This thesis evaluates the mobility management policy that was put in place by
the Erasmus University Rotterdam (EUR) in 2011. The goal of the policy was to see a
reduction in car commuters in order to become a more sustainable campus.

Several policies were put in place. This thesis gives special attention to the
introduction of parking charges since June 2013. The analysis is based on three
years of data, which is provided by the EUR by means of surveys in 2010, 2014 and 2016.

The introduction of parking fees shows a decrease in car commuting.
Furthermore, an estimation of the reduction in CO2 is made, which finds a total
daily reduction of 1137.8 kg CO2 in 2016 compared to 2010.

The results suggest that the EUR is well on its way to realize their aim in
reduction of employee commuting, and that future policy measures are likely to
be found in behavioural measures as opposed to parking measures. Overall, the
EUR has become a more sustainable campus since 2010.

Providing information to influence dynamic parking choice behaviour

The main goal of this master thesis is to define how information can be provided to support the optimisation of dynamic parking choice behaviour in urban areas. To influence the dynamic parking choice behaviour of drivers, the right content of information should be provided at the right moment in time.

  • It has been found that 85 percent of drivers in Leeuwarden notice information road signs while searching for an available parking location, however only 38 percent of drivers’ parking choice behaviour is influenced by this information.

  • Information road signs on the availability and location of parking facilities are the most common utilised information sources, followed by Internet and navigation systems.

  • 91 percent of drivers’ parking choice is influenced by the distance of a parking facility to the end destination and 59 percent is influenced by the costs of parking.

  • The moment of parking choice is dependent on the parking situation. With lower levels of experience, or higher impact of the parking choice, drivers tend to make their parking choice at an earlier point in time.

  • Two different types of drivers are distinguished based on their moment of
    parking choice.

    • The first type of driver that makes his parking choice before he enters the car, or while entering the city center, dependent on the parking situation or intention.

    • The second type of driver decides where to park while approaching his end destination independent of the parking situation or intention.

The basis of parking policies in Leeuwarden is in place, as sufficient parking
facilities are provided and differentiated pricing strategies are applied. To enhance
the utilisation of available parking facilities, information should be provided
specifically targeted at different types of drivers. Dynamic comparisons
of parking alternatives should be provided by means of information road sings,
to promote the benefits of specific parking locations. Information on tariff,
availability and walking distance to the city center must be provided.

Advancing sustainable transportation by charging EVs with PV power at the workplace - An optimal charging strategy

Arguably the most important challenge of our time is climate change. In The Netherlands in 2014, 30% and 21.5% of total CO2 emissions were emitted by the electricity producing and transportation sector, respectively. Electric vehicles (EVs) have therefore gained interest as they do not emit carbon dioxide whilst driving and therefore do not pollute, at least directly. Nevertheless, when EVs are charged with electricity produced by a fossil-fuel power plant there are indirect emissions. Additionally, high penetration of EVs will inevitably lead to increased stress on the grid and consequently capital expenditure.

A viable solution to mitigate both these disadvantages is by charging EVs at the workplace with locally produced PV power. The high level of coincidence between parking time and solar power paves way to charge EVs in a sustainable and cost-efficient manner.

The thesis work presents the design of an energy management system (EMS) capable of forecasting photovoltaic (PV) power production and optimizing power flows between PV system, grid and EVs at the workplace. The aim is to reduce energy demand on the grid by increasing PV self-consumption while minimizing charging costs and consequently increasing sustainability of the EV fleet. The developed EMS consists of two components:
an autoregressive integrated moving average (ARIMA) model to predict PV power production and a mixed integer linear programming (MILP) framework that optimally allocates power to minimize charging costs.

The EMS is designed such that it can be implemented in practice and moreover, is versatile, implying that it can be utilized for alternative purposes as well. Additionally, the predictive quality of the system enables it to anticipate and act accordingly, rather than solely react. In order to perform sensitivity analyses, case studies will be formulated in which the effectiveness of the system can be ascertained.

The results show that the developed EMS is able to reduce charging costs significantly, while simultaneously increasing PV self-consumption and reducing energy demand from the grid. Furthermore, during a case study analogous to one repeatedly considered in literature, i.e. dynamic grid tariff and dynamic feed-in tariff (FIT), the EMS reduces charging costs by 118.44% and 427.45% in case of one and two charging points, respectively.

Moreover, stress on the grid is alleviated through both load shifting and power injection during peak demand. In addition, the EMS proves that vehicle-to-grid (V2G) leads to optimality only in extraordinary cases. The optimization problemis modeled in GAMS, whereas the ARIMA process ismodeled inMatlab and subsequently, the EMS is simulated inMatlab.

The thesis award is a partnership between the Erasmus University Rotterdam and Q-Park. The Erasmus University is committed to high-calibre academic education, embedded in societal requirements. As trend-setting company in the field of parking solutions, Q-Park is committed to innovation and sustainability. Since its inception, this partnership generates innovative contributions from students and interesting insights for the parking industry.