In the Netherlands and some neighbouring European countries, the electric vehicle (EV) charging sector is receiving attention from market regulators. Concerns relating to competitive processes in this developing and rapidly growing sector are being raised. This paper identifies specific markets where regulation can help increase the level of competition for the development of affordable and accessible public charging infrastructure, both within the built environment (slow charging) as well as along highways (fast charging). Barriers to competition include exclusive concessions at the municipality level and long-term exclusive concessions at locations along highways.@en

In the Netherlands, a big move towards electrification has been underway for decades, while the share of renewable energy in the Dutch energy mix is increasing. Grid capacity issues and the intermittency inherent to renewables require intelligent solutions, one of which may be V2G. V2G allows for bi-directional flows of energy between an EV and a DC charging station. Focussing on consumer acceptance of V2G is vital to the technology's adoption. Previous research is scarce in this regard, especially considering the influence of trial experience on consumer acceptance. In this research, using qualitative methods including semi-structured interviews, this influence is described for EV drivers in the Netherlands. It is found that trial experience using V2G alleviates earlier worries regarding range anxiety and (desired) user-friendliness. Trial experience also revealed that EV drivers find controlling the state-of-charge a vital barrier for adoption, as this would take away most of their uncertainties. This research, being one of the only studies assessing trial experience of V2G at short term parking qualitatively, can function as a building block for other research, such as similar experiments in different geographical locations or with different case settings.

Most nations have agreed to limit the emission of greenhouse gases within the Paris Agreement. The agreement relies on the assumption that all participating nations have accurate means of estimating carbon emissions and offsets accurately. However, global carbon emission accounting methodologies lack accuracy in approach and required carbon intensity data of utility grid electricity. From this, a need for developing a standardized accurate carbon emissions assessment methodology arises. The aim of this research is to develop an accurate carbon offset assessment methodology and determine the effect of using marginal, hourly average and annual average emission factors. The methodology is applied to a solar carport system in the Netherlands, consisting of a 465 kWp solar PV system, a 345 kWh nickel metal hydride battery and 16 DC charge points for EVs, in order to quantify the emission offset potential of the respective system components. This research presents a comprehensive literature review of existing carbon accounting methodologies based on which a new accurate methodology to calculate carbon offsets is developed. This methodology uses marginal emission factors from observed power dispatch and computes offsets on an hourly timestep. Application of marginal emission factor results in a 30 % and 23 % increase in carbon offset compared to hourly average emission factors and annual average emission factors, respectively. The carbon offset attributed to the battery system is roughly 100 kg CO2eq annually in 2019 and 1.5 -1.7 tons CO2eq in 2030. Relative to the lifecycle emissions caused by the battery system of about 200 tons CO2eq, including the battery system is not beneficial in terms of mitigating carbon emissions in solar carport applications. 99.96 % of the total offset is attributed to the solar PV system and lifecycle emissions of the solar carport can be mitigated after operation of 1.5 years when excluding the battery. Including the battery, lifecycle emissions are mitigated after 2 years and 3 months. To conclude, the results show that using marginal emission factors results in significant impact on the assessment results and are conceptually more accurate. Hence, they should be applied for carbon offset studies. Additionally, the carbon offset potential of the PV system is high while the contribution of the battery is low and installation of battery systems at solar carports is, therefore, not recommended.

The shifts towards more use of electric vehicles and more use of renewable energy sources create the need for Vehicle-to-Grid (V2G) technology. To penetrate the market, the development of V2G business models is critical. However, there are no sustainable V2G business models determined yet. Therefore, this research focused on what the key components are for such business models focusing on the Netherlands. By applying a qualitative approach, this study analyzed the actor's environment, technological developments, and three cases. After that, semi-structured interviews were conducted interviewing eleven experts with regards to the development of sustainable V2G business models. The results showed that there are three themes (business environment, business model, sustainability), twenty-six categories, and 229 components. This research provided an overview of the key components in a business model framework categorized into three use cases: Public V2G charging, V2G for homeowners (Vehicle-to-Home), and V2G for office/building owners (Vehicle-to-Building). The results showed that the business environment is vital and that the Dutch market is at the moment not ready for V2G to be commercial because of institutional, technical, and standardization issues. However, there is also potential due to the increasing trend of EVs, increasing grid congestion, decreasing costs of V2G charging infrastructure, and other trends.

The need for sustainable practises in all walks of society are more pressing than ever, with the effects of climate change being felt worldwide. Furthermore, the increasing share of variable and decentralised power generators coupled with the growing electricity demands from electric vehicles (EVs) at irregular times is placing unprecedented stresses on national power grids. To this end, innovative solutions to these complex issues are required. Electric vehicle solar carports (EVSCs) are structures that provide shelter for cars parked under a canopy roof fitted with PV modules. Adjacent to these parking spaces are the EV chargers, powered with the solar generated electricity. The aim of this study was to develop an accurate model and simulate an off-grid EVSC system for long stay parking applications, more specifically for the case of Lelystad Airport.
The base case consisted of ‘dumb charging’ which simply split the generated current evenly amongst the actively charging EVs and curtailed any excess. The results of this found that across the year, 85% of EVs left with and adequate state of charge (SOC), defined as being greater than 75% of nominal battery capacity.
This was then compared to various other scenarios in a rigorous sensitivity analysis to better understand the influential design parameters and attain a better final SOC distribution. Additionally, an economic assessment was performed, in which the base case was compared to a conventional grid-dependent system as well as a grid-inclusive, PV + grid, system.
It was found that the off-grid EVSC system is a profitable investment, and that better system design can result in a better charging performance as well as provide resilience to detrimental scenarios.

The objective of this research is to understand what smart charging can bring business and society at large. In close collaboration with the largest fleet operator in the world and a commercial aggregator, the impact of smart charging on both cost reduction and carbon reduction was simulated for an electric vehicle (EV) fleet in 2018. The simulation is designed to quantify the cost reduction of EV smart charging in The Netherlands as realistic as possible. Besides cost reduction quantification, the objective is to create a better understanding of what variables influence smart charging cost reduction. This is done via a statistical analysis of the smart charging simulations output. Furthermore, this research also has the objective find the direct impact of smart charging on carbon intensity of the electricity used for personal transport.
In this research, an EV aggregators perspective is leading. The EV aggregators could utilizing available flexibility in an EV fleet to deliver flexibility services. The strategy chosen to simulate is based on day ahead market optimization and passive balancing on the imbalance market. The EV fleet is assumed to be an isolated portfolio handled by the balance responsible party (BRP). The average synthetic load profile over 2018 was €41,56 per MWh and this is used as benchmark to quantify the smart charging savings in the simulations.
Different smart charging simulation set-up scenarios are designed and executed. In all simulations a real-world charging data set with 300.000 historic charging sessions was used. For each session, a new smart charging profile is determined by the optimization algorithms. The session price and session carbon intensity is calculated for both the smart charging scenarios as the business-as-usual scenarios. To compare the results of the different smart charging set-up scenarios, the average session price of all session in that simulations is used. At the same time, the smart charging savings is calculated based on the defined benchmark. The findings within this thesis support the conclusion that the used smart charging algorithms work properly and could decrease the electricity purchase price in The Netherlands. Additionally we found that the carbon intensity of the charged electricity during the smart charging schedule decreases compared to a business as usual scenario. This is a direct result of a correlation between the carbon intensity in the grid and day ahead prices in The Netherlands. EV aggregators are able to add flexibility to the demand side of the electricity system by means of smart charging, if a strong price incentive is provided. If stakeholders across the mobility and the energy sector work together, a real-world commercial implementation based on the price incentives on day ahead market and imbalance market in The Netherlands is possible. In the statistical analysis, multiple regression models show a linear relation between three independent variables (the session duration, session volume and maximum power of the charge point) and two dependent variables (the average session purchase price and savings per session). The key insights from the models empowered three main recommendations to EV aggregators to optimize the smart charging savings in the future: 1) Encourage longer session length. 2) Encourage regular overnight charging sessions behaviour, independent from the charging needs. 3) Stimulate access to high charging power. The data showed compelling differences between the 20% BEVs and the 80% PHEVs and their results were separated accordingly in this research. In all simulation set-up scenarios are the PHEVs outperforming the BEVs in terms of a lower average session price and higher cost reduction. If the smart charging strategy is executed as proposed in this thesis, the EV aggregator is exposed to the day ahead market and imbalance settlements for its portfolio. The EV aggregator is able to decrease the electricity purchase price, while acting as BRP. The exposure to the markets brings significant risk. Collaboration with an electricity supplier or BRP could potentially increase the smart charging savings for the EV aggregator. Furthermore, other revenue streams to utilize flexibility could be investigated. If stacking different flexibility strategies is possible, it could increase the smart charging value in the future.

Smart charging offers the potential for electric vehicles to use renewable energy more efficiently, lowering costs and improving the stability of the electricity grid. Many computer models have been developed to simulate the behavior of smart charging. Yet these models often assume that future information is known perfectly, including when vehicles will begin charging and how much solar energy will be available at that time. In reality, this information is subject to uncertainty, meaning the performance of smart charging may be worse than predicted by these models. This report details the development of an improved model which considers future uncertainty in smart charging behavior. It is determined that uncertainty does decrease the effectiveness of smart charging, but with strategies that are able to robustly consider this uncertainty smart charging can still offer tremendous benefits over traditional uncoordinated charging.