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.

In a world where electricity demands are progressively growing along with the worsening climate crisis, it is essential to conduct research and build systems that can meet this demand in a sustainable, reliable and cost effective manner. The building sector accounts for nearly 40% of greenhouse gas emissions in the EU, this is primarily due to the dependence on fossil fuels to provide heat for spaces, heating water and for cooking. Countries have made ambitious goals to reduce these emissions, and one such way is electrification. By electrifying heating, some research suggests that all the Renewable Energy Sources (RES) planned to be deployed in the Netherlands will not be suffcient to meet the demand, even with storage technologies. There are multiple ways to address this problem, one of them is decentralising energy production such that each household or institution accounts for their own production and consumption of energy. While this is in theory a simple solution, in the higher latitudes becomes harder during the colder months to meet the increased electricity demand using only renewable sources. Thus, a combination of them must be used to combat the effects of seasonal RES production. Simultaneously, the wholesale electricity prices in the Netherlands are also projected to increase in the near future, to almost 57e/MWh. Universities being large load customers, will feel the effects of this increase in electricity prices and the need for heating electrification by 2030. This need could be due to policy implementations or personal choice. It is in the benefit of the university to increase their self-sufficiency, to decrease costs and carbon emissions. Thus, a microgrid is proposed for a university in the Netherlands. This microgrid, utilises on-site Photovoltaics (PV) generation, Fuel Cell Electric Vehicles (FCEVs) in the capacity of back up generation and a battery to store any excess energy generated by the PV system. In order to ensure the smooth integration of the components mentioned, an energy management system is designed. Furthermore, a new value proposition is made for the energy storage system where it is utilised during times of high electricity prices. For the energy management system two control strategies are proposed with different end goals; one based solely on increasing self-sufficiency, while the other is based on decreasing costs. A comparison is made to understand when each control returns the most benefits and what exactly these benefits are. Using a combination of MATLAB and Simulink each of the components mentioned above were modelled using current practices in literature. Scenarios were developed to create a basis for comparison: baseline scenario, Self-sufficiency based (SSB) scenario and Price-based (PB) scenario. The last two are collectively termed the Distributed Energy Resource (DER) scenario. The electrification of heating has a significant impact on the load prole, the largest loads occur in the winter. It was found that the highest self-sufficiency achieved was 43% utilising the SSB control, whereas with the PB control a maximum self-sufficiency of 41.3% was achieved. These percentages can mainly be attributed to the combination of large load and low PV production during the colder months of the year, indicating a clear need for studies into the impacts of heating electrification for consumers. This fraction can be increased by identifying further combinations of DERs that are sustainable, low cost and also available during the colder months of the year. Furthermore, levelised cost of electricity of the PV system accounted for only 19% of the total system levelised cost of electricity; while the zinc-bromine flow battery and and FCEVs accounted for nearly 60% of it. On average the proposed system provides energy at an average (across both controls) cost of 0.304e/kWh. The costs of the proposed system are relatively high, and the largest contributors to this are the FCEV fleet and the chosen battery.

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 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 objective of this study was identifying factors that contribute to Dutch electric vehicle (EV) drivers’ acceptance of vehicle-to-grid (V2G) at long-term parking lots. The results of this study aim to help V2G system designers to improve the quality of bi-directional V2G charging services for EV users and to foster V2G acceptance. The following problem statement was formulated: “To what extent do Dutch EV drivers accept V2G at long-term parking?” Based on a literature review and 20 exploratory semi-structured interviews with Dutch EV users, the conceptual model of the Theory of Planned Behaviour was contextualized for V2G acceptance by extending it. The resulting model includes V2G acceptance as a core concept and following influencing main factors or categories: perceived benefits, perceived barriers, attitudes, subjective norms, perceived behavioural control, EV driver’s profile characteristics, trust and intention to accept. Based on the interviews, the main conclusion was that EV users predominantly showed high acceptance of V2G at long-term parking, but that it was dependent on a relatively high number of different underlying factors or sub-factors (85) and that their individual attitudes differed with regards to several topic areas or categories (e.g. perceived benefits and barriers). Most interviewees would have the intention to use V2G at long-term parking on condition that they could receive monetary compensation for possible battery degradation, compensation for experienced discomfort and that the (technical) risks of V2G participation are transparently communicated. Furthermore, the interviewees indicated that the use of V2G systems should be simple, easy-to-use and not significantly different from (using) regular charging devices. Based on the results of this study, it is recommended that future research should focus on EV drivers that have practical experience with V2G systems. Furthermore, V2G system designers should adopt a consumer-centric approach by focussing on clear-cut information provision for EV users, create business cases so that EV users show a level of content, choose for V2G bi-directional charger vendors and aggregators that offer a user-friendly interface, so that EV drivers can have the option to exert control.

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.