The electricity grid in the Netherlands is currently unable to provide sufficient capacity for both the integration of new renewable electricity powerplants as well as for the integration of new electricity demands like electric vehicle charging. Symptoms of this scarcity of capacity, also seen in other countries undergoing an energy transition, are observed in various forms. On the generation side, newly planned solar photovoltaic projects at both commercial and residential scales are increasingly being denied permission to connect to the grid or face long delays for grid reinforcement before they are connected. Since 2020, new utility-scale solar Photovoltaic (PV) installations were provided a maximum of 70% grid connection capacity relative to the solar installed capacity. In 2022, this permitted grid connection capacity has been further lowered to 50% for new projects larger than 1 MWp. On the demand side, recent mapping studies by the Dutch grid operators show that a majority of the country faces structural congestion in the distribution and transmission grids. The Dutch ambition, as stated in the Regional Energy Strategy (RES), is to integrate 12 GWp of additional solar installed capacity to the existing 14 GWp by 2030. Also by 2030, the total number of Electric Vehicles (EVs) in the Netherlands is expected to increase from about 390,000 (4.4% of the total Dutch passenger vehicle fleet) today to about 1 million (10%), increasing the peak electricity demand. The scarcity of capacity in the electricity grid to integrate both low carbon solar generation and electric vehicle charging presents an obstacle to the realisation of both short and long term emissions targets. Even though significant grid expansion is already planned and commissioned, this scarcity of capacity is expected to be a characteristic feature of the electricity grid over the coming decades. This thesis aims to investigate how the coupling of solar carparks and EV charging can enable their integration in a grid with scarce capacity while lowering operational carbon emissions. Two configurations of solar carparks for EV charging are analysed, with the aim of reducing the grid capacity needed: Chapter 3 analyses the first configuration: a solar carpark for charging EVs at a workplace in the Netherlands where demand peaks are caused by the simultaneous charging of EVs. The inclusion of EV demand forecasting within the scheduled charging reduces annual peak EV charging power by 36-39% relative to immediate charging. These reductions in peak demand enable a more effective use of the available power capacity (now mandated to 50% of solar installed capacity) as well as increase the utilisation of generated solar energy by reducing the need for solar curtailment. Chapter 4 investigates the second configuration: an off-grid solar carpark for EV charging at a long term (>24 hours) parking lot in a Dutch airport. Offgrid solar charging would enable rapid planning of charging facilities for EVs, removing the uncertainty, delays and costs associated with a grid connection. However, these benefits come with a trade-off: not all vehicles are fully charged at the time of departure. With immediate charging, 20% of EVs over the year leave with a state-of-charge lower than 60% and 3% of EVs leave with a state-of-charge lower than 40%. The adequacy of fleet-level charging is lowest during the low irradiance month of December, during which 63% of vehicles leave with a state-of-charge lower than 60% and 11% of vehicles leave with a state-of-charge lower than 40%. Prioritising the charging of plugged-in vehicles with the lowest state-of-charge ensures that no vehicles leave with a state-of-charge lower than 40% over the entire year, even in the low irradiance winter months. Increasing the minimum duration of parking reduces the fraction of vehicles leaving with state-of-charge below 60% by about 2% per day. The consequences of scheduled charging on greenhouse gas emissions are investigated in Chapters 5 and 6: Chapter 5 analyses a recently constructed solar carpark located in Dronten, the Netherlands, which includes a solar array, a nickel metal hydride battery and charge points for electric vehicle charging. The aim of the study is to quantify the magnitude of offset carbon emissions per year by the solar carport, and the contribution of battery storage to this offset. The prevalent practice of using the annual average carbon intensity is found to be unsuitable for estimating the annual offset carbon emissions since it does not account for the intra-day patterns of solar production, EV charging and battery cycling. To overcome this, we propose a novel method to calculate the annual offset carbon emissions, making use of the hourly average and hourly marginal carbon intensity. The choice of approach is found to make a difference to the calculated values of the annual offset emissions of the solar carpark. The use of hourly average carbon intensity, which takes into account variation in production, generation and storage, leads to a higher calculated value of annual offset carbon emissions by about 7% relative to a method using the annual average carbon intensity. The use of the hourly marginal carbon intensity to calculate the annual offset carbon emissions suggests that solar carparks have about a 55% higher incremental effect on the carbon intensity associated with the new load of EV charging than what is conventionally calculated. When comparing the annual offset carbon emissions from the solar carpark with and without a battery, we find that the use of the battery has a negligible effect on the annual carbon offset by the system. This result is found to be robust across all the methods of calculation. We therefore conclude that the use of batteries in solar carparks have a low contribution to the total carbon offset by the solar carport. Chapter 6 investigates the effect of price-based scheduling of EV charging on the carbon intensity of the electricity used by a scheduled fleet of EVs. Real data of over 55,000 home charging sessions collected from 1031 charge points in the Netherlands is analysed. A simulation is made with a commercial smart charging algorithm to create a scheduled charging profile ex post from the EV charging data set. The profile results in an average price reduction of 25% for the overall fleet relative to the costs for unscheduled charging of the fleet over the same period. The time dependent hourly carbon intensity of electricity consumed in the Dutch low voltage grid in 2018 is used to find the impact of price-based scheduling on the mean carbon intensity of electricity used by the fleet. A small decrease of 1.2% in carbon intensity used by the entire EV fleet is observed over the year. Although price optimisation has large effects on the carbon intensity in individual sessions, the effect is found to balance out over the large number of sessions in the year. Chapter 7 investigates the factors affecting the consumer acceptance of Vehicle-to-Grid (V2G) charging, which remains an insufficiently investigated barrier for the use of the full potential of EVs in demand response and storage. The research work comprises two stages of semi-structured interviews: the first with EV drivers who have never experienced V2G charging, and the second with EV drivers who experienced V2G charging. The participants in the second stage are given access to a V2G-compatible Nissan LEAF and the V2G charging facilities set up in a living lab on the University campus for at least a week each, after which they are interviewed. Clear communication of the battery impacts, financial compensation and operational control are all found to foster acceptance and were, in many cases, necessary conditions for acceptance. The main barriers for acceptance found are range anxiety in various forms, concerns about the effects of V2G charging on the EV battery and the perceived loss of freedom associated with private vehicles. A majority of participants interviewed from both groups are found to accept or conditionally accept V2G charging. This suggests that the use of EVs for demand side storage in addition to demand response is already acceptable to a subset of current EV drivers. The study also clarifies the conditions under which V2G charging would be more acceptable to a broader group of EV users. The results obtained in this thesis show that the coupling of solar photovoltaics and EV charging enables the integration of both in a grid with scarce capacity. We therefore recommend that solar carparks for EV charging be more widely implemented at workplaces and at longterm (>24 hour) parking lots, though without stationary batteries.@en

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

This study aims to investigate the consumer acceptance of Vehicle-to-Grid (V2G) charging of electric vehicle (EV) drivers. To the best of the authors’ knowledge, this is the first V2G acceptance study that is based on actual users’ experience of V2G charging. A test set up with a V2G charge point at a solar carport was constructed at the Delft University of Technology. Seventeen participants in the study were given access to a V2G-compatible Nissan LEAF and the constructed V2G charging facilities, after which they were interviewed. Clear communication of the impacts of V2G charging cycles on EV batteries, financial compensation covering these impacts, real-time insight on the battery state-of-charge and the ability to set operational parameters through a user-friendly interface were all found to foster acceptance. The main barriers for acceptance were the uncertainty associated with battery state-of-charge, the increased need for planning charging and trips, the increased anxiety about the ability of the vehicle to reach its destination, economic and performance-related effects on the EV’s battery and the restriction of the freedom that users associated with their personal vehicles. The participants were found to be divided across high, conditional and low acceptance of V2G charging. The use of V2G charging over the trial period was found to inform their opinions: tangible factors such as range anxiety and the user interface were given more importance than abstract concepts such as lack of standards that were discussed by users without experience of V2G charging. Our study indicates that V2G charging in its current form is acceptable to a section of current EV users. The discussion provides insights on extending the relevance of our findings across other user groups and over further developments in the field.@en

The objective of this study is to identify factors that influence actual electric vehicle (EV) drivers’ acceptance of Vehicle-to-Grid (V2G) charging. The study takes a qualitative approach in order to provide insight into actual EV users’ perceptions of V2G technology and their underlying motivation to accept or not accept V2G. The Theory of Planned Behaviour is adopted to create a basic conceptual model of the potential factors influencing users’ acceptance of V2G. Twenty semi-structured interviews are conducted among Dutch EV drivers, including both regular EV drivers, as well as participants who had previously taken part in V2G projects. The factors that are found to be most important for fostering acceptance are financial compensation, transparent communication and reliable control of the system by the user. On the other hand, the factors that are found to have a negative effect on acceptance are range anxiety, discomfort experienced while participating and battery degradation. Our study shows that the majority of our interview participants accept V2G albeit with some reservations and caution. As EVs and V2G are new technologies, our sample of twenty actual EV users consists of early adopters. As such, their attitudes may not reflect those of the majority of future users. However, our study suggests that there are EV users who are willing to use V2G charge points and will continue to do so. The reasons behind such user acceptance are further described in the study together with additional insights and ideas for future research.@en

This work analyses the effectiveness of an off-grid solar photovoltaic system for the charging of electric vehicles (EVs) in a long-term parking lot. The effectiveness of charging is investigated through analysis of the states of charge (SoC) at departure of EVs plugged in at the parking lot over the simulated year. Although the share of vehicles leaving with inadequate charge over the entire year is small, this share is relatively high during low irradiance winter months. We show that an increase in efficiency of the solar modules used in the system and an increase in the minimum duration of time spent at the parking lot are effective within limits at improving charging adequacy. We then formulate three strategies to allocate the available energy in the system with the objective of reducing the number of vehicles leaving at lower SoCs: 1) curtailment of charging beyond 80% state of charge, 2) prioritised charging of vehicles at low SoCs and 3) prioritised charging based on both SoC and time before departure. We identify the strategy prioritising vehicles with low state of charge to be most effective, but performance in the worst month remains a challenge for the location considered.

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Aggregation of sufficiently large electric vehicle (EV) fleets and control over their charging schedules enables aggregators to utilise the flexibility of EV charging in the Day Ahead Market. Optimising the charge scheduling of such fleets enables time-shifting of electricity demand to hours when electricity is cheaper, reducing the electricity cost for charging the entire fleet. Time shifting with scheduled charging is expected to influence the average carbon intensity of the energy used by these vehicles. This work aims to quantify the change in the carbon intensity of energy used by smart charged vehicles. It uses real data collected from over 55, 000 home charging sessions from 1031 chargepoints in the Netherlands in 2018. A simulation was made with a commercial smart charging algorithm to create a scheduled charging profile ex post from the historic EV charging dataset. The simulation resulted in an average price reduction of electricity for the fleet of about 25% relative to unscheduled charging of the same fleet over the same period. The time dependent average carbon intensity of electricity consumed in the Netherlands was used to calculate the mean carbon intensity of the electricity used to charge the fleet over the period in the scheduled and unscheduled charging cases. The results revealed a small decrease in carbon intensity by 1.2%. Analysis reveals that price optimisation can have large effects on the mean carbon intensity of individual sessions in the Dutch grid, but the net effect is averaged out over a large number of sessions and over the year.

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Microgrids enable distribution of electricity with higher shares of variable renewables, higher power quality, greater reliability and higher efficiency. There are a large number of factors in addition to the technology, which affect their shift towards market competitiveness and widespread adoption. The PESTEL framework, covering Political, Economic, Social, Technical, Environmental and Legislative factors, is used to identify and describe the drivers and barriers for microgrid development at the global level. The framework enables a broader approach to describe potential for microgrid applications. The results aim to provide engineers, project developers and microgrid specialists with an overview of the prospects for microgrid deployment.

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Scheduled charging offers the potential for electric vehicles (EVs) to use renewable energy more efficiently, lowering costs and improving the stability of the electricity grid. Many studies related to EV charge scheduling found in the literature assume perfect or highly accurate knowledge of energy demand for EVs expected to arrive after the scheduling is performed. However, in practice, there is always a degree of uncertainty related to future EV charging demands. In this work, a Model Predictive Control (MPC) based smart charging strategy is developed, which takes this uncertainty into account, both in terms of the timing of the EV arrival as well as the magnitude of energy demand. The objective of the strategy is to reduce the peak electricity demand at an EV parking lot with PVarrays. The developed strategy is compared with both conventional EV charging as well as smart charging with an assumption of perfect knowledge of uncertain future events. The comparison reveals that the inclusion of a 24 h forecast of EV demand has a considerable effect on the improvement of the performance of the system. Further, strategies that are able to robustly consider uncertainty across many possible forecasts can reduce the peak electricity demand by as much as 39% at an office parking space. The reduction of peak electricity demand can lead to increased flexibility for system design, planning for EV charging facilities, deferral or avoidance of the upgrade of grid capacity as well as its better utilization@en

This paper outlines the challenges faced during the implementation of a Vehicle-2-Grid set-up from the design phase, through project planning, application for permits and clearances, procurement of equipment and installation. It is based on the experience of designing a living lab at the Green Village in TU Delft, the Netherlands. Desk research and active collection of information from various stakeholders was performed to outline the current state of the technology and the barriers for various stakeholders. It is the aim of this work to provide insight into the subsequent design of V2G systems for future research and pilot projects.

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