Combining electric cars with utility services seems to be a natural fit and holds the promise to tackle various mobility as well as electricity challenges at the same time. So far no viable business model for vehicle-to-grid technology has emerged, raising the question which characteristics a vehicle-to-grid business model should have. Drawing on an exploratory study amongst 189 Dutch consumers this study seeks to understand consumer preferences in vehicle-to-grid business models using conjoint analysis, factor analysis and cluster analysis. The results suggest that consumers prefer private ownership of an EV and a bidirectional charger instead of community ownership of bidirectional charger, they prefer utility companies instead of car companies as the aggregator and they require home and public charging. The most salient attributes in a V2G business model seem to be functional rather than financial or social. The customer segment with the highest willingness to adopt V2G prefers functional attributes. Based on the findings, the study proposes a business model that incorporates the derived preferences
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Controlled charging of electric vehicles (EVs) can be used to avoid peaks in the power grid by limiting, and shifting the EV power demand during peak hours. This paper presents results on user preferences and experiences regarding controlled (or smart) charging of EVs via home chargers. Data is derived from a controlled charging demonstration project, in which 138 Dutch households participated. With the availability of an override button, households were assigned either a static or dynamic charging profile. Using surveys and interviews, data was collected on three topics: (1) controlled charging, (2) the override button and (3) financial motivations.
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On the eve of the large-scale introduction of electric vehicles, policy makers have to decide on how to organise a significant growth in charging infrastructure to meet demand. There is uncertainty about which charging deployment tactic to follow. The main issue is how many of charging stations, of which type, should be installed and where. Early roll-out has been successful in many places, but knowledge on how to plan a large-scale charging network in urban areas is missing. Little is known about return to scale effects, reciprocal effects of charger availability on sales, and the impact of fast charging or more clustered charging hubs on charging preferences of EV owners. This paper explores the effects of various roll-out strategies for charging infrastructure that facilitate the large-scale introduction of EVs, using agent-based simulation. In contrast to previously proposed models, our model is rooted in empirically observed charging patterns from EVs instead of travel patterns of fossil fuelled cars. In addition, the simulation incorporates different user types (inhabitants, visitors, taxis and shared vehicles) to model the diversity of charging behaviours in an urban environment. Different scenarios are explored along the lines of the type of charging infrastructure (level 2, clustered level 2, fast charging) and the intensity of rollout (EV to charging point ratio). The simulation predicts both the success rate of charging attempts and the additional discomfort when searching for a charging station. Results suggest that return to scale and reciprocal effects in charging infrastructure are considerable, resulting in a lower EV to charging station ratio on the longer term.
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In the coming decades, a substantial number of electric vehicle (EV) chargers need to be installed. The Dutch Climate Accord, accordingly, urges for preparation of regional-scale spatial programs with focus on transport infrastructure for three major metropolitan regions among them Amsterdam Metropolitan Area (AMA). Spatial allocation of EV chargers could be approached at two different spatial scales. At the metropolitan scale, given the inter-regional flow of cars, the EV chargers of one neighbourhood could serve visitors from other neighbourhoods during days. At the neighbourhood scale, EV chargers need to be allocated as close as possible to electricity substations, and within a walkable distance from the final destination of EV drivers during days and nights, i.e. amenities, jobs, and dwellings. This study aims to bridge the gap in the previous studies, that is dealing with only of the two scales, by conducting a two-phase study on EV infrastructure. At the first phase of the study, the necessary number of new EV chargers in 353 4-digit postcodes of AMA will be calculated. On the basis of the findings of the Phase 1, as a case study, EV chargers will be allocated at the candidate street parking locations in the Amsterdam West borough. The methods of the study are Mixed-integer nonlinear programming, accessibility and street pattern analysis. The study will be conducted on the basis of data of regional scale travel behaviour survey and the location of dwellings, existing chargers, jobs, amenities, and electricity substations.
Based on the model outcomes, Houtlaan’s energy transition will likely result in congestion and curtailmentproblems on the local electricity grid within the next 5-7 years, possibly sooner if load imbalance between phasesis not properly addressed.During simulations, the issue of curtailment was observed in significant quantities on one cable, resulting in aloss of 8.292 kWh of PV production per year in 2030. This issue could be addressed by moving some of thehouses on the affects cable to a neighboring under-utilized cable, or by installing a battery system near the end ofthe affected cable. Due to the layout of the grid, moving the last 7 houses on the affected cable to the neighboringcable should be relatively simple and cost-effective, and help to alleviate issues of curtailment.During simulations, the issue of grid overloading occurred largely as a result of EV charging. This issue can bestbe addressed by regulating EV charging. Based on current statistics, the bulk of EV charging is expected to occurin the early evening. By prolonging these charge cycles into the night and early morning, grid overloading canlikely be prevented for the coming decade. However, such a control system will require some sort of infrastructureto coordinate the different EV charge cycles or will require smart EV chargers which will charge preferentiallywhen the grid voltage is above a certain threshold (i.e., has more capacity available).A community battery system can be used to increase the local consumption of produced electricity within theneighborhood. Such a system can also be complemented by charging EV during surplus production hours.However, due to the relatively high cost of batteries at present, and losses due to inefficiencies, such a systemwill not be financially feasible without some form of subsidy and/or unless it can provide an energy service whichthe grid operator is willing to pay for (e.g. regulating power quality or line voltage, prolonging the lifetime of gridinfrastructure, etc.).A community battery may be most useful as a temporary solution when problems on the grid begin to occur, untila more cost-effective solution can be implemented (e.g. reinforcing the grid, implementing an EV charge controlsystem). Once a more permanent solution is implemented, the battery could then be re-used elsewhere.The neighborhood of Houtlaan in Assen, the Netherlands, has ambitious targets for reducing the neighborhood’scarbon emissions and increasing their production of their own, sustainable energy. Specifically, they wish toincrease the percentage of houses with a heat pump, electric vehicle (EV) and solar panels (PV) to 60%, 70%and 80%, respectively, by the year 2030. However, it was unclear what the impacts of this transition would be onthe electricity grid, and what limitations or problems might be encountered along the way.Therefore, a study was carried out to model the future energy load and production patterns in Houtlaan. Thepurpose of the model was to identify and quantify the problems which could be encountered if no steps are takento prevent these problems. In addition, the model was used to simulate the effectiveness of various proposedsolutions to reduce or eliminate the problems which were identified
