© 2025 SURF
Following the Sector Protocol for Quality Assurance for Practice-Based.Contributors Academy for AI, Games and Media:Mata Haggis Burridge (prof. EG), Qiqi Zhou, Hillevi Boerboom, Maria Pafi (postdoc, WuR), Alexander van Buggenum, Ella Betts, Wilma Franchimon (dir. AGM), Nick van Apeldoorn (Coord.Digireal), Harald Warmelink (Coord. Cradle & MSP Challenge), Magali Patrocínio Gonçalves, Ard Bonewald (MT Games), Marin Hekman, Marie Lhuissier, Carlos Santos (CTO Cradle), Jeremiah van Oosten (MT, games), Kevin Hutchinson, Frank Peters (MT ADS&AI), Bram Heijligers, Joey Relouw, Marnix van Gisbergen (Prof. DMC), Shima Rezaei Rashnoodi (Coord. DMC), Phil de Groot, Igor Mayer (prof. SG), Niels Voskens, Fabio Ferreira da Costa Campos, Tuki Clavero, Jens Hagen, Wilco Boode, Natalia Harazhanka-Pietjouw (PPC), Jacopo Fabrini & Silke Hassreiter.
Over the last years a large growth in Electric Vehicles (EV) and charging infrastructure (CI) development has been observed. Particularly in metropolitan areas this growth has led to a system in which multitudes of interactions between EV users take place. While many researchers have focused on EV user charging behavior and deployment strategies for CI, little attention has been paid to conceptualizing the problem domain. This research provides a brief overview of complex systems theory, and derives six characterizing elements of complex systems that may be applicable for CI. The paper investigates both theoretically but also empirically how these characterizing elements apply for CI and provides implications for the further roll-out of CI for both policy makers and researchers. We illustrate our findings with preliminary results form ongoing research. Recommendations include the further development of simulation tools that are capable of exploring effects of e.g. non-linear behavior, feedback loops and emergence of new patterns on CI performance. In the end this paper aims to provide directions to enable policy makers to be better prepared for the anticipated exponential growth of EVs and CI.
MULTIFILE
The idea that technologies influence society—both positively and negatively—is not new. This is mainly the terrain of the philosophy and the ethics of technolo-gy research. Similarly, design research aims to help create new technologies in line with individual, social, and societal needs and values. Against this backdrop, it seems essential to expose relations between design and philosophy of tech-nology research, particularly from a methodological perspective. The main goal of this paper is to suggest a preliminary overview of methods and approaches that can inspire and inform interdisciplinary collaboration and, with that, sys-tematic engagement with ethics in design processes. Through interdisciplinary exchange, we propose a preliminary typology of ethics-informed methods and approaches based on two main dimensions, namely theory-grounded approaches to theoretically-flexible techniques and assessment to accompaniment. This mapping intends to help navigate the ethical qualities of selected methods from both disciplines, and it aims to create a platform for fruitful interdisciplinary conversations.
MULTIFILE
The idea that technologies influence society—both positively and negatively—is not new. This is mainly the terrain of the philosophy and the ethics of technolo-gy research. Similarly, design research aims to help create new technologies in line with individual, social, and societal needs and values. Against this backdrop, it seems essential to expose relations between design and philosophy of tech-nology research, particularly from a methodological perspective. The main goal of this paper is to suggest a preliminary overview of methods and approaches that can inspire and inform interdisciplinary collaboration and, with that, sys-tematic engagement with ethics in design processes. Through interdisciplinary exchange, we propose a preliminary typology of ethics-informed methods and approaches based on two main dimensions, namely theory-grounded approaches to theoretically-flexible techniques and assessment to accompaniment. This mapping intends to help navigate the ethical qualities of selected methods from both disciplines, and it aims to create a platform for fruitful interdisciplinary conversations.
MULTIFILE
As society has to adapt to changing energy sources and consumption, it is driving away from fossil energy. One particular area of interest is electrical driving and the increasing demand for (public) charging facilities. For municipalities, it is essential to adapt to this changing demand and provide more public charging facilities.In order to accommodate on roll-out strategies in metropolitan areas a data driven simulation model, SEVA1, has been developed The SEVA base model used in this paper is an Agent-Based model that incorporate past sessions to predict future charging behaviour. Most EV users are habitual users and tend to use a small subset of the available charge facilities, by that obtaining a pattern is within the range possibilities. Yet, for non-habitual users, for example, car sharing users, obtaining a pattern is much harder as the cars use a significantly higher amount of charge points.The focus of this research is to explore different model implementations to assess the potential of predicting free-floating cars from the non-habitual user population. Most important result is that we now can simulate effects of deployement of car sharing users in the system, and with that the effect on convenience for habitual users. Results show that the interaction between habitual and non habitual EV users affect the unsuccessful connection attempts based increased based on the size of the car-sharing fleet up to approximately 10 percent. From these results implications for policy makers could be drawn.
MULTIFILE
Dynamic energy contracts, offering hourly varying day-ahead prices for electricity, create opportunities for a residential Battery Energy Storage System (BESS) to not just optimize the self-consumption of solar energy but also capitalize on price differences. This work examines the financial potential and impact on the self-consumption of a residential BESS that is controlled based on these dynamic energy prices for PV-equipped households in the Netherlands, where this novel type of contract is available. Currently, due to the Dutch Net Metering arrangement (NM) for PV panels, there is no financial incentive to increase self-consumption, but policy shifts are debated, affecting the potential profitability of a BESS. In the current situation, the recently proposed NM phase-out and the general case without NM are studied using linear programming to derive optimal control strategies for these scenarios. These are used to assess BESS profitability in the latter cases combined with 15 min smart meter data of 225 Dutch households to study variations in profitability between households. It follows that these variations are linked to annual electricity demand and feed-in pre-BESS-installation. A residential BESS that is controlled based on day-ahead prices is currently not generally profitable under any of these circumstances: Under NM, the maximum possible annual yield for a 5 kWh/3.68 kW BESS with day-ahead prices as in 2023 is EUR 190, while in the absence of NM, the annual yield per household ranges from EUR 93 to EUR 300. The proposed NM phase-out limits the BESS’s profitability compared to the removal of NM.
Electric vehicles and renewable energy sources are collectively being developed as a synergetic implementation for smart grids. In this context, smart charging of electric vehicles and vehicle-to-grid technologies are seen as a way forward to achieve economic, technical and environmental benefits. The implementation of these technologies requires the cooperation of the end-electricity user, the electric vehicle owner, the system operator and policy makers. These stakeholders pursue different and sometime conflicting objectives. In this paper, the concept of multi-objective-techno-economic-environmental optimisation is proposed for scheduling electric vehicle charging/discharging. End user energy cost, battery degradation, grid interaction and CO2 emissions in the home micro-grid context are modelled and concurrently optimised for the first time while providing frequency regulation. The results from three case studies show that the proposed method reduces the energy cost, battery degradation, CO2 emissions and grid utilisation by 88.2%, 67%, 34% and 90% respectively, when compared to uncontrolled electric vehicle charging. Furthermore, with multiple optimal solutions, in order to achieve a 41.8% improvement in grid utilisation, the system operator needs to compensate the end electricity user and the electric vehicle owner for their incurred benefit loss of 27.34% and 9.7% respectively, to stimulate participation in energy services.
