Mindful Power
Evaluating Energy Justice in Automated Decision-Making for Urban Electric Vehicle Charging Infrastructure in the Netherlands
F.M. Jocker (TU Delft - Architecture and the Built Environment)
G. Kortuem – Mentor (TU Delft - Internet of Things)
Clemens Driessen – Mentor (Wageningen University & Research)
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Abstract
This thesis examines the role of Automated Decision-Making (ADM) systems in advancing energy justice within urban Electric Vehicle Charging Infrastructure (EVCI) in the Netherlands. Centred on distributive, procedural, and recognition justice, the study explores how ADM impacts equitable access to EV charging and fair energy distribution amid the rapid electrification of passenger mobility. While ADM promises improved grid efficiency and stability, alleviating congestion, it also risks exacerbating socio-economic disparities in access to essential charging resources and energy, potentially widening existing inequalities.
Using a mixed-method approach encompassing Geographic Information System (GIS) analysis, Scenario Development, and Q-methodology, this research examines ADM’s effects on equity, fairness, inclusivity, and transparency across socio-economic groups. GIS findings reveal disparities in EVCI accessibility between affluent and low-income neighbourhoods in Amsterdam, highlighting the need for ADM frameworks that consider socio-economic factors in energy allocation. Scenario Development projects futures where stakeholders must balance individual and community needs, illustrating the critical trade-offs required to achieve equitable energy distribution. The Q-methodology builds consensus among diverse stakeholders, underscoring transparency and procedural fairness in promoting trust and aligning ADM outcomes with public values.
This study contributes to energy justice literature by showing how ADM systems can promote equitable EVCI outcomes that are just and inclusive. Policy recommendations offer a phased roadmap: in the short term, prioritise equitable distribution of EVCI using socio-economic data; in the medium term, develop adaptive ADM models for high-demand and grid-constrained regions; and in the long term, enhance community engagement through accessible platforms. \textit{Mindful Power} envisions ADM systems for EVCI that optimise technological efficiency without sacrificing social justice, supporting a fairer, more inclusive energy transition. Ultimately, this thesis provides a structured roadmap for sustainable, community-centred urban energy solutions, ensuring that the transition leaves no one behind.