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- Eindhoven University of Technology (TU/e)
- Delft University of Technology (TU Delft); today published
- Delft University of Technology (TU Delft); yesterday published
- Eindhoven University of Technology (TU/e); Published today
- Eindhoven University of Technology (TU/e); Published yesterday
- University of Twente
- University of Twente (UT)
- University of Twente (UT); Published today
- University of Twente (UT); yesterday published
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Field
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exploratory research approach involving longitudinal case studies and participatory action research (PAR) in a set of use cases with energy community projects ranging from smart grid experimentation and energy
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adopts a qualitative exploratory research approach involving longitudinal case studies and participatory action research (PAR) in a set of use cases with energy community projects ranging from smart grid
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a set of use cases with energy community projects ranging from smart grid experimentation and energy sharing in rural regions in the Netherlands to developing an energy community in Amsterdam
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optimization lab (EES EMPDO lab). The former focuses on intelligent energy network research, including: demand management and flexibility, digital twinning, data analytics, smart grid ICT architectures and
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technology companies to develop solar-integrated electric buses, smart charging hubs, and advanced grid services. Within this project, the University of Twente is involved in developing multi-port, high
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on intelligent energy network research, including: demand management and flexibility, digital twinning, data analytics, smart grid ICT architectures and systems integration in multi energy systems. The latter
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optimization lab (EES EMPDO lab). The former focuses on intelligent energy network research, including: demand management and flexibility, digital twinning, data analytics, smart grid ICT architectures and
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energy network research, including: demand management and flexibility, digital twinning, data analytics, smart grid ICT architectures and systems integration in multi energy systems. The latter specializes
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electrical power, enabling smart sensors to operate without batteries. You will explore novel capacitor-based rectifier architectures, adaptive impedance-matching algorithms, and on-chip protection mechanisms
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longer sustainable. This project pioneers a new paradigm: we design smart, low-power digital AI co-processors that learn and correct the imperfections of their analog counterparts in real-time. As a PhD