Biografie

Onderzoek

Voormalige teamleden

• Qisong Yang (2023; promotor: Matthijs Spaan) "Risk Aversion and Guided Exploration in Safety-Constrained Reinforcement Learning"
• Chenguang Wang (2023; promotor: Peter Palensky) "Anomaly Detection and Synthetic Data Generation for Power Systems Using Autoencoder Neural Networks"
• Michael Evans (2019, Imperial College London; first supervisor: David Angeli) "Characterising and maximising aggregate flexibility of heterogeneous energy storage units"

• Lotte Zwart (2022, with Stedin), "Congestion forecasting using a custom loss function"
• Thomas Georgiou (2022, with Qirion/Alliander), "Interpretation of the Machine Learning Fault Classification Model Results Using Explainable Features"
• Kevin Dankers (2022), "Profit optimized machine learning aided electricity storage; Comparison between privately owned and neighborhood shared"
• Archana Ranganathan (2021, with Qirion/Alliander), "Automatic Identification of Fault Types in the Distribution Network using Supervised Learning"
• Sai Suprabhath Nibhanupudi (2021, with Phase to Phase), "State Estimation in Medium Voltage Distribution Networks"
• Ramon Mengerink (2021), "Cross-Border Participation in Capacity Mechanisms"
• Devendra Kulkarni (2020, with Qirion/Alliander), "Unsupervised Learning to Locate Weak Spots in the Medium Voltage Grid"
• Jules Zweekhorst (2020, with TenneT), "The development of a two day ahead power forecasting model for an offshore windpark"
• Julian Betge (2020, with Alliander), "Monte Carlo Sampling Techniques for the Efficient Estimation of Risk Metrics of a Stochastic Distribution Grid Power Demand Model"
• Subhitcha Ramkumar (2020), "Real Time Market Based Control of Flexible Distributed Energy Resources"
• Medha Subramanian (2020, with TenneT), "Optimising Grid Topology Reconfiguration using Reinforcement Learning"
• María Miranda Castillo (2019, with ENTSO-E), "Evaluation of missing capacity and resource adequacy in an interconnected power system"
• Shreyas Nikte (2019), "Investigation of active learning techniques for dynamic Time-of-Use (dToU) tariff policy design for residential users"
• Jennie Christiaanse (2019, with HyTEPS), "Algorithm for Determining the Hosting Capacity of Independent PV, or EV Charger Systems"
• Jonathan Budez (2019), "Quantifying the Contribution of distributed flexible loads to congestion management"
• Sotiris Dimitrakopoulos (2019, with DEPsys), "Linear state estimation method for distribution grids"
• Roberto Francica (2019, with Alliander), "Assessment of machine learning algorithms for the purpose of heat pump detection based on load profiles and temperature readings"
• Cheng-Kai Wang (2018), "Urban building energy modeling using a 3D city model and minimizing uncertainty through Bayesian inference"
• Rob de Nie (2018, with DWA), "Detecting a change in building electricity consumption patterns from electricity master meter data"

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