
Dr. S.H. (Simon) Tindemans
Dr. S.H. (Simon) Tindemans
Profiel
Biografie
Simon Tindemans is een universitair docent in de Intelligent Electrical Power Grids groep. Hij doet onderzoek op het thema "statistische energiesystemen," op het raakvlak tussen de elektrotechniek, (computationele) statistiek en informatica.
Onderzoek
Zie de Engelse versie van deze pagina (schakelen rechtsboven op deze pagina) voor een uitgebreide beschrijving van mijn onderzoek.
Huidig team
Promovendi: Hazem Abdelghany, Chenguang Wang, Roman Hennig, Qisong Yang, Ensieh Sharifnia, Nanda Panda, Kutay Bölat
MSc-afstudeerstudenten: Lotte Zwart, Thomas Georgiou, Kevin Dankers
Voormalige teamleden
Promovendi (copromotor)
- Michael Evans (2019, Imperial College London; first supervisor: David Angeli) "Characterising and maximising aggregate flexibility of heterogeneous energy storage units"
Scripties beschikbaar via https://repository.tudelft.nl/islandora/search/?collection=education
- 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"
Publicaties
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2022
Flexibility Framework with Recovery Guarantees for Aggregated Energy Storage Devices
Michael Evans / Simon H. Tindemans / David Angeli
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2022
Safety-constrained reinforcement learning with a distributional safety critic
Qisong Yang / Thiago D Simão / Simon H. Tindemans / Matthijs T.J. Spaan
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2022
State-of-the-art of data collection, analytics, and future needs of transmission utilities worldwide to account for the continuous growth of sensing data
Felix Rafael Segundo Sevilla / Yanli Liu / Emilio Barocio / Petr Korba / Manuel Andrade / Balarko Chaudhuri / Jochen Cremer / Jose Rueda / Simon Tindemans / More Authors
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2022-7-15
What is a good distribution network tariff?—Developing indicators for performance assessment
Developing indicators for performance assessment
R.J. Hennig / David Ribó-Pérez / Laurens De Vries / Simon H. Tindemans -
2021
Coordination of Heterogeneous Deferrable Loads using the F-MBC Mechanism
S. Ramkumar / H.A.M.F. Abdelghany / S.H. Tindemans
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