Simon Tindemans

Assistant Professor

TU Delft

Netherlands

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About

Simon Tindemans is an Assistant Professor at TU Delft in the Netherlands. His research focuses on energy systems, particularly in the areas of energy storage, electric vehicles, and congestion management in electricity distribution networks. Recent articles authored by Professor Tindemans include topics such as the quantification of aggregate flexibility in electric vehicles and the application of probabilistic models for power system planning.

Articles (17)

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2025

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2024

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2024

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2024

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2024

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2024

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2023

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2023

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2022

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2022

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2022

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2022

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2021

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2021

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2021

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2020

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2020

Collaborators (5)

David Angeli

Imperial College London

UNITED KINGDOM

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Anoeska Buijze

Utrecht University

NETHERLANDS

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David Ribó-Pérez

Delft University of Technology

NETHERLANDS

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Peter Palensky

Professor at Delft University of Technology

Delft University of Technology

NETHERLANDS

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L.J. de Vries

Professor

Delft University of Technology

NETHERLANDS

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Simon Tindemans

Research Interests

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About

Articles (17)

Linear Aggregate Model for Realizable Dispatch of Homogeneous Energy Storage

Risk vs. restriction—An investigation of capacity-limitation based congestion management in electric distribution grids

Enhancing smart charging in electric vehicles by addressing paused and delayed charging problems

Efficient quantification and representation of aggregate flexibility in Electric Vehicles

Stable training of probabilistic models using the leave-one-out maximum log-likelihood objective

Representative days and hours with piecewise linear transitions for power system planning

Improved Anomaly Detection and Localization Using Whitening-Enhanced Autoencoders

Congestion management in electricity distribution networks

Flexibility Framework With Recovery Guarantees for Aggregated Energy Storage Devices

What is a good distribution network tariff?—Developing indicators for performance assessment

Generating multivariate load states using a conditional variational autoencoder

Generating multivariate load states using a conditional variational autoencoder

Scheduling of energy storage

Scheduling of energy storage

Low-Complexity Decentralized Algorithm for Aggregate Load Control of Thermostatic Loads

Correction to “Minimizing Unserved Energy Using Heterogeneous Storage Units” [Sep 19 3647-3656]

Accelerating system adequacy assessment using the multilevel Monte Carlo approach

Collaborators (5)

David Angeli

Anoeska Buijze

David Ribó-Pérez

Peter Palensky

L.J. de Vries

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