Zobrazeno 1 - 10
of 148
pro vyhledávání: '"P. Tindemans"'
Electric vehicles (EVs) play a crucial role in the transition towards sustainable modes of transportation and thus are critical to the energy transition. As their number grows, managing the aggregate power of EV charging is crucial to maintain grid s
Externí odkaz:
http://arxiv.org/abs/2403.13367
Aggregate peak Electric Vehicle (EV) charging demand is a matter of growing concern for network operators as it severely limits the network's capacity, preventing its reliable operation. Various tariff schemes have been proposed to limit peak demand
Externí odkaz:
http://arxiv.org/abs/2403.12215
Autor:
Silani, Amirreza, Tindemans, Simon H.
The rapid increase of photovoltaic cells, batteries, and Electric Vehicles (EVs) in electric grids can result in congested distribution networks. An alternative to enhancing network capacity is a redispatch market, allowing Distribution System Operat
Externí odkaz:
http://arxiv.org/abs/2403.11836
Publikováno v:
2023 IEEE Belgrade PowerTech, pp. 1-6. IEEE, 2023
The growing penetration of renewable energy sources (RESs) is inevitable to reach net zero emissions. In this regard, optimal planning and operation of power systems are becoming more critical due to the need for modeling the short-term variability o
Externí odkaz:
http://arxiv.org/abs/2310.04244
Electric demand and renewable power are highly variable, and the solution of a planning model relies on capturing this variability. This paper proposes a hybrid multi-area method that effectively captures both the intraday and interday chronology of
Externí odkaz:
http://arxiv.org/abs/2310.04239
Probabilistic modelling of power systems operation and planning processes depends on data-driven methods, which require sufficiently large datasets. When historical data lacks this, it is desired to model the underlying data generation mechanism as a
Externí odkaz:
http://arxiv.org/abs/2310.03556
Aggregation is crucial to the effective use of flexibility, especially in the case of electric vehicles (EVs) because of their limited individual battery sizes and large aggregate impact. This research proposes a novel method to quantify and represen
Externí odkaz:
http://arxiv.org/abs/2310.02729
Safety is critical to broadening the application of reinforcement learning (RL). Often, we train RL agents in a controlled environment, such as a laboratory, before deploying them in the real world. However, the real-world target task might be unknow
Externí odkaz:
http://arxiv.org/abs/2307.14316
Variational autoencoder (VAE) neural networks can be trained to generate power system states that capture both marginal distribution and multivariate dependencies of historical data. The coordinates of the latent space codes of VAEs have been shown t
Externí odkaz:
http://arxiv.org/abs/2303.11410
Autor:
Nico Brinkel, Thijs van Wijk, Anoeska Buijze, Nanda Kishor Panda, Jelle Meersmans, Peter Markotić, Bart van der Ree, Henk Fidder, Baerte de Brey, Simon Tindemans, Tarek AlSkaif, Wilfried van Sark
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-10 (2024)
Abstract Smart charging of electric vehicles can alleviate grid congestion and reduce charging costs. However, various electric vehicle models currently lack the technical capabilities to effectively implement smart charging since they cannot handle
Externí odkaz:
https://doaj.org/article/93901f08ac034996ae4ae4dfaec24c52
