Related papers: Modelling hydrogen integration in energy system mo…
Tulipa Energy Model aims to optimise the investment and operation of the electricity market, considering its coupling with other sectors, such as hydrogen and heat, that can also be electrified. The problem is analysed from the perspective…
This paper analyzes the implications of simplified pipeline gas flow models for integrated energy system planning. A case study of an integrated power-hydrogen expansion planning problem shows that simplifying pressure-flow relationships…
The modeling of complex systems such as ecological or socio-economic systems can be very challenging. Although various modeling approaches exist, they are generally not compatible and mutually consistent, and empirical data often do not…
The increasing penetration level of energy generation from renewable sources is demanding for more accurate and reliable forecasting tools to support classic power grid operations (e.g., unit commitment, electricity market clearing or…
In High Energy Physics (HEP), analysis metadata comes in many forms -- from theoretical cross-sections, to calibration corrections, to details about file processing. Correctly applying metadata is a crucial and often time-consuming step in…
The design of the future European energy system depends heavily on how Europe balances its domestic hydrogen production against its reliance on imports. This study reveals that neither-extreme full self-sufficiency nor complete reliance on…
Extensive molecular dynamics computer simulations have been conducted for ethanol-water liquid mixtures in the water-rich side of the composition range, with 10, 20 and 30 mol % of the alcohol, at temperatures between room temperature and…
Green hydrogen is essential for producing renewable fuels that are needed in sectors that are hard to electrify directly. Hydrogen production in a grid-connected hybrid renewable energy plant necessitates smart planning to meet long-term…
This paper studies the long-term energy management of a microgrid coordinating hybrid hydrogen-battery energy storage. We develop an approximate semi-empirical hydrogen storage model to accurately capture the power-dependent efficiency of…
This paper addresses the problem of predicting the energy consumption for the drivers of Battery electric vehicles (BEVs). Several external factors (e.g., weather) are shown to have huge impacts on the energy consumption of a vehicle…
Diffusion models, which leverage stochastic processes to capture complex data distributions effectively, have shown their performance as generative models, achieving notable success in image-related tasks through iterative denoising…
Probabilistic forecasting is receiving growing attention nowadays in a variety of applied fields, including hydrology. Several machine learning concepts and methods are notably relevant towards addressing the major challenges of formalizing…
Recent developments based on relativistic hydrodynamic models in high energy heavy ion collisions are discussed. I focus especially on how hydrodynamics works at RHIC energies and how one can use the most of it in analyses of jet quenching…
Hydrogen is becoming an increasingly appealing energy carrier, as the costs of renewable energy generation and water electrolysis continue to decline. Developing modelling and decision tools for the H$_{2}$ supply chain that fully capture…
In this article, we outline the modeling of a realistic dynamical model for comprehensive description of high energy heavy ion collisions. Comparing theoretical calculations and experimental data at RHIC, we give detailed discussions on the…
The emerging paradigm of interconnected microgrids advocates energy trading or sharing among multiple microgrids. It helps make full use of the temporal availability of energy and diversity in operational costs when meeting various energy…
Many studies have shown that hydrogen could play a large role in the energy transition for hard-to-electrify sectors, but previous modelling has not included the necessary features to assess its role. They have either left out important…
A key question for machine learning approaches in particle physics is how to best represent and learn from collider events. As an event is intrinsically a variable-length unordered set of particles, we build upon recent machine learning…
Given the central role of green e-molecule imports in the European energy transition, many studies optimize import pathways and identify a single cost-optimal solution. However, cost optimality is fragile, as real-world implementation…
In this work, we combine Density Functional Theory data with a Thermodynamic and a kinetic model to determine the total concentration of hydrogen implanted in the sub-surface of tungsten exposed to a hydrogen flux. The sub-surface hydrogen…