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Application of Machine Learning and Mathematical Programming in the Optimization of the Energy Management System for Hybrid-Electric Vessels Having Cyclic Operations

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Identification of typical district configurations: A two-step global sensitivity analysis framework

François Maréchal, Jonas Schnidrig, Cédric Terrier

The recent geopolitical conflicts in Europe have underscored the vulnerability of the current energy system to the volatility of energy carrier prices. In the prospect of defining robust energy systems ensuring sustainable energy supply in the future, the ...

Pergamon-Elsevier Science Ltd2024

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Paul Scharnhorst

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

EPFL2024

Design and assessment of an evaporating water-cooled methanation reactor for a SOE-based power-to-methane system

Philippe Aubin

The transition towards clean renewable energy sources, where wind and solar are prone to variation, requires adequate energy storage. Power-to-methane (PtM) systems can be part of the solution. Specifically, solid-oxide-electrolyser (SOE) based PtM systems ...

EPFL2024

Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets

Mohammad Khaja Nazeeruddin

Herein, machine learning (ML) models using multiple linear regression (MLR), support vector regression (SVR), random forest (RF) and artificial neural network (ANN) are developed and compared to predict the output features viz. specific capacitance (Csp), ...

Elsevier Science Sa2024

Koopman-based Data-driven Robust Control of Nonlinear Systems Using Integral Quadratic Constraints

Alireza Karimi, Mert Eyuboglu

This paper introduces a novel method for data-driven robust control of nonlinear systems based on the Koopman operator, utilizing Integral Quadratic Constraints (IQCs). The Koopman operator theory facilitates the linear representation of nonlinear system d ...

2024

Biodiesel from Bark and Black Liquor-A Techno-Economic, Social, and Environmental Assessment

Julia Granacher

A techno-economic assessment and environmental and social sustainability assessments of novel Fischer-Tropsch (FT) biodiesel production from the wet and dry gasification of biomass-based residue streams (bark and black liquor from pulp production) for tran ...

MDPI2024

The Effect of Rivers on Energy Balance at the Neighborhood Scale. A comparative analysis of four Rhodanian sites in France and Switzerland

Sergi Aguacil Moreno, Martine Laprise, Sara Sonia Formery Regazzoni, Emmanuel Rey

This research aims to compare the greenhouse gas (GHG) emissions of new neighbourhood projects near the Rhône River in France and Switzerland. The study considers the influence of the river on energy demand and resilience to climate change of 12 project-ba ...

Wrocław University of Science and Technology Publishing House2024

Beyond the average consumer: Mapping the potential of demand-side management among patterns of appliance usage

Claudia Rebeca Binder Signer, Matteo Barsanti, Selin Yilmaz

To support the decarbonisation of the power sector and offset the volatility of a system with high levels of renewables, there is growing interest in residential Demand-Side Management (DSM) solutions. Traditional DSM strategies require consumers to active ...

2024

Federated Reinforcement Learning for Electric Vehicles Charging Control on Distribution Networks

Yuning Jiang, Wei Chen, Xin Liu, Ting Wang

With the growing popularity of electric vehicles (EVs), maintaining power grid stability has become a significant challenge. To address this issue, EV charging control strategies have been developed to manage the switch between vehicle-to-grid (V2G) and gr ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Learning to Remove Cuts in Integer Linear Programming

Volkan Cevher, Grigorios Chrysos, Efstratios Panteleimon Skoulakis

Cutting plane methods are a fundamental approach for solving integer linear programs (ILPs). In each iteration of such methods, additional linear constraints (cuts) are introduced to the constraint set with the aim of excluding the previous fractional opti ...

2024

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Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets

Mohammad Khaja Nazeeruddin

Elsevier Science Sa2024

Koopman-based Data-driven Robust Control of Nonlinear Systems Using Integral Quadratic Constraints

Alireza Karimi, Mert Eyuboglu

2024

Biodiesel from Bark and Black Liquor-A Techno-Economic, Social, and Environmental Assessment

Julia Granacher

MDPI2024

The Effect of Rivers on Energy Balance at the Neighborhood Scale. A comparative analysis of four Rhodanian sites in France and Switzerland

Sergi Aguacil Moreno, Martine Laprise, Sara Sonia Formery Regazzoni, Emmanuel Rey

Wrocław University of Science and Technology Publishing House2024