Editorial Model Predictive Control for Energy Systems: Economic and Distributed Approaches

In view of the growing discussion around climate change, emission targets, and emission taxation, there is widespread scientific consensus about the need for decarbonization and defossilization of energy supply. These necessities are closely related with the demand for efficient management and opera...

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Autores principales: Ferramosca, Antonio, Faulwasser, Timm
Formato: Artículo publisherVersion
Lenguaje:Inglés
Publicado: 2021
Materias:
Energy Systems; Economic; Distributed Approaches
Acceso en línea:http://hdl.handle.net/20.500.12272/4922
https://doi.org/10.1002/oca.2573
Aporte de:
RIA - Repositorio Institucional Abierto (UTN) de Universidad Tecnológica Nacional
id I68-R174-20.500.12272-4922
record_format dspace
institution Universidad Tecnológica Nacional
institution_str I-68
repository_str R-174
collection RIA - Repositorio Institucional Abierto (UTN)
language Inglés
topic Energy Systems; Economic; Distributed Approaches
spellingShingle Energy Systems; Economic; Distributed Approaches
Ferramosca, Antonio
Faulwasser, Timm
Editorial Model Predictive Control for Energy Systems: Economic and Distributed Approaches
topic_facet Energy Systems; Economic; Distributed Approaches
description In view of the growing discussion around climate change, emission targets, and emission taxation, there is widespread scientific consensus about the need for decarbonization and defossilization of energy supply. These necessities are closely related with the demand for efficient management and operation of energy systems. The corresponding technological and scientific challenges cannot be mastered without progress on tailored methods for control and automation of sector‐coupled energy systems, that is, systems comprising electricity and other forms of energy such as heat, cold, gas, and so on. Among the manifold advanced control methods at hand, model predictive control (MPC) stands out due to its proven applicability on industrial scale and due to its ability to effectively handle system constraints, forecast information, and performance criteria. In this light, the present special issue collects 12 original research articles on MPC for energy systems, whereby special focus is put on economic and distributed approaches. The first group of articles in this special issue puts focus on method development. These articles investigate different aspects of economic and noneconomic MPC ranging from the use of barrier functions, performance, and stability results for time‐varying settings via tracking in a stochastic formulation to distributed schemes relying on dual composition.1-4 The second group of articles considers the application of MPC to problems arising in electrical power systems such as multiperiod power flow problems, smart grids, and induction motors.5-9 Finally, the third group of articles discusses application‐oriented settings, which share the common attribute of sector coupling, that is, they include elements of coupling different energy forms and the corresponding sectors.10-12 Naturally, this special issue merely provides a snapshot of the manifold and concurrent research activities on tailored predictive control methods for multienergy systems. Yet, it is also a strong indicator that economic and distributed MPC approaches will continue to play a pivotal role in the years to come.
format Artículo
publisherVersion
author Ferramosca, Antonio
Faulwasser, Timm
author_facet Ferramosca, Antonio
Faulwasser, Timm
author_sort Ferramosca, Antonio
title Editorial Model Predictive Control for Energy Systems: Economic and Distributed Approaches
title_short Editorial Model Predictive Control for Energy Systems: Economic and Distributed Approaches
title_full Editorial Model Predictive Control for Energy Systems: Economic and Distributed Approaches
title_fullStr Editorial Model Predictive Control for Energy Systems: Economic and Distributed Approaches
title_full_unstemmed Editorial Model Predictive Control for Energy Systems: Economic and Distributed Approaches
title_sort editorial model predictive control for energy systems: economic and distributed approaches
publishDate 2021
url http://hdl.handle.net/20.500.12272/4922
https://doi.org/10.1002/oca.2573
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