Test Beds for Component Integration in Energy Systems

Becker, Birger; Kochanneck, Sebastian; Schmeck, Hartmut

doi:10.1109/fas-w.2019.00023

Cited by 3 publications

(1 citation statement)

References 10 publications

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“…e) Test: System self-integration poses particular testing and assessment challenges. Testbeds for cyber-physical systems [77], UAVs [78] and Smart Grids [79] have been introduced that are mainly domain-dependent. More generalpurpose approaches are limited to bio-inspired high performance computing simulation [80] for self-building embedded systems as well as conceptual architectures [49,81].…”

Section: System Aspectsmentioning

confidence: 99%

Self-improving system integration: Mastering continuous change

Bellman

Botev

Diaconescu

et al. 2021

Future Generation Computer Systems

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Section: System Aspectsmentioning

confidence: 99%

Self-improving system integration: Mastering continuous change

Bellman

Botev

Diaconescu

et al. 2021

Future Generation Computer Systems

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Test and optimization of a control algorithm for demand-oriented operation of CHP units using hardware-in-the-loop

Haase

Thomas

2021

Applied Energy

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Development of control systems that operate independently without human intervention

Venugopal

2022

JIC

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The development of control systems that operate independently without human intervention is a rapidly growing field in instrumentation and control engineering. These systems are designed to function autonomously, using Artificial Intelligence (AI) and Machine Learning (ML) techniques to make decisions and perform tasks. Applications of these systems can be found in a variety of fields, including autonomous vehicles, robotics, and industrial automation. The key benefits of these systems are their ability to perform tasks without human intervention, which can lead to increased efficiency and productivity. They also have the ability to operate in environments that may be too dangerous for humans, such as deep-sea exploration or space. Additionally, they are able to collect and process large amounts of data in realtime, which can be used to improve decision-making and control. This includes the use of machine learning and evolutionary algorithms to improve the ability of systems to adapt to changing conditions. This research is also focused on the integration of these systems with communication networks, such as the internet, to enable remote monitoring and control. With advancements in technology and increasing demand for automation, it is expected that autonomous systems will play an increasingly important role in various industries in the future.

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Test Beds for Component Integration in Energy Systems

Cited by 3 publications

References 10 publications

Self-improving system integration: Mastering continuous change

Self-improving system integration: Mastering continuous change

Test and optimization of a control algorithm for demand-oriented operation of CHP units using hardware-in-the-loop

Development of control systems that operate independently without human intervention

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