Abstract
This paper describes a methodology for optimizing the operation schedule of energy plants, which is exemplarily applied for a combined heat and power plant and a heat pump. The methodology is based on the computational intelligence algorithms Ant Colony Optimization and Simulated Annealing and allows a customized description of the optimization objective. This is demonstrated by several optimization objectives that have been considered, such as the price on the electricity market. The methodology replaces a conventional, guided operating mode of the system with an intelligent, prognostic-based operation planning. In this way, the systems can be operated more economically and/or more sustainably.
Zusammenfassung
Der Beitrag beschreibt eine Methodik zur Optimierung des Betriebsablaufs von Energieanlagen, welche exemplarisch für ein Blockheizkraftwerk und eine Wärmepumpe umgesetzt wird. Die Methodik basiert auf den Algorithmen Ant Colony Optimization und Simulated Annealing und ermöglicht eine individuelle Beschreibung der Optimierungsziele. Dies belegen mehrere betrachtete Optimierungsziele, wie z. B. der Preis auf dem Strommarkt. Die Methodik ersetzt eine konventionelle, geführte Betriebsweise der Anlage durch eine intelligente, prognosebasierte Betriebsplanung. Auf diese Weise können die Anlagen wirtschaftlicher und/oder nachhaltiger betrieben werden.
Funding source: Bundesministerium für Bildung und Forschung
Award Identifier / Grant number: 13FH757IX6
Funding statement: This work was partially funded by the Federal Ministry of Education and Research (BMBF) under the project number 13FH757IX6 and by the Federal Ministry of Economic Affairs and Energy (BMWi) under the project number 03ET7530.
About the authors
Johannes Mast received the M.Eng degree in Systems Engineering in 2017 from the Albstadt-Sigmaringen University, after having previously completed his Bachelor of Engineering in Computer Engineering. He is currently working as a research assistant in the funded research project in the field of energy technology and is Ph. D. student in Computer Science at the University of Tübingen.
Stefan Rädle received the M.Eng degree in Systems Engineering in 2018 from the Albstadt-Sigmaringen University, after having previously completed his Bachelor of Engineering in Computer Engineering. He is currently working as a research assistant in the funded research project in the field of energy technology and is Ph. D. student in Computer Science at the University of Tübingen.
Joachim Gerlach graduated from the Technical University of Karlsruhe in 1995 with a diploma in computer science and received his Ph. D. in digital circuit and system design from the Department of Computer Engineering at the University of Tübingen in 2000. From 2002 to 2009, he worked with Robert Bosch GmbH, Automotive Electronics Division, in the field of semiconductor development. Since 2009, Joachim Gerlach is professor at the Faculty of Computer Science at Albstadt-Sigmaringen University.
Oliver Bringmann is Professor for Embedded Systems at the University of Tübingen, Germany and is serving as deputy head of the Department of Computer Science. He studied computer science at the University of Karlsruhe (KIT) and received the doctoral degree (PhD) in computer science from the University of Tübingen in 2001. Until April 2012 he was division manager of the research division Intelligent Systems and Production Engineering (ISPE) and member of the management board at FZI Karlsruhe. He is the author and co-author of more than 200 publications in the area of electronic design automation (EDA), embedded system design, performance, power and thermal analysis, embedded many-core architectures, energy-efficient AI architectures, and verification of cyber-physical systems.
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