Reinpold, Lasse Matthias

The integration of increasing shares of intermittent renewable energy necessitates flexibility in both energy generation and consumption. Typically, the operation of flexible energy resources is orchestrated through optimization models. However, the manual creation of these models is a complex and error-prone task, often requiring the expertise of domain specialists. This work introduces a methodology for the automatic generation of optimization models for systems of flexible energy resources to simplify the modeling process and increase the use of energy flexibility. This methodology utilizes a modular, generic model structure designed to depict systems of flexible energy resources. It incorporates algorithms for model parameter derivation from operational data and an information model that represents the system’s structure and dependencies of resources. The efficacy of this methodology is demonstrated in two case studies, highlighting its relevance and ability to significantly streamline the optimization modeling process by minimizing the need for manual intervention.

Die rasche Expansion erneuerbarer Energiequellen führt zu erheblicher Volatilität und Unvorhersehbarkeit in der Energieversorgungskette, was die Stabilität und Zuverlässigkeit des Stromnetzes herausfordert. Diese Arbeit präsentiert daher eine Methode, die bestehende statische Optimierungsmodelle flexibler Energiequellen echtzeitfähig macht und damit ermöglicht, dass diese sowohl für die mittelfristige Planung als auch für Echtzeitanwendungen eingesetzt werden können. Durch die Anpassung statischer Modelle für die Echtzeitanwendung ermöglicht eine in diesem Beitrag vorgeschlagene zweistufige Optimierungsstrategie flexible Anpassungen von Betriebsplänen, wodurch erneuerbare Energien auch trotz unvorhergesehener Schwankungen bestmöglich genutzt werden können. Dieser Ansatz gewährleistet nicht nur die Zuverlässigkeit des Netzes, sondern verbessert auch die wirtschaftliche Effizienz durch die Optimierung der Ressourcennutzung. Die Wirksamkeit dieser Methode wird durch eine Fallstudie mit einem System von Elektrolyseuren demonstriert, die deutliche Vorteile gegenüber traditionellen statischen Optimierungsmethoden bei der Ausrichtung des Energieverbrauchs auf die Erzeugung erneuerbarer Energie aufzeigt.

Due to increasing amounts of energy being supplied by intermittent renewable energy sources, future energy systems need to be able to react flexibly to sudden changes. To address this challenge, a large body of research is devoted to improving the utilization of energy flexibility of various types of energy resources on the supply and demand side. This is commonly done by applying mathematical models. The objective of this paper is to review such models and identify common modeling approaches used to quantify and optimize the use of flexible energy resources. The literature review is conducted systematically, encompassing 215 publications that feature 694 models of different energy resources. The main distinction of this work, in comparison to other reviews on the topic of energy flexibility lies in its focus on the mathematical formulation of models of energy resources and the quantification of the models’ level of detail. The aim is to identify common modeling approaches and the corresponding research problems they address. The review shows that the majority of research efforts are directed towards the management and optimization of distributed energy resources. The most commonly employed modeling approach involves abstract black-box models with limited levels of detail. Linear programming and meta-heuristics are frequently used to optimize energy flexibility. A critical reflection of the current common practice is conducted and recommendations for future research are formulated