At the Institute of Climate and Energy Systems – Energy Systems Engineering (ICE-1), we develop advanced models, algorithms, and control solutions for simulating, optimizing, and operating future integrated energy systems. We address the challenges arising from the increasing integration of renewable energy, sector coupling, decentralization, and growing energy infrastructure complexity. The Control Solutions department develops methods and algorithms for controlling energy systems and their components. We focus on application-oriented methods that can operate in real time and are suitable for operating decentralized systems. We aim to enable the reliable, cost-efficient, resilient, and sustainable operation of future energy networks by combining our knowledge of energy systems with cutting-edge developments in machine learning, and digital infrastructures.
The Einstein Telescope is a next-generation research infrastructure currently in development, featuring a large-scale computing center whose energy demands present a unique opportunity: to develop climate-neutral operations through the integration of renewable energy sources and hybrid storage systems. As part of an EU-funded research project, ICE-1 is collaborating with research groups and companies to address the challenge of designing and operating the Einstein Telescope's computing center in a sustainable and energy-efficient manner. The project's main goal is to develop and validate an innovative, scalable energy concept in which the computing infrastructure and energy system are tightly coupled and jointly optimized. During the project, a container-scale prototype will be realized, which will combine a fully operational computing stack with a flexible, renewable-based energy system incorporating both battery and hydrogen storage. Alongside the physical prototype, a comprehensive co-simulation environment will be developed using hardware-in-the-loop components, enabling realistic scale-up to a full computing center and systematic evaluation of advanced operating strategies. Specifically, the PhD candidate will be involved in the development of model predictive control to operate the energy system and IT load largely self-sufficiently under varying weather conditions, with particular focus on the role of battery and hydrogen storage during Dunkelflaute periods. The developed algorithm will be first test in the hardware-in-the-loop environment developed together with the other partners. After that, the same algorithm will be tested on the real container-scale prototype.
Your tasks within framework in detail:
In addition to exciting tasks and a collegial working environment, we offer you much more.
We welcome applications from people with diverse backgrounds, e.g. in terms of age, gender, disability, sexual orientation / identity, and social, ethnic and religious origin. A diverse and inclusive working environment with equal opportunities in which everyone can realize their potential is important to us.
The following links provide further information on diversity and equal opportunities: and on specific support options:
Place of Employment: Jülich Start Date: To the next possible date Salary: Pay group 13 (75%) TVöD-Bund Application Deadline: The position will be advertised until it is successfully filled.
Tagged as: Life Sciences
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