Predictions and decision based on complexly interacting variables are omnipresent in energy, finance and logistics. When using mathematical models to describe such systems, often similar structures are employed like graphs, decision trees or differential equations. Solving these models requires optimisation algorithms or computationally expensive simulations.
Within the Josef Ressel Centre we work together with the following Industry partners: Hypo Vorarlberg Bank AG, myPEX, Vorarlberger Kraftwerke AG und Vorarlberger Landesversicherung. Former Partners are: infeo und Gebrüder Weiss.
To bring together corresponding experts from the different fields of application, researchers from the Research Centre Energy as well as the Research Centre Process and Product-Engineering worked together in the Josef Ressel Centre. The following is merely an overview of the work of the subproject Energy Model Library. Further information on the other work areas and all centre staff can be found on the project page at www.fhv.at/en/research/energy/josef-ressel-centre-for-applied-scientific-computing/.
Electrical energy supply and the energy economy are facing massive changes: digitalization on the one hand and the liberalization of the energy markets and the progressive expansion of renewable energy generation in Europe on the other. These transitions promote and require the development of new technologies and business models. In the course of this development, Demand Side Management (DSM) has been attracting rapidly growing interest since the 2010s. The problem of adapting consumption to generation was first formulated in the 1970s. The wealth of possible concepts in response to this is summarized under the term DSM. DSM includes a variety of technical and economic control mechanisms, from permanent energy efficiency measures such as equipment replacement, through time-variable energy tariffs, to control and regulation concepts for energy storage systems.
Researchers of the subproject Energy Model Library focused on the development of autonomous algorithms for decentralized energy storage systems. The approach pursued here is known as autonomous DSM (ADSM). Based on an incentive function, the storage management is optimized decentralized by autonomous devices. The approach served as the basis for a large number of rich scientific topics and questions that have been dealt with.
Electric hot water storage tanks have a decade-long history as a shiftable load. Due to the classic night operation, the capacity to performance ratio has developed in such a way that they are very well suited for load shifting during the day. They provided the blueprint for the development of the method, which was later transferred to electrochemical storage. Within the framework of the Ressel Centre, Peter Kepplinger finished his dissertation about ADSM with electrically operated hot water storage tanks. This deals in particular with the possibility of estimating the current system status using measurement technology and computing capacities that are as reduced as possible. This makes it possible to retrofit the storage tank for optimum deployment planning using ADSM.
Due to their rapidly increasing use (also due to electromobility), stationary battery storage systems represent a great future potential for DSM. In the context of Bernhard Fäßler's dissertation, ADSM stationary battery storage was investigated as a 2nd use case for batteries from electric vehicles that are no longer used. Algorithms for autonomous optimization based on real-time market prices were developed and implemented on a real test system in cooperation with Vorarlberger Kraftwerke AG (VKW).
In order to investigate the effects of the autonomous algorithms on the electrical low-voltage networks, a grid simulation software was developed as part of a master thesis. Special attention was paid to the parallelizability via the Distributed Execution Framework (DEF) developed at the Josef Ressel Center. The network simulation made it possible to examine the benefits of autonomously managed stationary storage systems in the network. The results were able to show the enormous disadvantages of autonomous systems reacting to unfavorable incentives. For example, supra-regional prices could be identified as disadvantageous for the network infrastructure.
This result was also confirmed for the specific case of charge load management of electric vehicles via ADSM. It led to the research question of more suitable incentive functions for incentivizing the operation of autonomous energy storage systems. As a possible alternative to cost minimization, power signal tracking by utilizing storage flexibility was investigated. The advantage of this approach compared to cost optimization lies in the full exploitation of the flexibility available. Despite the improved controllability of the autonomous loads, the decentralized optimization problem to be solved remains linear, and, thus can be implemented techno-economically on site.
Overall, the work has shown that ADSM as a concept can offer a medium-term solution for the integration of decentralized energy storage systems for consumer flexibility on the way to the Smart Grid. The resulting work was summarized in a scientific overview article (Kepplinger, P., Fässler, B., Huber, G. et al. Autonomous demand side management of distributed energy storage systems. Electrotech. Inftech. 137, 52-58 (2020). doi.org/10.1007/s00502-019-00782-9).
The project duration was 5 years, from 01.01.2015 to 31.12.2019.
Josef Ressel Centres are 5-year research projects which are jointly funded by the Federal Ministry Republic of Austria Digital and Economic Affairs (BMWD) and industrial partners. The Christian Doppler Forschungsgesellschaft has the coordination for this Public Private Partnership.