A hybrid storage plant XS is the heart of a smart grid. The control station fulfills all control and regulation tasks that will arise in the future from a modern decentralized energy infrastructure. The most important task is to ensure security of supply in the grid for all forms of energy and to control sector balancing in order to optimize the efficiency and cost-effectiveness of the overall system.
In terms of its functionality, it largely takes over the automated implementation of an energy management system according to ISO 50001.
The project approach arises from the question of how to organize an energy exchange between the individual storage solutions and the generators, some of which are intermittent, in order to realize the lowest possible losses, high availability and good controllability. The challenge here is how and whether it is possible to connect the operating points of different storage technologies in such a way that several business models can be technically realized simultaneously. The hybrid storage plant should provide energy in a smart grid in any form and additional capacities for other energy services, such as merit-order trading or electric mobility.
The basis for efficient control processes in a hybrid storage plant is a high data density from consumptions, environmental influences, and possible generation capacities. The application of neural networks makes it possible to build an intelligent, self-learning system, to work out optimal control processes and to guarantee a predictive mode of operation.
As a result, automated parameter control is to be implemented.
The technical realization of the control station, as it will be implemented in the project, will make it possible to provide reliable consumption data to the operators of higher-level distribution networks with a very low error rate. This will be an essential prerequisite for a new energy model.
Convia GmbH, G.f.S. e.V., Digitale Haustechnik GmbH, Mecklenburgischer Energie und Anlagenbau GmbH
Universität Zielona Gora; u.w.