at Google ScholarTitle data
Weber, Thomas ; Schel, Daniel ; Schott, Paul ; Bauer, Dennis ; Pullmann, Jaroslav ; Abele, Eberhard ; Bauernhansl, Thomas ; Fridgen, Gilbert ; Jarke, Matthias:
Generic Data Model for Describing Real-Time Data-Supported Power Flexibility.
2018
Event: SmartER Europe
, 08.02.2018
, Essen.
(Conference item: Conference
,
Paper
)
Project information
| Project title: |
Project's official title Project's id Projektgruppe WI Nachhaltiges Energiemanagement & Mobilität No information |
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Abstract in another language
In the course of the German Energiewende, the share of controllable power generation is decreasing, while renewable, volatile generation resources (wind turbines and pho-tovoltaics), are being expanded. Therefore, the need for flexibility on the consumer side to compensate for this volatile generation is growing, because the balance of power production and power consumption needs to be guaranteed [1]. The German industrial sector consumes the largest share by 43.7 % of electricity [2] and also holds enormous potential for load flexibility in Germany [3]. However, many potentials cannot be ex-ploited because the necessary information technology connections are missing. The ge-neric data structure presented in this paper offers an approach to describe power flexi-bility potentials in a standardized way for a prevailing situation. This state-dependent flexibility potential can thus be made available to a higher-level instance for optimizing the operation strategy. As digitization progresses, the degree of automation increases, and so does the flexibility potential of the system. To this end, the basic characteristics of flexibility are first of all worked out and the corresponding degrees of freedom are explained in more detail. The existing approaches for describing flexibility of conven-tional power plants, such as the transmission code [4], will also be discussed. There are two classes of power flexibility - time-restricted and time-independent flexibility. Sep-arate sets of flexibility indicators are created for both classes, which are then transferred to a data structure. Finally, an information architecture to process the data model is presented.