Abstract
Power grids are constantly evolving, and data changes are increasing. Operational technology (OT) is controlled by IT technologies in smart grids, where changes in the physical world impose changes in the software data model, as well as the continuous generation of data points, resulting in time series datasets. The increased need for processing large amounts of data combined with requirements to maintain and increase overall performances has created a significant challenge for traditional database solutions and relational database models. The main idea of this paper was to find and propose a graph model that will allow the retrieval of historical connectivity in a reduced time complexity. Furthermore, the research question was addressed by evaluating three different approaches where the results provide a foundation for the proposed design guidelines related to optimizing graph-based databases for a modern smart grid system. The results of the experiments demonstrated reduced time complexities from 3 to 5 times depending on the typical industry usage patterns and the selected graph model. This suggests that the design decision may severely affect the outcome for given smart grid use cases when using historical features in OT technologies. Therefore, the main contribution of the research is the proposed guidelines on how to design an optimal graph model that satisfies the described smart grid requirements.
Highlights
IntroductionPower network grids (the grids ) were designed in the previous century, but the requirements and context of modern cities have forced the grid to evolve, rendering current grids obsolete
With the aim to provide the best approach to reduce the time complexity of retrieving the connectivity in arbitrary historical points, this paper proposes clear guidelines on what graph model type to use based on the smart grid use cases and patterns of database usage
A linked list is generated and exgrid at any time in history consisting of frequent topology changes
Summary
Power network grids (the grids ) were designed in the previous century, but the requirements and context of modern cities have forced the grid to evolve, rendering current grids obsolete. Connectivity in the grids can vary as a consequence of: (1) changes in the state of its elements such as switching the equipment on and off, or (2) physical changes to the grid’s topology such as extending the feeders to new parts of the city or replacing existing equipment. We focused on the first scenario, while the second scenario introduces a much lower rate of changes in the equivalent period. There are about a hundred changes during a day, and during storms (e.g., storm mode), there are about several thousand. Distribution System Operators (DSO) make various analyses as they must have insight into the connectivity of the whole network, both in real-time and to keep a history for training purposes and post-accident analyses
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