Integrating distribution system operator system landscapes

Ascher, Dominik; Bytschkow, Denis

doi:10.1007/s00450-017-0355-6

Cited by 2 publications

(2 citation statements)

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“…Note that, based on the established metamodel, we then derive a general domain model for the domain of distribution system operators, which we described in detail in previous work (Ascher and Bytschkow 2018). Here, a domain model represents a model about the relevant parts of an application domain (Broy 2013).…”

Section: Domain Analysismentioning

confidence: 99%

“…The Common Information Model (CIM) has been recognized as a key element to connect different DSO systems and applications using a standardized data model and enable interoperability for smart grid applications (Hargreaves et al 2014;Ascher and Bytschkow 2018). In that, a substantial challenge consists in bridging the gap between applicationspecific data models and the application-independent CIM data model in order to make data accessible for applications requiring multiple data sources such as power system simulations.…”

Section: Related Workmentioning

confidence: 99%

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Towards model-driven CIM-based data exchange for DSOs

Ascher

Kondzialka

2018

Energy Inform

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Smart energy systems (SES) promote the transformation of the distribution grid towards more sustainable operation and planning strategies, but also impose a set of considerable technological and political challenges. In this, distribution system operators (DSOs) are faced with the necessity of adapting their information system landscapes to enable the efficient utilization of information within their internal structures. In this work, we propose a model-based approach to derive an open middleware platform supporting the integration of existing system landscapes of DSOs. For this, we shortly describe a domain analysis on the DSO domain, which we use to derive the requirements of our platform. The platform is then implemented utilizing the Common Information Model (CIM) and open standards. Finally, we demonstrate the applicability of our approach within a small case study for a single use-case.

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Section: Domain Analysismentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%