The transition of classical power distribution grids towards actively operated smart grids locates new functionality into intelligent secondary substations. Increased computational power and newly attained communication infrastructure in thousands of secondary substations allow for the distributed realization of sophisticated functions, which were inconceivable a few years ago. These novel functions (e.g., voltage and reactive power control, distributed generation optimization or decentralized market interaction) can primarily be realized by software components operated on powerful automation devices located on secondary substation level. is crucial and has a broad set of requirements. In this paper, we present a flexible and modular software ecosystem for automation devices of substations, which is able to handle these requirements. This ecosystem contains means for high performance data exchange and unification, automatic application provisioning and configuration functions, dependency management, and others. The application of the ecosystem is demonstrated in the context of a field operation example, which has been developed within an Austrian smart grid research project.
With the increase of the volume of data produced by IoT devices, there is a growing demand of applications capable of elaborating data anywhere along the IoT-to-Cloud path (Edge/Fog). In industrial environments, strict real-time constraints require computation to run as close to the data origin as possible (e.g., IoT Gateway or Edge nodes), whilst batch-wise tasks such as Big Data analytics and Machine Learning model training are advised to run on the Cloud, where computing resources are abundant. The H2020 IoTwins project leverages the digital twin concept to implement virtual representation of physical assets (e.g., machine parts, machines, production/control processes) and deliver a software platform that will help enterprises, and in particular SMEs, to build highly innovative, AI-based services that exploit the potential of IoT/Edge/Cloud computing paradigms. In this paper, we discuss the design principles of the IoTwins reference architecture, delving into technical details of its components and offered functionalities, and propose an exemplary software implementation.
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