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As a result of the energy transition, an increasing number of Decentralized Energy Systems (DES) will be installed in the distribution grid in the future. Accordingly, new methods to systematically integrate the growing DES in distribution power systems must be developed utilizing the constantly evolving Information and Communication Technologies (ICT). This paper proposes the Automated Data Model Integration of DES (ADMID) approach for the integration of DES into the ICT environment of the Distribution System Operator (DSO). The proposed ADMID utilizes the data model structure defined by the standard-series IEC 61850 and has been implemented as a Python package. The presented two Use Cases focus on the Supervisory Control and Data Acquisition (SCADA) on the DSO operational level following a four-stage test procedure, while this approach has enormous potential for advanced DSO applications. The test results obtained during simulation or real-time communication to field devices indicate that the utilization of IEC 61850-compliant data models is eligible for the proposed automation approach, and the implemented framework can be a considerable solution for the system integration in future distribution grids with a high share of DES. As a proof-of-concept study, the proposed ADMID approach requires additional development with a focus on the harmonization with the Common Information Model (CIM), which could significantly improve its functional interoperability and help it reach a higher Technology Readiness Level (TRL).

The integration of decentralized renewable energy systems into our distribution networks leads to a need of more detailed information about local network structure and state estimation down to the low voltage level [1]. This enforces the transformation of today’s distribution networks into smart grids. Smart Meters with Smart Meter Gateways (iMSys) and Controllable Local Systems (CLS) are the essential new bricks of the future smart grid. In Germany the new law "Digitalization of the Energiewende"[2] sets up the rules for network operators to establish this secure energy information system based on the smart meter infrastructure.During the last two years the authors developed and demonstrated on laboratory and field level such a secure energy information system. The main innovation of the project is the direct and secure communication with decentralized energy systems such as photovoltaic inverters, battery storage systems, E-mobility charging stations or power to heat applications within this new smart meter infrastructure, which has been defined by technical rules from the German regulator for data security (BSI) [3]. The two-way communication is able to read measurement values from the field as well as change set points or activate curtailment of decentralized energy systems (see figure 1).

Tryptophan metabolites such as kynurenate (KYNA), xanthurenate (XA), and quinolinate are considered to have an important impact on many physiological processes, especially brain function. Many of these metabolites are secreted with the urine. Because organic anion transporters (OATs) facilitate the renal secretion of weak organic acids, we investigated whether the secretion of bioactive tryptophan metabolites is mediated by OAT1 and OAT3, two prominent members of the OAT family. Immunohistochemical analyses of the mouse kidneys revealed the expression of OAT1 to be restricted to the proximal convoluted tubule (representing S1 and S2 segments), whereas OAT3 was detected in almost all parts of the nephron, including macula densa cells. In the mouse brain, OAT1 was found to be expressed in neurons of the cortex cerebri and hippocampus as well as in the ependymal cell layer of the choroid plexus. Six tryptophan metabolites, including the bioactive substances KYNA, XA, and the serotonin metabolite 5-hydroxyindol acetate inhibited [3H] p-aminohippurate (PAH) or 6-carboxyfluorescein (6-CF) uptake by 50–85%, demonstrating that these compounds interact with OAT1 as well as with OAT3. Half-maximal inhibition of mOAT1 occurred at 34 μM KYNA and 15 μM XA, and it occurred at 8 μM KYNA and 11.5 μM XA for mOAT3. Quinolinate showed a slight but significant inhibition of [3H]PAH uptake by mOAT1 and no alteration of 6-CF uptake by mOAT3. [14C]-Glutarate (GA) uptake was examined for both transporters and demonstrated differences in the transport rate for this substrate by a factor of 4. Trans-stimulation experiments with GA revealed that KYNA and XA are substrates for mOAT1. Our results support the idea that OAT1 and OAT3 are involved in the secretion of bioactive tryptophan metabolites from the body. Consequently, they are crucial for the regulation of central nervous system tryptophan metabolite concentration.