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. The effective and safe operation of such software 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.

This paper presents control relationships between the low voltage distribution grid and flexibilities in a peer-to-peer local energy community using a stratified control strategy. With the increase in a diverse set of distributed energy resources and the next generation of loads such as electric storage, vehicles and heat pumps, it is paramount to maintain them optimally to guarantee grid security and supply continuity. Local energy communities are being introduced and gaining traction in recent years to drive the local production, distribution, consumption and trading of energy. The control scheme presented in this paper involves a stratified controller with grid and flexibility layers. The grid controller consists of a three-phase unbalanced optimal power flow using the holomorphic embedding load flow method wrapped around a genetic algorithm and various flexibility controllers, using three-phase unbalanced model predictive control. The control scheme generates active and reactive power set-points at points of common couplings where flexibilities are connected. The grid controller’s optimal power flow can introduce additional grid support functionalities to further increase grid stability. Flexibility controllers are recommended to actively track the obtained set-points from the grid controller, to ensure system-level optimization. Blockchain enables this control scheme by providing appropriate data exchange between the layers. This scheme is applied to a real low voltage rural grid in Austria, and the result analysis is presented.

Digitalisation enables the clean energy transition but introduces fragmentation across platforms, protocols, and standards. The PARMENIDES project addresses these challenges by introducing EMS4HESS – an ontology-based Energy Management System for Hybrid Energy Storage Systems within Renewable Energy Communities. EMS4HESS leverages the PARMENI-DES Energy Community Ontology (PECO) to ensure semantic interoperability across data models and information layers. PECO describes community structures, asset properties, optimisation strategies, and flexibility signals, enabling automated reasoning and adaptive control. The system integrates diverse storage technologies and optimises their operation to improve resilience and sustainability. Real-world pilots in Austria and Sweden validate the approach under contrasting regulatory frameworks. Initial results show significant improvements in self-sufficiency and self-consumption compared to baseline scenarios without HESS, confirming the feasibility of ontology-driven, grid-aware energy management as a scalable solution for the clean energy transition.