Although the increase of distributed and often renewable energy sources makes sense from an environmental perspective, this new paradigm poses significant challenges to distribution grids, which were not initially designed for bidirectional power flow. The distribution system operators must expand their grids or develop intelligent control algorithms. Considering these challenges, this thesis proposes control algorithms for real-time control of the various flexibilities using distributed measurements to prevent voltage and thermal violations. The control algorithms are configured using IEC 61850 data models, which were not done in previous research, and applied to a selected research prototype. Such an implementation provides the advantage of modularity by separating the hardware and software, which essentially makes the software easily portable. This thesis also proposes countermeasures to mitigate such failures and make the algorithms more robust by implementing hierarchical control strategies and using data-based learning methods. The implemented algorithms are experimentally verified using a real-time simulator and an analogue grid model in the laboratory. In order to analyse the effectiveness of the implemented algorithms, they are experimentally verified in various benchmark grids. To demonstrate the applicability and versatility of the algorithms, they are applied on international grids. The results of the hardware-in-the-loop simulations and the laboratory test show that the implemented algorithms could support the distribution grid operation by providing voltage control using real-time control of the flexibilities. The implemented algorithms could be validated in reality when the local grid policies allow real-time control of the distributed energy resources.weiterlesen