Existing electric power distribution systems are evolving and changing as a result of the high renewable energy sources integration. Hence, future smart distribution networks will involve various technical challenges; one of them is real-time monitoring and controlling the network to operate it effectively and efficiently. This paper develops and analyzes a cyber-physical co-simulation testbed for real-time reactive power control in the smart distribution network. The testbed is a two-layer system, with Typhoon HIL 604 representing the physical layer and the other layer as a cybernetic layer. The cybernetic layer is used to model a test system and control reactive power from smart inverters in real-time. The implementation of real-time reactive power control of smart inverters on a CIGRE MV distribution network is shown in this study. The proposed testbed's usefulness in real-time reactive power control is demonstrated through simulation results.@en

Future distribution networks (DN) are subject to rapid load changes and high penetration of variable distributed energy resources (DER). Due to this, the DN operators face several operational challenges, especially voltage violations. Optimal power flow (OPF)-based reactive power control (RPC) from the smart converter (SC) is one of the viable solutions to address such violations. However, sufficient communication and monitoring infrastructures are not available for OPF-based RPC. With the development of the latest information communication technology in SC, cyber-physical co-simulation (CPCS) has been extensively used for real-time monitoring and control. Moreover, deploying OPF-based RPC using CPCS considering the controller design of SC for a realistic DN is still a big challenge. Hence, this paper aims to mitigate voltage violations by using OPF-based RPC in a real-time CPCS framework with multiple SCs in a realistic DN. The OPF-based RPC is achieved by performing the CPCS framework developed in this study. The CIGRE medium-voltage DN is considered as a test system. Real-time optimization and signal processing are achieved by Python-based programs using a model-based toolchain of a real-time DN solver and simulator. Real-time simulation studies showed that the proposed method is capable of handling uncertain voltage violations in real time.@en