Voltage Control Using Optimization-Based Method in a Digital Twin

Recent advancements in the 4.0-technology domain, especially in the fields of Information and Communications Technology (ICT) and Internet of Things (IoT), allow power systems to be supervised and commanded from afar in a more complex and intelligent manner. According to the Smart Grid Architecture Model (SGAM), this is made possible with data exchange by implementing protocols and data models on top of the components layer. Digital twin (DT) – a virtual copy of a physical system – has become a vital tool and more realistic than any simulation models since this technology takes into consideration communication latency for real-time applications. Integrating renewable energy sources, being intermittent in nature while increasing grid’s flexibility, has introduced a voltage-stability threat to the network. For this purpose, the authors showcase a solution to deal with voltage control using artificial-intelligence-based (AI) optimizations. The technique to synchronize and exchange data between the grid and its digital twin is also demonstrated in the process. The proposed method is validated and performed based on a real low-voltage distribution network located in France.