부산대학교 도서관

Power system operation is gaining complexity due to the changes imposed by the energy transition. Especially, the increased share of intermittent and decentralized renewable generation units in the energy mix, an increased uncertainty regarding the supply of energy, and the predominantly market-driven cross-region and cross-border transport of electricity impose new challenges on the operation of power systems in Europe. In particular, power system operators must facilitate higher utilization of the grid capacity and coordinate more with neighboring transmission system operators (TSOs) and distribution system operators (DSOs). To deal with these new challenges, there is a pressing need to improve the observability and controllability of key system parameters to safeguard the reliability of power systems. Furthermore, the aforementioned developments and challenges go hand in hand with the need to improve the system resilience from the cybersecurity and system stability points of view. In the future, these challenges cannot be met without innovation towards intelligent decision support systems and assistant functions, which allow a look ahead combined with fast response and proactive actions. Here, the rather novel digital twin (DT) concept in combination with data-driven (i.e., machine learning) applications can be purposefully applied.