For most power grid operators, it is challenging to have an accurate and up to date overview of the condition of their grid, equipment, and power lines. In fault situations and for preventive and corrective maintenance of power grid infrastructure, power grid companies have traditionally relied on manual ground based inspections (crews walking the lines and inspecting transformer substation) and helicopter based inspections. This industry PhD project aims at investigating the use of the new generation of information technologies based on big data, machine learning, and real-time processing, to develop advanced tools for dynamic analysis of risks related to smart-grids in large-scale interconnected power systems.
Project leader: Davide Roverso
Institution: ESMART SYSTEMS AS