Unlocking automated self-healing procedures to handle faults and outages in the distribution grid requires optimising the use of available measurement data in support of decision-making and defining requirements and priorities for the digitalisation and automation of the distribution grid. To overcome these challenges, the DSO Avacon of the E.ON Group collaborated with the Fraunhofer IEE Institute to develop a modular self-healing system.
Thanks to an innovative approach based on artificial intelligence, the developed software offers independent modules for state estimation, fault location and isolation and optimal grid reconfiguration with different levels of automation. The solution was validated with real grid and measurement data, and the achievable benefits in terms of grid operation, planning and decision-making support were proven even in the case of grid areas over which the system operator has limited visibility.
