INFRADAPT develops machine learning-based methods for optimal or maximum utilization of existing capacities in low-voltage distribution networks. The impact of climate change on the energy infrastructure and a fair distribution of capacities are considered. The methods are developed and trained for universal use in real time and thus can be used regardless of the network topology. This includes developing and validating (technically and economically) methods for i) optimal placement and sizing of metering infrastructure in low-voltage distribution networks and ii) topology-independent capacity management that allocates available network resources based on metering, AI-based estimation, and AI-based load flow methods.
