of voltage and current measurement data from sensor networks already installed in power grids. To develop and validate methods to identify unreliable measurement data points in real-time, for example, detection of invalid data caused by sensor malfunction. Methods will include comparing grid data to a trained machine-learning profile based on reliable datasets.
to complement the use of real data for comprehensive validation and optimisation of grid data analysis methods. To determine the grid model parameters such as impedance and grid inertia from real grid measurement data and implement digital twins of real grids for the simulation of a range of possible grid scenarios and measurement conditions. To use software-based simulation models and laboratory-based grid simulators to generate test datasets for the general testing of grid data analysis methods.
data analysis methods, including AI techniques, for the early detection of abnormal grid events such as frequency deviations, sub-synchronous oscillations, power quality disturbances, and grid asset faults. To quantify the robustness and reliability of methods using existing grid measurement data as well as the test datasets generated in Objective 2 by determining the uncertainty of the probability of the predicted events.
data analysis methods, including AI techniques, for forecasting grid congestion and system imbalance between supply and demand, including the use of other data, such as weather predictions and temperature measurements of cables and lines. To quantify the robustness and reliability of methods using existing grid measurement data and the test datasets generated in Objective 2 by determining the uncertainty of the forecasts. To provide Good Practice Guides on the validation of data-driven grid applications.
of the technology and measurement infrastructure developed in the project by the measurement supply chain (NMIs, DIs, research laboratories), standards developing organisations (IEEE, IEC/ISO SMART) and end users (grid operators, stakeholders of the European Metrology Network on Smart Electricity Grids).