Key Topics
INFUSE overarching goal is achieving an optimal energy transfer in emerging, inertialess grids, with high share of RESbased energy sources. Planned for 24 months with a small consortium (5 partners and one observer, from three EU countries), the project addresses multiple topics.
Enhancing grid intelligence
Enhancing grid intelligence as a way to successfully transform the operation of emerging power systems by including
local information processing (edge-computing) in the context of distributed generation and high-penetration of RES.
Optimization of the MV distribution grid
Optimization of the MV distribution grid operation by design and validation of a software tool able to process data
streams from synchronized measurements (PMUs) with further input to hybrid state estimators
Implement correlation and data analytics computing
Develop an intelligent data analytics engine that can process and correlate information from various sources (energy transfer parameters, environmental and contextual conditions). Develop and adapt data analytics algorithms to extract meaningful insights from the integrated information, enabling real-time anomaly detection, predictive maintenance, and energy control.
Develop multi-vector, heterogeneous sources data integration framework
Create a robust data integration and exchange framework within a software cross-platform using a standard format capable of handling multi-vector measurement information, including power profiles with a high-reporting rate (1 frame/s) and environmental conditions data from sensors with a time resolution of 1s or lower.
Implement a hybrid state estimator for distribution network operators
Develop a data integration module capable of seamlessly integrating PMU data with very high-reporting rates (50 frames /s) in the same open-source platform using the common format. Ensure the synchronization and real-time availability of PMU data for grid monitoring and control purposes by implementing a hybrid state estimation system that combines PMU data and smart meter data (mixed reporting rates).
Integration of real-time digital simulation tools and live demonstration in campus grid
Establish an integration mechanism of heterogeneous data with real-time (heterogenous) digital simulation tools for modelling and simulation of energy transfer in emerging power grids.