INFUSE

Information Fusion of Multi-Vector Real-Time Data Streams for Energy Management in Emerging Power Grids

01

Overarching goal

Achieving an optimal energy transfer in emerging, inertialess grids, with high share of RESbased energy sources

02

Goals

Edge-computing boosting grid intelligence for managing distributed generation and high RES.

A software tool to optimize MV grid operations using PMU data for state estimation.

04

Objectives

Develop multi-vector, heterogeneous sources data integration framework

Implement correlation and data analytics computing

Implement a hybrid state estimator for distribution network operators

Integration of real-time digital simulation tools and live demonstration in campus grid

INFUSE Demonstrators

Trial Sites

Trail Sites in Romania

Romanian partners (ICPE-CA and UPB) will contribute with their high expertise and infrastructure which supports a wide range of renewable energy sources applications, products, services and technical consultancy on PV modules, BIPV, Smart Grids, wind and hydropower, operation and maintenance. In addition, the coordinator will enable the adoption of Fiware platform philosophy and extend its use cases for HIL simulation (Typhoon) implementing and testing the capabilities of the digital twins for various scenarios

Trail Sites in Czech Republic

Czech Republic partners (BUT and ELVAC) will use the hybrid (PMUbased) state estimators for network reconfiguration in various scenarios (ensuring maximal energy transfer, minimal impact on energy users, lower stress on installations etc.) In addition for control and design optimization algorithm for distributed assets, a SW tool will be developed to use data from distributed PMUs at MV level system, integrated in the same cloud-platform for analysis, control, data transfer, GUI and validation with the DSO for the interconnection of two fed areas.

Key Topics

Enhancing grid intelligence

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.

Multi-vector heterogeneous sources data integration

Robust data integration and exchange framework within a software cross-platform using a standard format

Correlation and data analytics computing

Intelligent data analytics engine that can process and correlate information from various sources (energy transfer parameters, environmental and contextual conditions)

Hybrid state estimators

Data integration module capable of seamlessly integrating PMU data with very high-reporting rates

Real-time digital simulation tools

Integration mechanism of heterogeneous data with real-time (heterogenous) digital simulation tools

Optimization of the MV distribution grid operation

Intelligent data analytics engine that can process and correlate information from various sources (energy transfer parameters, environmental and contextual conditions)

Consortium Partners

This project has received funding in the framework of the European Joint Programming Platform ERA-Net Smart Energy Systems (JPP ERA-Net SES) in collaboration with the global Mission Innovation Initiative under the Joint Call 2023 on digital transformation for green energy transition, co-funded by the European Commission and with the funding organizations below.
Supported by the Romanian National Authority for Scientific Research and Innovation
Supported by the Technology Agency of the Czech Republic
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