Our approach

Our approach


iAMP-Hydro has identified many challenges which must be overcome in order to enable the desired digital transition of existing hydropower plants.
These include specific needs (SN) and challenges on the lack of: 

  • SN1. Reliable and adaptable sensor technology and models for the prediction of operation and maintenance of hydromechanical and electrical equipment; 
  • SN2. Sensors and models for the assessment of the impact of plant operations on environmental, bio-diversity and socio-economic sustainability;
  • SN3. Reliable weather and flow forecasting models for predicting water availability predictions, power production planning, and management of downstream flow impacts;
  • SN4. Standardised secure data collection, communication and sharing protocols to enable trusted open and transparent digital optimization across multiple sensors, and interoperability between hydro operators and other renewable energy plants;
  • SN5. Decision making algorithms which enable data-driven operation and maintenance to increase flexibility, optimize performance in energy markets and increase interoperability with other power sources; and
  • SN6. Evidence for policymaking 

 

In the iAMP-Hydro project, we work on the identified challenges in 11 different work packages, each one dealing with a specific challenge, and working in the consortium to find and realise the solution. Following, you can have a look at our approach:

Condition Monitoring for Hydropower Equipment

Predictive Maintenance Modelling for Hydropower

Ecology Monitoring Sensor Development, Data Analysis & Smart Flow Steering

Flow and available power prediction model development & forecasting

Semantic Interoperability Mechanisms for Hydropower, Energy and Other Relevant Data

End-User Requirements and Architecture Design for the ICT Components of iAMP-Hydro

iAMP-Hydro Platform Implementation

Data Analytics and Hydro Asset Management Platform Development

System Validation in Operating Hydro plants & Case studies



© WIP Munich 2024
This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No 101122167.
This website reflects only the author's view and that the European Commission is not responsible for any use that may be made of the information it contains.


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