intelligent Asset Management Platform for HYDROpower operation & maintenance (iAMP-Hydro)
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Project Team:
Principle Investigators:
- Aonghus McNabola, (Trinity College Dublin)
- Biswajit Basu (Trinity College Dublin)
- Paul Coughlan (Trinity College Dublin)
Collaborators:
- Easy Hydro Ltd, SME, Ireland
- Cuerva, Hydro operator, Spain
- Suite5, SME, Cyprus
- CARTIF, Research Institute, Spain
- EDP, Hydro operator, Spain
- PPC Renewables, Hydro operator, Greece
- WIP, SME, Germany
- Norce, Research Institute, Norway
- University Politehnica of Bucharest, University, Romania
Trinity Researchers:
- Maciej Janiszkiewcz (PhD Researcher)
- Bhaskar Paudel (PhD Research)
- Israel Ohiemi (Postdoctoral Fellow)
Website:
Under construction
Funding Agency:
Location:
Spain, Greece, Ireland, Romania, Germany, Norway
Themes:
Renewable Energy, AI, IoT, Hydropower
Description:
iAMP-Hydro is a collaborative research effort of 10 parties coming from a wide field of academia and industry. Its target is to build digital solutions that will improve the efficiency, flexibility and sustainability of the existing EU hydropower fleet. The project has the potential to make a huge impact on energy sustainability in the EU, where 50% of the current hydro generation assets may require upgrading by 2030. This research aims to develop iAMP - a novel intelligent Asset Management Platform encompassing secure open and transparent data sharing protocols and three novel digital solutions:
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- Condition monitoring and predictive maintenance modelling based on IoT sensors for electromechanical equipment using vibration, temperature, acoustic and electrical data.
- Ecological status monitoring and water management, improving biodiversity and environmental and socio-economic sustainability of existing plants.
- Improved weather and flow forecasting applying operational data from power plants and open source data in differing climates, with differing power capacities and flow regimes achieving significant improvement in reservoir inflow, outflow and water balance prediction accuracy.
- The full package of digital solutions will be validated at five real-world existing hydropower plants producing evidence for policy making to support the green and digital transition of hydro.
