WP1-Digital transformation tools for HP O&M
- Carried out state-of-the-art research to define “what does digitisation of hydropower mean?”, what technological trends are involved and provide industry examples available in literature.
- Developed requirements and detailed descriptions of the Di-Hydro use cases were delivered (PPC- Greece, A2A-Italy, EPS-Serbia).
- Collected historical data regarding Operation & Maintenance, weather/flow, biodiversity, environmental and socio-economic data from the participant HPPs.
WP2-Innovative sensor technologies for HP digitalization
-The following type of sensors were developed that will be used in Di-Hydro project: a) Structural health and condition monitoring sensor node containing sensors for: acoustic emission, vibrations, temperature & humidity, magnetic flux and crack growth. b) Real-time environmental monitoring sensor for measuring: E coli, ammonia, pH, Dissolved oxygen, Conductivity, Turbidity and Chlorophyll A. c) Biodiversity sensor using digital holographic microscope for biodiversity monitoring and tryptophan-like fluorescence sensor for pathogenic monitoring.
-An anti-biofouling system has been tested under lab conditions with the aim of assessing its application in heat exchangers of hydropower plants. The system has shown to be very effective in biofouling prevention with further real life testing waiting to take place.
-Image processing and denoising techniques have been developed for application in underwater inspections.
-Context-aware data models were developed based on input from project partners, and a federated architecture was implemented to enable secure and interoperable acquisition, processing, and exchange of sensor data across hydropower clusters.
WP3-HP digital modeling for optimal O&M
-A secure-by-design framework for reliable and privacy-preserving data exchange across hydropower clusters has been completed. The work is based on the conceptual principles of secure interoperability and addresses the cybersecurity challenges that arise in federated environments where operational data from various sources is exchanged in real time.
-Hydrological modelling and forecasting of water inflows in the context of A2A Friuli HPPs use case, data collection and geomorphological extraction have been completed. The calibration of the hydrological model for the Lumie reservoir in Italy has been completed, while the calibration of the hydrological model for the Ambiesta reservoir is ongoing.
-Historical environmental and biodiversity data relevant to the operation of hydropower plants (HPPs) have been collected and digitized to support the development of predictive models.
-Regarding the biodiversity multiparametric platform, a two-layer model is currently being developed. The first layer is an automated classification system for identifying key microorganism species present in the water. This classifier will rely on computer vision techniques and be enhanced with machine learning algorithms. The second layer relies on a model that will incorporate additional data from the platform, including TLF intensity, to estimate the concentrations of pathogenic organisms. By correlating these datasets with water quality parameters such as pH, temperature or turbidity, the model will provide an integrated overview of microorganism distribution.
-Prediction models/algorithms have been developed that will be used to process the data from the SHM/CM sensors including historical operational data from hydropower plant machinery.
-A first version of a generic Digital Twin of a hydropower plant has been developed and will be used to built a specific DT for one of the Di-Hydro power plants.
-A visualisation tool where hydropower plant operators can view various operational parameters from the Di-Hydro solutions as well as plant sensors has been developed.
-A reduced-order system model of the electrical interconnection between the cluster of the 3 PPC HPPs (Ilarionas, Thisauros and Pournari) and the national grid is on going.
