Periodic Reporting for period 1 - Di-Hydro (DIGITAL MAINTENANCE FOR SUSTAINABLE AND FLEXIBLE OPERATION OF HYDROPOWER PLANT)
Periodo di rendicontazione: 2023-10-01 al 2025-03-31
Di-Hydro project focuses on the aspect of digitisation of the hydropower sector. The project stems from the growing need for digitisation and modernisation of the hydropower sector as a result of the aging infrastructure.
The specific objectives of Di-Hydro are the following:
-Develop innovative sensors and data technologies for HP plants. Di-Hydro will develop sensors for structural health monitoring and condition monitoring of HPP machinery or infrastructure as well as sensors for environmental and biodiversity monitoring.
-Digitize maintenance and operation of HP plants for sustainability through a variety of digital solutions such as: a) Digital Twins, b) predictive maintenance algorithms, c) inflow forecasting, d) environmental and biodiversity modeling and their affect on operation and maintenance, d) grid modeling
-Develop reliable, secure and robust HP data architecture and solutions for storing and exchanging historical, operational, sensorial and forecasting data.
-Support Decision-Making on O&M of HP plants and clusters in modern power markets. Creation of Di-Hydro Decision Making Platform, which operates in conjunction with Di-Hydro DT, as a base for optimizing HP O&M, their environmental and socio-economic impact, as it involves energy market prediction algorithms.
The specific objectives of Di-Hydro are the following:
-Develop innovative sensors and data technologies for HP plants. Di-Hydro will develop sensors for structural health monitoring and condition monitoring of HPP machinery or infrastructure as well as sensors for environmental and biodiversity monitoring.
-Digitize maintenance and operation of HP plants for sustainability through a variety of digital solutions such as: a) Digital Twins, b) predictive maintenance algorithms, c) inflow forecasting, d) environmental and biodiversity modeling and their affect on operation and maintenance, d) grid modeling
-Develop reliable, secure and robust HP data architecture and solutions for storing and exchanging historical, operational, sensorial and forecasting data.
-Support Decision-Making on O&M of HP plants and clusters in modern power markets. Creation of Di-Hydro Decision Making Platform, which operates in conjunction with Di-Hydro DT, as a base for optimizing HP O&M, their environmental and socio-economic impact, as it involves energy market prediction algorithms.
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.
- 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.
Currently the results of Di-Hydro within the first 18 months are mostly related to specific project items.
1) The Di-Hydro structural health and condition monitoring sensors are passive devices so that there is no transmission of signals to interrogate a structure or machinery for defects. This greatly reduces power consumption compared to active sensors that continuously consume power that also have much higher cost compared to acoustic emission sensors. 2) Di-Hydro environmental sensors provide water quality real time monitoring and analysis on key spots. A portable and automated Digital Holographic Microscope (DHM) for key microscopic species classification is being tested, together with complementary fluorescence sensors (TLF/ HLF) to add information on pathogenic activity and total organic matter to reinforce the measurement. DHM represents a great alternative beyond the state of the art to expensive time-consuming laboratory analysis, allowing a label free non-invasive visualization of cells. 3)Data security, safety, interoperability, and openness: Di-Hydro introduces a modular, federated architecture that advances secure and interoperable data sharing across HPPs. It combines NGSI-LD based semantic models (capturing both static and dynamic properties of HPPs) with real-time, distributed publish/subscribe mechanisms for selective data sharing, while also integrating proactive, attack graph-driven trust enforcement.
1) The Di-Hydro structural health and condition monitoring sensors are passive devices so that there is no transmission of signals to interrogate a structure or machinery for defects. This greatly reduces power consumption compared to active sensors that continuously consume power that also have much higher cost compared to acoustic emission sensors. 2) Di-Hydro environmental sensors provide water quality real time monitoring and analysis on key spots. A portable and automated Digital Holographic Microscope (DHM) for key microscopic species classification is being tested, together with complementary fluorescence sensors (TLF/ HLF) to add information on pathogenic activity and total organic matter to reinforce the measurement. DHM represents a great alternative beyond the state of the art to expensive time-consuming laboratory analysis, allowing a label free non-invasive visualization of cells. 3)Data security, safety, interoperability, and openness: Di-Hydro introduces a modular, federated architecture that advances secure and interoperable data sharing across HPPs. It combines NGSI-LD based semantic models (capturing both static and dynamic properties of HPPs) with real-time, distributed publish/subscribe mechanisms for selective data sharing, while also integrating proactive, attack graph-driven trust enforcement.