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Digitalization and Data Analytics in Hydro Power

Detailed overview of innovation with sample startups and prominent university research


What it is

Digitalization and data analytics in hydropower involve using digital technologies and data analysis techniques to optimize the performance, reliability, and sustainability of hydropower plants. This approach leverages data-driven insights to improve plant design, operation, and maintenance, leading to increased energy production, reduced costs, and minimized environmental impacts.

Impact on climate action

Digitalization and Data Analytics in Hydropower bolster climate action by optimizing operations, enhancing efficiency, and reducing environmental impact. By analyzing real-time data, these innovations improve hydropower performance, minimize resource usage, and mitigate ecological disturbances, contributing to a more sustainable and resilient energy infrastructure while reducing carbon emissions.

Underlying
Technology

  • Sensors and Data Acquisition: Hydropower plants are equipped with sensors that collect data on various parameters, such as water flow, turbine performance, generator output, and environmental conditions. This data is essential for real-time monitoring and control.
  • Data Analytics and AI: Data analytics and AI algorithms are used to analyze hydropower plant data, identify performance trends, detect potential issues, and provide optimization recommendations.
  • Hydropower Plant Management Software: Software platforms provide tools for visualizing and analyzing plant data, managing operations, and optimizing performance.
  • Predictive Maintenance: AI and data analytics can be used to predict potential equipment failures, allowing for proactive maintenance and reducing downtime.
  • Hydrological Modeling and Forecasting: Advanced hydrological models and forecasting techniques can be used to predict water availability and optimize reservoir operations.
  • Environmental Monitoring: Digital technologies can be used to monitor the environmental impacts of hydropower plants, such as water quality and fish populations, and support mitigation measures.

TRL : 7-8


Prominent Innovation themes

  • AI-Powered Hydropower Plant Optimization: Advanced AI algorithms and machine learning techniques are being developed to optimize hydropower plant performance in real-time, taking into account factors such as water flow, turbine efficiency, and grid requirements.
  • Digital Twins for Hydropower Plants: Digital twins of hydropower plants can be used to simulate and optimize plant operations, predict maintenance needs, and test new technologies.
  • Hydropower Plant Performance Monitoring and Diagnostics: Advanced data analytics platforms can provide real-time monitoring of plant performance, identify potential issues, and provide diagnostic information to facilitate troubleshooting and repairs.
  • Hydrological Forecasting and Reservoir Optimization: AI and data analytics can be used to improve the accuracy of hydrological forecasts and optimize reservoir operations, ensuring efficient water management and maximizing energy production.
  • Environmental Monitoring and Mitigation: Digital technologies, such as sensors and remote sensing, can be used to monitor the environmental impacts of hydropower plants and support mitigation measures, such as fish passage and habitat restoration.

Other Innovation Subthemes

  • Real-Time Performance Optimization
  • Digital Twin Simulation
  • Predictive Maintenance Solutions
  • Advanced Hydrological Forecasting
  • Environmental Impact Monitoring
  • AI-Driven Plant Management
  • Remote Sensing for Environmental Mitigation
  • Sensor-Integrated Plant Design
  • Reservoir Management Optimization
  • In-Pipe Hydropower Systems
  • Data-Driven Grid Integration
  • Advanced Diagnostics and Troubleshooting
  • Remote Monitoring Capabilities

Related Innovations

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Sample Global Startups and Companies

  • Emrgy:
    • Technology Enhancement: Emrgy specializes in the digitalization and data analytics of small-scale hydropower systems. Their proprietary technology includes IoT sensors, data analytics software, and digital twin modeling to monitor, optimize, and manage distributed hydroelectric assets. Emrgy’s platform enables real-time monitoring of hydropower performance, predictive maintenance, and remote control of systems for improved efficiency and reliability.
    • Uniqueness of the Startup: Emrgy stands out for its focus on digitalization and data-driven optimization of small-scale hydropower systems, particularly modular hydrokinetic turbines. Their approach enables the integration of IoT and AI technologies to transform traditional hydropower infrastructure into smart, connected assets, unlocking new opportunities for decentralized renewable energy generation.
    • End-User Segments Addressing: Emrgy serves a diverse range of end-users, including utilities, municipalities, industrial facilities, and rural communities seeking sustainable energy solutions. Their digitalization and data analytics platform are deployed in distributed hydropower projects, microgrids, and off-grid applications, providing reliable and cost-effective renewable energy generation.
  • Natel Energy:
    • Technology Enhancement: Natel Energy specializes in the digitalization and data analytics of low-head hydropower systems. Their flagship product, the Restoration Hydro Turbine (RHT), incorporates advanced sensors, control systems, and cloud-based analytics to optimize energy production, environmental performance, and asset health. Natel’s platform enables real-time monitoring, predictive maintenance, and adaptive control of hydropower installations for maximum efficiency and sustainability.
    • Uniqueness of the Startup: Natel Energy stands out for its focus on digitalization and performance optimization of low-head hydropower assets, particularly for ecological restoration projects. Their technology leverages data-driven insights to balance energy production with environmental considerations, ensuring minimal impact on aquatic ecosystems while maximizing renewable energy generation.
    • End-User Segments Addressing: Natel Energy serves utilities, conservation organizations, and hydropower developers seeking innovative solutions for sustainable water and energy management. Their digitalization and data analytics platform are deployed in river restoration projects, irrigation canals, and existing hydropower facilities, offering a holistic approach to water-energy nexus challenges.
  • Rentricity:
    • Technology Enhancement: Rentricity specializes in the digitalization and data analytics of water and wastewater infrastructure for energy recovery. Their system, known as Flow-to-Wire™, integrates flow monitoring sensors, predictive analytics software, and energy recovery turbines to harness wasted energy in water distribution and treatment systems. Rentricity’s platform enables utilities and municipalities to optimize energy efficiency, reduce operational costs, and generate renewable energy from existing infrastructure.
    • Uniqueness of the Startup: Rentricity stands out for its innovative approach to digitalization and energy recovery in water infrastructure. Their Flow-to-Wire™ technology offers a scalable and cost-effective solution for transforming water distribution and treatment facilities into energy-generating assets, contributing to sustainability goals and resilience in urban water systems.
    • End-User Segments Addressing: Rentricity serves water utilities, municipalities, and industrial facilities seeking to enhance energy efficiency and sustainability in water management. Their digitalization and data analytics platform are deployed in water distribution networks, wastewater treatment plants, and industrial processes, providing economic and environmental benefits through energy recovery and optimization.

Sample Research At Top-Tier Universities

  • Norwegian University of Science and Technology (NTNU):
    • Research Focus: NTNU is a frontrunner in research on Digitalization and Data Analytics in Hydropower, focusing on leveraging digital technologies and advanced data analytics to optimize the operation, maintenance, and performance of hydropower plants.
    • Uniqueness: Their research involves developing intelligent monitoring systems, sensor networks, and predictive analytics algorithms to continuously monitor key parameters such as water flow, turbine efficiency, and structural integrity in hydropower facilities. They also explore the integration of digital twins, machine learning models, and real-time control strategies to enhance operational flexibility, resilience, and sustainability.
    • End-use Applications: The outcomes of their work have applications in hydropower asset management, condition-based maintenance, and grid integration. By harnessing digitalization and data analytics, NTNU’s research helps hydropower operators optimize energy production, reduce downtime, and minimize environmental impacts, thereby enhancing the overall efficiency and reliability of hydropower generation.
  • Swiss Federal Institute of Technology Lausanne (EPFL):
    • Research Focus: EPFL conducts innovative research on Digitalization and Data Analytics in Hydropower, leveraging its expertise in cyber-physical systems, remote sensing, and hydroinformatics to develop advanced solutions for monitoring and managing hydropower assets.
    • Uniqueness: Their research encompasses the development of smart sensor networks, remote sensing technologies, and IoT platforms for collecting and analyzing data from hydropower infrastructure in real-time. They also explore the use of advanced analytics techniques, including machine learning, optimization, and anomaly detection, to identify operational inefficiencies, detect faults, and optimize resource allocation.
    • End-use Applications: The outcomes of their work find applications in dam safety, reservoir management, and environmental monitoring. By harnessing digitalization and data analytics, EPFL’s research supports sustainable hydropower development, enhances water resource management, and promotes ecosystem conservation in river basins and watersheds.
  • Technical University of Munich (TUM):
    • Research Focus: TUM is engaged in cutting-edge research on Digitalization and Data Analytics in Hydropower, leveraging its expertise in hydrology, fluid mechanics, and renewable energy systems to develop innovative solutions for optimizing hydropower operations and enhancing system resilience.
    • Uniqueness: Their research involves the development of hydrological models, computational fluid dynamics simulations, and remote sensing techniques for assessing water availability, flow dynamics, and sediment transport in hydropower reservoirs and rivers. They also explore the use of digital twins, distributed sensing, and predictive analytics to improve flood forecasting, drought management, and environmental impact assessment.
    • End-use Applications: The outcomes of their work have applications in hydropower planning, risk assessment, and climate adaptation. By integrating digitalization and data analytics, TUM’s research supports informed decision-making, enhances stakeholder engagement, and fosters sustainable hydropower development in a changing climate and evolving regulatory landscape.

commercial_img Commercial Implementation

Digitalization and data analytics technologies are being increasingly implemented in hydropower plants around the world, improving efficiency, reliability, and sustainability. For example, many hydropower operators use data analytics platforms to monitor turbine performance and identify potential issues, while others are exploring the use of digital twins for plant optimization.



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