The adoption of digital technologies by hydropower plant owners is gaining traction as they seek to optimise the cost of operation and prevent forced outages. They are increasingly bringing in enhanced technologies to refurbish and modernise old plants. The range of applications of digital technologies in the hydropower sector spans the entire hydropower plant life cycle, from planning and design to construction, and operations and maintenance (O&M), in order to meet the larger objectives of safety, sustainability and commerce. Gencos are implementing a range of digital solutions, including smart devices, internet of things (IoT), data analytics, machine learning (ML) and artificial intelligence (AI) to increase the operational efficiency of hydropower plants, optimise time and resources, and provide predictive asset analytics.
Digital use cases for hydropower
Digitalisation enables fault prediction and dynamic maintenance of assets. With the use of AI in hydropower, equipment failures can be predicted well in advance to significantly reduce the cost of downtime and maintenance. Predictive O&M collects and processes data in real time. In addition, with ML and big data, critical parameters such as temperature, vibration, corrosion and short-circuit currents can also be tracked in real time. Old hydropower plants operate at low operational efficiencies and entail high expenses. However, the high cost can be managed through better planning and targeted maintenance, enabled by digitalisation. In the past few years, digitalisation of hydropower plants has entailed the development and testing of a variety of algorithms and methods designed to analyse operational data from power plant control systems, sensors and other measuring equipment installed in the plants. Digital twins, AI and ML provide prompt notifications regarding changes in the functioning or performance of power plant equipment. These models and algorithms are also useful in identifying faults in the plants in advance, preventing serious malfunction. Further, AI/ML, paired with simulation, can help optimise the management of capital and allocation of expenditure for operations.
Many hydropower operators struggle with effective collection, management and utilisation of data from their assets. This limits their ability to maximise asset performance and perform predictive maintenance. Big data can play a major role here, in aggregating large volumes of data from multiple sources to facilitate the integration of other energy sources and market data into production planning. Big data can manage the incoming data from hydropower plants, which can be further used in forecasting tools. IoT allows the analysis of plant operation data to improve performance. The use of sensors provides a continuous, high-rate stream of data on a real-time basis. Developing cognitive machine-to-machine communications is needed to tune hydropower performance as per energy demand and environmental conditions. Data analytics has been useful in forecasting generation and consumption for many years; however, analytics, cognitive computing, and IoT are now being used to enhance operational efficiency.
Digital twin technology is another powerful application of digitalisation in hydropower. It creates an exact virtual replica of a technical component by combining mathematical models with sensors and data measurements, via IoT. Sensors attached to key components collect and process real-time data so that the digital version can act like the real object, allowing the staff to remotely monitor the component, easily detect faulty items, and take immediate actions on site, or even simulate what-if scenarios of stress in the plant. Older power plants have traditionally been difficult to automate, as their mechanical equipment would have to be replaced to prevent them from interfering with the supervisory control and data acquisition (SCADA) system. Often the entire SCADA system would need to be replaced. IoT sensors and devices are able to operate outside the SCADA world, thus allowing for partial upgrades of older plants as a transition to further upgrades to SCADA if needed. Further, digital workforce management solutions assist the O&M staff in routine work such as operation scheduling and documentation. Also, augmented and virtual reality data visualisation tools can be applied at various stages, from investment decisions to design and planning, to maintenance and workforce training.
Challenges and the way forward
The huge penetration of intermittent generation from solar and wind power has created new conditions for the power system, putting at risk its stability. Digitalisation of the older hydropower plants will be necessary to improve sector operations alongside other variable technologies, and ensure the security and efficiency of the power system. However, poor network connectivity between power stations and remote centres poses a major challenge, as effective digitalisation depends on strong communications and connectivity. There is also the risk of increased cyberthreats. To minimise them, gencos will need to raise awareness about cybersecurity and build strong strategies for technological and cyber resilience.
Going forward, digitalisation is key to enabling growth in the hydropower sector. With digitalised maintenance plans, the sector can benefit from optimised O&M costs, improved reliability, and better risk management.