Hydropower is an important strategic asset in India’s evolving power system as it supports renewable generation while also providing flexibility services as variable renewable energy scales up.
Hydropower projects are increasingly being digitalised to operate as flexible, data-driven assets in a grid facing rising renewable energy variability. Advanced digital control and monitoring systems help operators optimise generation scheduling, improve availability, and manage ramping and ancillary service requirements more reliably, while also strengthening condition-based maintenance and response time during outages. According to the Central Electricity Authority (CEA), India’s exploitable large hydropower potential is estimated at 133.41 GW, with a large share in the Northeast, including 50 GW in Arunachal Pradesh alone.
Digital architecture for hydropower operations
Digitalisation in a hydroelectric power plant has the potential to connect field equipment, control systems, communications and analytics into a single decision environment. At the base lie instrumentation and protection systems, which translate physical conditions into measurable signals and enforce safety interlocks during operations. Above this is the plant control layer, which typically comprises digital turbine governing and excitation systems that manage speed, synchronisation, voltage control, reactive power support and stable operation under frequent ramping. The supervisory layer is anchored by a supervisory control and data acquisition (SCADA) system or a distributed control system, providing operators with real-time visibility into turbine generator performance, balance-of-plant equipment, alarms and sequence control while enabling remote command and control within defined permissions. A critical interface is the telemetry and communication link with the load despatch centre, which enables operational coordination for scheduling, ramping and grid support.
As utilities move towards centralised supervision models, the architecture extends beyond individual plants into a hydro operations centre that consolidates multi-plant dashboards and standard operating procedures, reducing dependence on manual coordination and improving response times, particularly for geographically remote sites. What differentiates the current wave of digital upgrades is the integration of operational technology with enterprise-grade data systems.
Key technologies and use cases
Modern plants are expanding measurement coverage beyond conventional process parameters to include higher-frequency condition indicators such as vibration signatures, temperature profiles, flow disturbances and electromagnetic indicators such as air gap and flux. Internet of things architectures are increasingly used to connect these data streams into time-series data sets that can be analysed continuously rather than reviewed in periodic rounds. The goal is to shift from “monitoring” to “actionable diagnostics” by improving data quality, timestamp accuracy and contextual tagging of operating states.
Once data availability improves, the most immediate use case is advanced asset condition monitoring. In hydropower, prescriptive asset health approaches are gaining importance because flexible operation increases transient stress and accelerates wear mechanisms that are not well captured by calendar-based maintenance schedules. Therefore, plants are adopting analytics workflows that evolve from detection to diagnosis and, increasingly, to prescriptive recommendations. In practice, this means integrating condition monitoring systems with data cleansing and correlation engines, using degradation models, and presenting operator-ready insights through dashboards rather than raw trends.
Artificial intelligence (AI) and machine learning (ML) add value through anomaly detection across plant subsystems. Techniques such as adaptive thresholding and dynamic alarm set-point adjustments, where alarm logic is tuned using real-time data rather than static limits, enable earlier detection of anomalies. ML models that learn equipment states, ranging “new” to “worn-out”, can identify early deviations that indicate degradation, often communicating risks through simple operator-facing outputs such as heatmaps.
Digital twin approaches represent the next layer of sophistication. By creating a living operational replica that combines mathematical and physics-based models with live plant measurements, hydrological inputs and operating constraints, digital twins allow operators to test despatch strategies, evaluate ramping and start-stop regimes, and quantify life extension trade-offs in a simulated environment before implementing changes on the machine. This is increasingly relevant as hydro assets are required to operate as flexible grid resources rather than baseload generators.
Digital engineering tools are also shaping performance improvements and refurbishment outcomes. Computational fluid dynamics enables engineers to predict internal flow behaviour, identify efficiency losses and cavitation risks, and refine turbine geometry during design and modernisation. The same modelling logic supports more customised turbine solutions, including variable speed operation strategies that improve efficiency across operating ranges, reduce dynamic loading and enhance performance in pumped storage duty cycles.
Cybersecurity has emerged as a key concern as hydropower plants adopt connected SCADA platforms, remote operations models and cloud-enabled analytics. In hydropower operations, cyber risk is not limited to data loss. A successful intrusion into industrial control environments can disrupt despatch response, trigger equipment trips or create conditions that damage high-value assets.
The Cyber Security in Power Sector Guidelines, 2021, issued by the CEA, lay out a comprehensive cyber assurance framework and mandate compliance across the power ecosystem. For plant operators, cybersecurity must be engineered into the digital architecture rather
than appended after commissioning. This requires disciplined access governance for control systems, secure remote access pathways, segmentation between corporate networks and operational technology, and integrity controls for operational data sets used in analytics and decision support. Equally important is readiness. Incident response procedures, role clarity between information technology and operations teams, and regular workforce training are essential to prevent cyber incidents from escalating into prolonged outages or safety events.
Finally, digitalisation is changing how plants inspect assets and manage people. Drones, computer vision and robotics reduce exposure to hazardous environments and improve the frequency and resolution of inspections in difficult-to-access locations. In parallel, digital workforce tools are replacing paper-based logs and dispersed documentation with mobile maintenance inputs, automated reporting and integrated work order histories. The cumulative impact are faster fault response, improved institutional memory and more consistent operating discipline across a fleet. These benefits are especially important when plants are supervised remotely through centralised operations platforms.
Key initiatives
A flagship example is THDC India Limited’s work at the 1,000 MW Tehri hydropower plant, where the utility has outlined a three-dimensional scanned digital twin initiative, integrated with a metaverse environment, as part of its digital transformation agenda. While outcomes will depend on how the model is operationalised, the initiative signals a shift towards high-fidelity virtual plant representations for training, planning and decision support.
On the operations side, NHPC Limited continues to issue tenders for SCADA upgrades and replacements at major hydro stations. These include a tender for the upgradation of the SCADA system at the Teesta V power station, focused on efficiency and security. NHPC Limited has also floated a package for the upgradation of SCADA systems at the Uri I and Uri II power stations, with provisions for data acquisition from plant-level SCADA systems to the corporate office, indicating a move towards centralised visibility and fleet-level supervision. Beyond supervisory control, NHPC Limited has listed work for static digital excitation systems at the Rangit power station with integration into the existing SCADA environment.
The gencos are also investing in asset condition monitoring and climate risk response. Recent initiatives include NHPC’s procurement of online vibration monitoring and analysis systems at the Salal power station, reinforcing the shift towards continuous health diagnostics for rotating equipment.
At projects such as the Malana I hydroelectric plant in Himachal Pradesh, specialised hydropower cybersecurity solutions have been deployed to protect turbine control systems and plant networks from known vulnerabilities. These solutions focus on patch management, anomaly detection and protection of proprietary control protocols, addressing risks that are distinct from conventional IT environments. SJVN Limited has undertaken retrofitting and upgradation of protection and control networks at assets such as the Rampur hydroelectric project following cybersecurity assessments. Such interventions typically involve redesigning network architecture, hardening communication interfaces and improving segregation between critical protection systems and non-critical networks.
Challenges and the way forward
Despite clear momentum, hydropower digitalisation faces several practical constraints that determine whether investments translate into measurable operational gains. The first is legacy integration. Many operating hydro stations run on heterogeneous control systems built over multiple decades, with limited interoperability and vendor-specific interfaces. Upgrading SCADA, excitation, or protection layers without introducing new failure points requires careful staging, rigorous testing and disciplined configuration management. Closely related is the risk of vendor lock-in, particularly when analytics platforms and proprietary data models sit above the control layer and constrain future integration choices.
The second constraint is data quality. Advanced analytics, anomaly detection and prescriptive maintenance depend on reliable instrumentation, stable communications and consistent tagging of operating conditions.
A phased approach remains the most practical pathway for operators. Once this foundation is in place, utilities can scale predictive analytics, remote operations and digital twins for scenario testing and life extension planning. Over time, such programmes can shift hydropower operations from reactive maintenance and site-dependent supervision to more standardised and digitalised models.