Amid the lofty mountains and steep valleys of southwest China, where hydropower resources abound, numerous hydropower stations stand like scattered "energy pearls" along the surging Dadu River. Nevertheless, how to link these pearls into an integrated chain, realize their coordinated operation, and maximize the potential of clean energy while ensuring operational safety has long been a perplexing challenge for the industry.
"In the past, we were like crossing the river by feeling the stones — relying on manual screen monitoring and empirical dispatching. By the time water level early warnings were triggered, risks were already imminent, leaving us faced with both water abandonment risks and immense safety pressure," recalled an operation engineer at the Production Command Center of Guoneng Dadu River Basin Hydropower Development Co., Ltd. (hereinafter referred to as "Guoneng Dadu River"). Today, thousands of real-time parameters covering water levels, flow rates and unit statuses of nine hydropower stations and nine reservoirs across the basin fluctuate on the system interface. The platform can detect subtle anomalies in advance, conduct automatic analysis and early warning, and push forward optimized operation strategies.
Behind this revolutionary transformation lies the in-depth empowerment of smart hydropower technologies. Under China’s national carbon peaking and carbon neutrality goals, hydropower enterprises represented by Guoneng Dadu River have deeply integrated new-generation information technologies such as artificial intelligence, big data and the Internet of Things into the millennium-old civilization of water governance. This drives the transformation of cascade hydropower dispatching in large river basins from traditional scheduling to digital scheduling, injecting strong green momentum into the development of a new energy system.
AI Brain on Duty: Making Every Drop of Water Count
The intelligence of hydropower stations is first reflected in the precise regulation and utilization of water, the core resource of hydropower generation. As a form of clean energy, hydropower generation efficiency is constrained by complex and variable hydrological and meteorological conditions. In particular, large-scale cascade hydropower station clusters feature huge scale and intricate correlations. The traditional operation model struggles with delayed real-time risk identification and difficult coordinated dispatching when coping with multi-risk and multi-objective scenarios.
Guoneng Dadu River has joined hands with digital and intelligent service partners including Guoneng Dadu River Big Data Service Co., Ltd. and Luculent Technology Co., Ltd. to build China’s first fully self-controllable graphical one-stop real-time operation risk identification and decision-making system for cascade hydropower stations. It has facilitated a shift in basin dispatching toward a model featuring closed-loop safety management and human-machine collaborative decision-making.
The system has established a dual-objective evaluation system covering safety and economic efficiency with 12 key indicators, forming a full-chain closed-loop management mechanism encompassing perception and early warning, diagnostic analysis, optimization guidance and disposal feedback. Appraised authoritatively by the China Society for Hydropower Engineering at a scientific and technological achievement evaluation conference, this technology has reached an internationally leading level overall.
"Previously, it was difficult to accurately grasp the inflow of downstream stations when upstream stations conducted peak and frequency regulation, and water levels could only be estimated by experience," explained the operation engineer. Now, based on inflow forecast data, the system can accurately simulate and predict the water level variation process of all stations across the basin.
More importantly, this AI brain can not only monitor data, but also conduct computing and overall planning. It has built a panoramic economic model covering water level control, unit start-up combination recommendation, flood discharge suggestions and more. In load optimization scenarios, for instance, the system takes dozens of factors into account including unit efficiency, vibration range and maintenance status to calculate the optimal solution in real time.
Risk Perspective Vision: Forging a New Normal of Intelligent Prevention & Control
Operational safety of hydropower is of paramount importance. Traditional safety management relies heavily on regular inspections, manual records and empirical judgment, making real-time, full-domain and in-depth risk perception unattainable. By constructing a mechanism-data dual-driven perception and diagnosis system, Guoneng Dadu River has equipped the cascade hydropower cluster with a perspective vision and early warning alarm system.
"A bearing temperature of 55℃ may be deemed normal under traditional monitoring standards. However, combined with operating conditions such as unit load, vibration and oil level, our AI model can identify deviation from the normal health trajectory and issue an early warning," explained a smart hydropower expert from Luculent. Rather than evaluating individual parameters in isolation, this intelligent diagnosis builds dynamic correlation models among various parameters, enabling it to capture subtle abnormal signs imperceptible to human observation.
At present, more than 1,000 intelligent alarm models have been deployed for a single hydropower station in the Guoneng Dadu River Basin project, with over 6,000 such models covering the entire cascade station cluster. Deeply integrating equipment operating mechanisms with big data analysis, these models act as round-the-clock sentinels for power stations. For example, relying on the circuit breaker operation diagnosis model, the system accurately warned of an open-circuit risk in the C-phase secondary current loop. On-site verification confirmed loose current terminals, eliminating a potential equipment failure at an early stage.
Such intelligent diagnosis based on expert knowledge and dynamic models has transformed risk identification from over-reliance on manual experience to a new digital and intelligent model featuring machine intelligent recognition and human-machine collaborative decision-making, greatly enhancing the real-time risk prevention and control capability of large-scale hydropower station clusters.
Smart transformation has also profoundly reshaped frontline operation and maintenance scenarios. Digital twin technology creates a virtual mirror operating synchronously with physical power stations, allowing maintenance personnel to perceive the internal status of units remotely. Intelligent inspection robots, high-definition video and IoT sensors have replaced massive repetitive manual work, driving power plants toward unattended and minimally manned operation. The intelligent shift handover system has reduced manual recording workload before and after shifts by 90%. The integration of the intelligent work order and ticket system with IoT locks ensures full safety and controllability of on-site operations.
In the field of equipment maintenance, condition-based preventive maintenance is replacing traditional scheduled maintenance and breakdown maintenance. Through in-depth learning and mechanism modeling of operational data of core equipment such as water turbines and generators, the system can pre-warn of faults including bearing wear and bolt loosening, and automatically push maintenance suggestions. This effectively avoids resource waste caused by over-maintenance and shutdown risks resulting from under-maintenance.
Safeguarding River Basin Stability: Intelligent Commitment to Balanced Development and Ecological Protection
The value of smart hydropower lies not only in power generation, but also in safeguarding the stability and ecological security of river basins. During critical flood control periods, the system identifies potential operational risks of water levels and flow rates in real time based on multi-dimensional data including forecasted inflow, reservoir capacity, downstream discharge capacity and flood control targets, delivering precise early warnings and building a solid smart line of defense for flood prevention.
"During dry seasons or peak regulation periods, the discharge flow of hydropower stations bears directly on downstream ecology as well as the safety of production and domestic water supply," analyzed the operation engineer. The system continuously monitors reservoir discharge flow, complies with river ecological flow requirements, and adopts real-time computing to recommend unit load values that meet the daily average ecological flow standards. Operators can dynamically and precisely regulate water levels and discharge flow. Even in dry seasons, the system guarantees river water demand, maintains river biodiversity, and realizes simultaneous upgrading of economic and ecological benefits.
From the traditional model of manpower-based water governance, to quality upgrading through water conservancy projects, and further to innovative breakthroughs in smart dispatching, the iterative development of smart hydropower marks not only technological transformation in the hydropower industry, but also a reshaping of development philosophy. Today, the vision of smart hydropower featuring holographic perception, global optimization and full-domain collaboration has become a reality. The Dadu River, flowing endlessly for thousands of years, is endowed with brand-new digital genes. Marching toward the carbon peaking and carbon neutrality goals with higher safety assurance, better economic benefits and greener ecological background, it delivers sustained clean energy and a Chinese wisdom model for the green and low-carbon development of China and the world.
Author: He Zengliang, Production Command Center of Guoneng Dadu River BasinPublished in China Plant Engineering Magazine, Energy Vision of China Energy Media and other media platforms.
