| New developments
chain of hydropower plants. From planning and designing products, machines, and plants to operating products and production systems, this integration empowers users to act more flexibly and efficiently, customizing their manufacturing processes. Digital Twin of Product: The digital twin of a hydropower product is created as early as the definition and design stage. Engineers can simulate and validate product properties based on specific requirements, such as stability, intuitive use, aerodynamics, and reliability. Whether it involves mechanics, electronics, software, or system performance, the digital twin allows for thorough testing and optimization, resulting in better- performing products. Digital Twin of Production: The digital twin of production encompasses every aspect, from machines and plant controllers to entire production lines in a virtual environment. This simulation process optimizes production in advance, leveraging PLC code generation and virtual commissioning. By identifying and preventing sources of error or failure before actual operation begins, this approach saves time and lays the groundwork for efficient mass production, even for complex production routes. Digital Twin of Performance: The digital twin of performance is continuously fed with operational data from products or the production plant. This enables constant monitoring of status data from machines and energy consumption data from manufacturing systems. As a result, predictive maintenance can be performed to prevent downtime and optimize energy consumption. Companies can also leverage data-driven services to develop new business models, enhancing overall efficiency in their operations.
Siemens Digital Enterprise Suite To facilitate the adoption of digital twins in the
hydropower industry, the Siemens Digital Enterprise Suite has been designed to offer a comprehensive and integrated set of software and automation solutions. A central data platform enables the digitalization of the entire value-added process, while intelligent industrial communication networks allow data exchanges within different production modules, collecting operational data in real-time. To address growing industrial security requirements, the Defense in Depth strategy from Siemens is designed to ensure effective protection for industrial plants against internal and external threats. Additionally, MindSphere serves as a platform for developing new digital business models, providing state-of-the-art security functions for data acquisition and storage in the cloud. Customers who have embraced the Siemens Digital
Enterprise Suite are already witnessing impressive achievements. Special-purpose machine manufacturer Bausch + Ströbel experienced increased efficiency of at least 30% by 2020, thanks to the time saved during engineering. Schunk, a specialist in clamping technology and gripping systems, has streamlined its engineering process, leading to shorter project timelines, faster commissioning, and increased efficiency in building similar plants. A Vuong Hydropower has embraced digitalization
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to optimize operating costs and improve efficiency. Leveraging Siemens Xcelerator portfolio elements, including XHQ Operations Intelligence and COMOS, the company’s leaders can make faster and more accurate decisions. The first phase of its digital transformation, spanning
from 2021 to 2025, focuses on creating a digital twin of its hydropower facility. By digitizing the system, A Vuong Hydropower gains access to real-time transparent data and reports, enabling faster decision- making and efficient monitoring of production. Essential tools like XHQ Operations Intelligence
provide real-time management and remote accessibility of production operations via a web browser. This system equips operators with reports, alerts, and online data analysis to enhance decision- making capabilities. COMOS, on the other hand, facilitates more efficient asset maintenance, reducing downtime and increasing overall productivity. The combination of these software products creates a powerful digital twin of the hydropower plant.
Challenges and future prospects While digital twins offer immense benefits to the
hydropower industry, their implementation is not without challenges. Integrating data from legacy systems, ensuring data security, and addressing computational complexities are some of the hurdles that need to be overcome. Additionally, developing accurate digital twins requires continuous calibration and validation with real-world data, demanding a robust data management strategy. Nevertheless, the future prospects for digital twins in the hydropower sector are promising. Advancements in sensor technology, artificial intelligence, and cloud computing will bolster the capabilities of digital twins, making them more accurate, efficient, and accessible. The integration of Internet of Things (IoT) devices will enable a broader range of data collection and enhance the real-time monitoring capabilities of digital twins.
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