Case Studies

Smart wind turbine development driven by digital twin

SANY Heavy Energy realizes high-precision wind turbine simulation with Siemens Simcenter 3D.

Challenges for the wind power industry
Wind power is one of the fastest-growing sources of renewable energy in the world. However, following the rapid development of the past ten years, the wind power industry is faced with tremendous engineering challenges, and its economic efficiency is questioned. A new industry-recognized energy efficiency measure is the levelized cost of electricity (LCOE), which attempts to compare different methods of electricity generation on a consistent basis. LCOE is the cost of building and operating a power-generating asset over its lifecycle divided by lifecycle electricity output. To reduce this cost, wind turbine manufacturers must strive for continuous innovation and develop larger, lighter and more intelligent wind turbines. The aim is to reduce the production, operation and maintenance costs and increase electricity output per unit.

Wind farms are another challenge for the wind power industry. In the last 20 years, traditional high-speed wind farm resources have been used, but are reaching their limits. This results in the urgency for the industry to explore low-speed wind farm resources with the minimum wind speed being around 5 to 5.5 meters per second.

The wind power industry has entered a new era of low speeds. These factors must be taken into account in the development of new products, and present a number of engineering challenges.

Engineering challenges
A wind turbine is a large flexible structure subject to random transient aerodynamic excitation. Core components include blades, towers, direct drive motors and gearboxes. Due to the effects of complex dynamic loads, components sometimes fail, and the failure rate is the most significant contributor to lifecycle costs. Reliability is always an important requirement in the wind turbine design process.

Traditional wind turbine development processes are performed separately, which has a negative impact on the reliability of those machines. On the one hand, in the design process the wind load analysis is disconnected from structural design, forcing engineers to make many assumptions, and sometimes the assumptions are inappropriate. On the other hand, the control program design process is also disconnected from the structural design process. Control program designers must make assumptions about the structural responses under the given loads. Due to technical resource constraints, structural designers often cannot quickly determine the true structural response.

The problem is even more serious in the low-speed wind power market, where the turbine blade is much longer and the tower tube can be as high as 120 to 140 meters, making the turbine even more sensitive to the dynamic loads. Precise prediction of the dynamic response of wind turbines is essential for product development. Creating a high-precision digital simulation model of the complete machine is the fundamental task in predicting its dynamic response.

Large wind turbines are structurally very complex and have many parts and complex surfaces. Traditional finite element simulation cannot meet the requirements for rapid development in terms of either modeling or computation efficiency. Therefore, the model must be parameterized and simplified in preparation for complete machine dynamic performance simulation.

In addition to the challenges of designing individual wind turbines, manufacturers must also consider the overall control of wind farms with more than one turbine. An important way to lower LCOE is by using sensor technology for real-time monitoring of wind forces and wind directions, then using an optimization algorithm to adjust all the turbines in the farm to achieve the optimal power generation efficiency and safe operation. Use of a “digital twin” – an intelligent virtual model that accurately duplicates and simulates the real-world properties and performance of physical products − supports optimal simulation and smart control of physical systems.

SANY Heavy Energy’s choice
Since 2016, SANY Heavy Energy’s product development team has been developing new methods for predicting dynamic loads, developing digital design methods for product platforms and supporting operation and maintenance through optimizing the mechanical performance and control strategies for existing products.

The team has established a complete, mature and efficient digital simulation process, and uses software for external wind load computation and subsequent structural strength analysis of parts. The key step in this process is prediction of the dynamic response of the complete machine. For this purpose, SANY Heavy Energy compared several technical solutions available in the market and decided to implement SimcenterTM solutions from Siemens PLM Software, including LMS Samtech SamcefTM Wind Turbines software for digital simulation modeling and the LMS Samcef solver for prediction of complete machine dynamic response.

LMS Samcef Wind Turbines is a specialized solution for development of wind turbine systems. SANY Heavy Energy uses the software to create a high-precision simulation model that supports the entire development cycle (including conceptual design, detailed design, prototype or modified model development, certification, troubleshooting, and other tasks), thereby coordinating traditionally separate design processes.

The high-precision model of the complete machine provides important value. First, it improves simulation quality by supporting in-the-loop simulation. SANY Heavy Energy can import actual wind farm loads and calculate dynamic responses quickly and precisely to help optimize wind turbine structures and control systems. In addition, the model can also be driven by control system commands that adjust relevant parameters to rapidly obtain control responses.

An added complexity in wind turbine simulation is nonlinearity. For large flexible mechanisms like wind turbines, large rotations and deformations can result in simulation inaccuracy. SANY Heavy Energy uses the LMS Samcef solver’s nonlinear multibody simulation capabilities to compute more accurate dynamic loads.

One of the key capabilities of LMS Samcef Wind Turbines is parametric modeling of turbines. Parameterized models enable designers to easily compare and verify different designs or modify existing designs without complex and time-consuming model reconstruction. The result is shorter development cycles and reduced costs. The software also includes tools that streamline wind turbine certification, enabling SANY Heavy Energy to quickly execute standard sets of calculations and reports that are required by regulatory agencies.

Digital twin and smart wind turbines
SANY Heavy Energy has also implemented intelligent controls for wind turbine operation and maintenance processes. When weather conditions deteriorate or the remote monitoring system sends real-time messages, SANY Heavy Energy’s operation and maintenance team can quickly predict the status and develop an optimal control strategy or maintenance plan, thereby improving the overall wind farm efficiency while avoiding wind turbine failures and extending power generation time. This intelligent operation and maintenance results in a significantly reduced LCOE.

SANY Heavy Energy’s use of Simcenter solutions has yielded positive results. The insights gained through leading-edge simulation have enabled the company to improve wind turbine and farm efficiency by 50 percent, and to reduce projected LCOE by more than ten percent.

“In the rapidly changing wind power industry that has many giants, the key for SANY Heavy Energy to succeed is to fully utilize smart technologies like the digital twin to improve development efficiency and product reliability, thus lowering LCOE and supporting our ultra-low wind speed product strategy,” says Wu Shengfei, CAE simulation manager at SANY Heavy Energy. “In this process, Simcenter 3D provided by Siemens PLM Software is a key value.”

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