Hardcore Intelligent Control, Precise Wind Capture | Martec Intelligent Yaw Optimization System Helps 24 Wind Turbines in a Wind Farm in Anhui Undergo Renewal and Upgrade

The wind power industry has entered the stage of stock quality improvement, and reducing consumption and increasing efficiency of old wind turbines has become a key focus of wind farm operations. Most units that have been in service for many years commonly suffer from inaccurate wind alignment and delayed yaw response, causing hidden power generation losses over the long term. Coupled with high operation and maintenance costs, this continuously drags down the overall revenue of wind farms. In response to the above pain points, Martec's Intelligent Yaw Optimization System has been successfully implemented in an operating wind farm in Anhui, completing the intelligent upgrade and transformation of all 24 wind turbines in the farm. Through an integrated solution of hardware upgrades, algorithm optimization, and system reconstruction, the project promotes wind turbine yaw from passive response to active prediction, creating a high-quality benchmark case for the intelligent transformation of old units in the wind power aftermarket. Pain point: Yaw is "half a beat slow," and power generation continues to suffer hidden losses.
The yaw system is responsible for driving the nacelle to follow the wind direction and ensuring efficient wind capture by the rotor. It is a core part of wind turbine power generation, but it is also a major operational weakness of old units. After long-term operation of the old units in this wind farm, the drawbacks of the traditional yaw control system have become prominent: fixed control thresholds and rigid strategies cannot adapt to dynamic wind conditions, resulting in frequent ineffective yaw actions and poor wind alignment accuracy; old sensors provide unstable data under complex wind conditions, leading to delayed yaw response and aggravating mechanical wear of equipment; at the same time, the units only support a single-channel wind measurement input with no redundant backup, so a sensor failure will directly cause the yaw system to lose its decision-making basis, resulting in insufficient stability. Industry practice has confirmed that wind alignment deviation of wind turbines is directly related to power generation loss. The hidden power consumption caused by inaccurate yaw of old units is a core pain point restricting wind farm quality improvement and efficiency enhancement.
Breakthrough: Intelligent yaw precisely empowers turbines to achieve efficient and accurate wind alignment.
In combination with the various operational pain points of the old units in the wind farm, Martec has tailored a dedicated transformation solution based on its self-developed core products. The core of the solution is equipped with the self-developed XFC2-2 heated propeller-type wind speed and wind direction sensor (the core of perception hardware) and the DPM1-1 Intelligent Yaw Optimization System (the core of decision-making algorithms). Through integrated self-developed technology upgrades across the three layers of perception, decision-making, and control, it fundamentally solves the problems of inaccurate yaw and power generation loss of old units. 01 Perception layer upgrade: self-developed high-precision sensors build a solid data foundation. The self-developed XFC2-2 heated propeller-type wind speed and wind direction sensor has passed professional wind tunnel tests and authoritative metrological verification, holds a meteorological special technical equipment use license, and leads the industry in compliance and measurement accuracy. The device adopts a streamlined body paired with a large tail vane structure, with sensitive wind response and excellent wind-following performance. It can adaptively correct wind direction deviation, naturally filter high-frequency fine turbulence interference, and accurately capture the true dominant wind conditions, providing compliant and reliable high-precision raw data for intelligent yaw decision-making. At the same time, it is equipped with a self-developed intelligent heating module. Verified through rigorous icing and freezing rain experiments, it can effectively solve the industry-wide problem of sensor icing and data disconnection in low-temperature wind farms in winter, adapting to the complex outdoor operating environment of wind farms. 02 Decision layer optimization: self-developed algorithm system enables intelligent predictive upgrade. As the core of the project, the self-developed DPM1-1 Intelligent Yaw Optimization System is equipped with Martec's exclusive LSTM neural network + dynamic threshold fusion algorithm, completely breaking the fixed and rigid control logic of traditional units. The system can intelligently predict wind direction trends based on massive historical wind condition data, plan yaw actions in advance, and fundamentally solve the problem of delayed response; identify turbulence intensity in real time, adaptively adjust the yaw startup threshold, and precisely avoid ineffective yaw and equipment wear; and dynamically correct operating parameters in combination with real-time air density, enabling wind turbines to adapt to all-altitude and all-temperature conditions, always lock onto the optimal power generation curve, and maximize power generation potential. 03 Control layer reconstruction: upgrade the operating logic. In this project, a targeted reconstruction and upgrade of the unit main control system was carried out, adding a configurable input module, supporting synchronous access of dual-channel sensor data, and combining SCADA real-time dual-data monitoring to build a dual-channel wind measurement redundant operation mode, thoroughly solving the original problems of single-channel input without backup and susceptibility to failure shutdown, and building a double guarantee for yaw decision-making. At the same time, the blade control logic was optimized, with rapid gust unloading and smooth recovery, effectively reducing impact wear on the gearbox and blades. The low-wind grid connection strategy was optimized, shortening grid connection time and fully tapping the power generation potential under low-wind conditions.

Value: Say goodbye to experience-based operation and maintenance, and enter the era of precise data-based operation and maintenance. This transformation is not only an iteration of equipment and technology, but also achieves a leapfrog upgrade of the wind farm operation and maintenance model, completely getting rid of the limitations of traditional manual experience-based operation and maintenance. After the transformation, the wind farm can rely on real-time data to achieve visualized operation and maintenance of all units. Overall power generation efficiency is significantly improved, ineffective operation of equipment is greatly reduced, operation and maintenance losses are effectively lowered, and the service life of equipment is extended, truly achieving cost reduction and efficiency improvement of stock assets. Conclusion: The successful implementation of the intelligent transformation project of 24 wind turbines in the Anhui wind farm fully verifies the technical advantages of Martec's self-developed wind power sensing and intelligent yaw control system. In the future, the company will continue to deepen its efforts in the field of stock wind power transformation and, with refined intelligent technology, help wind farms achieve refined efficiency improvement and revenue growth.