Integrating with Renewable Energy sources: Low Pressure Steam Turbine Last Stage Blade Durability

可再生能源的增加部署需要与传统发电厂整合，以填补不可避免的供应下降。这意味着传统发电厂中的涡轮机叶片部件上的循环载荷急剧增加（由于双移位和载荷跟随，产生许多附加的停止-启动循环）。需要在大型涡轮机叶片中进行基于状态的监测/资产管理，并使用适当的（且经过验证的）预测工具。大型蒸汽涡轮机单元的一个特殊挑战是确保低压涡轮机末级叶片的完整性。由于这些额外的循环载荷，涡轮机叶片根部区域的疲劳裂纹发生率增加。目的是以完全可预测/定制的方式提高用于涡轮机叶片根部的马氏体不锈钢材料的疲劳耐久性。这将需要考虑在制造过程中应用的实际热处理（回火）程序的影响，并评估使用不会对部件形状产生实质性影响的可预测和有效的表面处理来提高叶根特定位置的疲劳耐久性的方法。这就需要充分了解这些系统中的微观结构优化如何提高抗疲劳性，以及疲劳缓解方法的预测，例如在工作缺口特征产生的复杂载荷梯度中进行喷丸处理。开发经验证的疲劳寿命预测是一项关键交付成果，可轻松应用于在役表面条件和关键应力位置的适当缺口几何形状测量。

The increased deployment of renewable energy sources requires integration with conventional power plant to back-fill the inevitable dips in supply. This has meant that the cyclic loading on turbine blade components in conventional power plant has sharply increased (due to two-shifting and load following, producing many additional stop-start cycles). Condition-based monitoring/asset management and the use of appropriate (and validated) prediction tools in large scale turbine blades is required. A particular challenge for large steam turbine units is ensuring the integrity of the low pressure turbine last stage blades. Increased incidences of fatigue cracking in the root region of the turbine blades is seen due to these additional cyclic loads. The aim is to improve the fatigue endurance of the martensitic stainless steel materials used in the turbine blade root in a fully predictable/tailored fashion. This will require consideration of the effects of practical heat treatment (tempering) procedures applied during manufacture and assessing approaches for improving the fatigue endurance in specific locations in the blade root using predictable and effective surface treatments that do not materially affect the shape of the component. This requires developing a full understanding of how microstructural optimisation in these systems can improve fatigue resistance - and also the prediction of fatigue mitigation approaches such as shot peening in the complex loading gradients produced by the service notch features. The development of validated fatigue lifing predictions that can be applied easily to in-service surface conditions and appropriate notch geometry measurements in critical stress locations is a key deliverable.