The intermittent nature of renewable energy sources (RESs) hamper their integration to the grid. The stochastic and rapid-changing operation of RES technologies impact on power equipment reliability. Transformers are key integrative assets of the power grid and it is crucial to monitor their health for the reliable integration of RESs. Existing models to transformer lifetime estimation are based on point forecasts or steady-state models. In this context, this article presents a novel hybrid transformer prognostics framework for enhanced probabilistic predictions in RES applications. To this end, physics-based transient thermal models and probabilistic forecasting models are integrated using an error-correction configuration. The thermal prediction model is then embedded within a probabilistic prognostics framework to integrate forecasting estimates within the lifetime model, propagate associated uncertainties and predict the transformer remaining useful life with prediction intervals. Prediction intervals vary for each prediction according to the propagated uncertainty and they inform about the confidence of the model in the predictions. The proposed approach is tested and validated with a floating solar power plant case study. Results show that, from the insulation degradation perspective, there may be room to extend the transformer useful life beyond initial lifetime assumptions.

中文翻译：

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用于增强可再生能源应用中概率预测的混合变压器预测框架

可再生能源 (RES) 的间歇性阻碍了它们与电网的整合。RES 技术的随机和快速变化的操作会影响电力设备的可靠性。变压器是电网的关键综合资产，监测其健康状况对于 RES 的可靠整合至关重要。现有的变压器寿命估计模型是基于点预测或稳态模型。在此背景下，本文提出了一种新型混合变压器预测框架，用于增强 RES 应用中的概率预测。为此，基于物理的瞬态热模型和概率预测模型使用误差校正配置进行集成。然后将热预测模型嵌入到概率预测框架中，以将预测估计集成到寿命模型中，传播相关的不确定性并预测变压器的剩余使用寿命以及预测间隔。每个预测的预测区间根据传播的不确定性而变化，它们告知模型在预测中的置信度。所提出的方法通过浮动太阳能发电厂案例研究进行了测试和验证。结果表明，从绝缘退化的角度来看，可能存在将变压器使用寿命延长到超出初始寿命假设的空间。每个预测的预测区间根据传播的不确定性而变化，它们告知模型在预测中的置信度。所提出的方法通过浮动太阳能发电厂案例研究进行了测试和验证。结果表明，从绝缘退化的角度来看，可能存在将变压器使用寿命延长到超出初始寿命假设的空间。每个预测的预测区间根据传播的不确定性而变化，它们告知模型在预测中的置信度。所提出的方法通过浮动太阳能发电厂案例研究进行了测试和验证。结果表明，从绝缘退化的角度来看，可能存在将变压器使用寿命延长到超出初始寿命假设的空间。