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Informative Article | Science and Technology | India | Volume 9 Issue 12, December 2020
Efficiency and Reliability: Machine Learning and Digital Twins for Power Plant Management
Abstract: In the modern era of energy production, the reliable operation of power plants is of paramount importance. Unplanned outages and equipment failures not only result in significant financial losses but also pose a considerable threat to energy security. To address this challenge, this paper presents an innovative approach to anomaly detection in coal-based power plants using machine learning models. The methodology involves the creation of digital twins for power plant machines and the training of these models using historical data. By employing pattern recognition techniques, these models can predict anomalies in real-time, enabling preventive maintenance measures and, ultimately, reducing unplanned outages. The application of this system not only enhances the operational efficiency of the power plant but also safeguards against potential penalties. The study utilizes OSIsoft software from Siemens to facilitate the model training process.
Keywords: Digital twins, OSI soft, Power plant outages, Anomaly detection, ML models
Edition: Volume 9 Issue 12, December 2020,
Pages: 1812 - 1815