Research on anomaly detection of steam power system based on the coupling of thermoeconomics and autoencoder

Guolong Li, Yanjun Li, Site Li, Shengdi Sun, Haotong Wang, Jian Su, Jianxin Shi and Xin Zhou

Energy, 2025, vol. 318, issue C

Abstract: Discovering the anomalies of the steam power system in time can optimize the operating efficiency and avoid major losses. The existing single anomaly detection method is not effective outside its assumptions. Aiming at this problem, a new anomaly detection method based on the coupling of thermoeconomics and autoencoder is proposed. This method uses the autoencoder to reconstruct the normal values of the thermoeconomic calculation benchmark and other parameters. Then the endogenous irreversible loss of each component is calculated according to the benchmark. Finally, it is detected together with the reconstruction error of the parameters, and the deviation exceeding the threshold is abnormal. The experimental results show that under the premise of ensuring the precision, the traditional thermoeconomic anomaly detection method, the autoencoder anomaly detection method and the proposed coupling anomaly detection method can detect 58.7 %, 88.9 % and 94 % abnormal samples, respectively. In terms of the accuracy and F1-score, the coupling method is also the highest, reaching 93.9 % and 96.8 % respectively. It is proved that the coupling method is superior to the single thermoeconomic method or the autoencoder method, which is of great significance to ensure the safe and stable operation of the steam power system.

Keywords: Steam power system; Anomaly detection; Autoencoder; Thermoeconomics; Coupling method (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:318:y:2025:i:c:s036054422500461x

DOI: 10.1016/j.energy.2025.134819

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