Latent-Space Dynamics for Prediction and Fault Detection in Geothermal Power Plant Operations

Yingxiang Liu, Wei Ling, Robert Young, Jalal Zia, Trenton T. Cladouhos and Behnam Jafarpour
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Yingxiang Liu: Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA 90089, USA
Wei Ling: Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, CA 90089, USA
Robert Young: Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, CA 90089, USA
Jalal Zia: Cyrq Energy Inc., Salt Lake City, UT 84101, USA
Trenton T. Cladouhos: Cyrq Energy Inc., Salt Lake City, UT 84101, USA
Behnam Jafarpour: Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, CA 90089, USA

Energies, 2022, vol. 15, issue 7, 1-17

Abstract: This paper presents a latent-space dynamic neural network (LSDNN) model for the multi-step-ahead prediction and fault detection of a geothermal power plant’s operation. The model was trained to learn the dynamics of the power generation process from multivariate time-series data and the effects of exogenous variables, such as control adjustment and ambient temperature. In the LSDNN model, an encoder–decoder architecture was designed to capture cross-correlation among different measured variables. In addition, a latent space dynamic structure was proposed to propagate the dynamics in the latent space to enable prediction. The prediction power of the LSDNN was utilized for monitoring a geothermal power plant and detecting abnormal events. The model was integrated with principal component analysis (PCA)-based process monitoring techniques to develop a fault-detection procedure. The performance of the proposed LSDNN model and fault detection approach was demonstrated using field data collected from a geothermal power plant.

Keywords: fault detection; neural network; latent space dynamics; geothermal operations; power plant (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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