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

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

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 e...

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Bibliographic Details
Main Authors: Yingxiang Liu, Wei Ling, Robert Young, Jalal Zia, Trenton T. Cladouhos, Behnam Jafarpour
Format: Article
Language:English
Published: MDPI AG 2022-03-01
Series:Energies
Subjects:
fault detection
neural network
latent space dynamics
geothermal operations
power plant
Online Access:https://www.mdpi.com/1996-1073/15/7/2555

Internet

https://www.mdpi.com/1996-1073/15/7/2555

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