Advanced EIS-Based Sensor for Online Corrosion and Scaling Monitoring in Pipelines of Geothermal Power Plants

Author:

Freire Lorena1ORCID,Ezpeleta Ignacio1,Sánchez Julio1,Castro Rubén1

Affiliation:

1. AIMEN Technology Centre, 36410 O Porriño, Spain

Abstract

Corrosion and scaling in metal pipelines are the major issues in the exploitation of geothermal sources. Geothermal fluids are complex mixtures consisting of dissolved gases and high-salinity solutions. This creates very aggressive environments primarily due to the high concentrations of carbon dioxide (CO2), hydrogen sulfide (H2S), chlorides, and other chemical species. Besides, the high temperature of the brines also increases corrosion rates, which can lead to failures related to stress and fatigue corrosion. On the other hand, reinjection of cooled brine exiting the heat exchanger favors the onset of scaling, since the chemicals dissolved in geothermal waters may tend to precipitate promoting inorganic depositions on the casing. Corrosion and scaling phenomena are difficult to detect visually or monitor continuously. Standard techniques based on pH, temperature pressure, electrical resistance measurements, chemistry composition, and physical properties are habitually applied as indirect methods for corrosion rate control. These methods, however, lack enough robustness for accurate and reliable measuring of the corrosion behavior of materials. To address this issue, a novel system has been proposed for the continuous monitoring of corrosion degradation caused by the effect of the geothermal brines. The present work aims to design, develop, and validate a dedicated electrochemical-based test system for online and onsite monitoring of the corrosion rate and scaling growth occurring on different materials exposed to real operating conditions. This system uses non-standard methods based on electrochemical impedance spectroscopy (EIS) to obtain quantitative data related to the material quality. It can be used to track the condition of the pipeline, reducing the operation and maintenance (O&M) costs and shutdown times. By providing early corrosion rate data, this system allows the prediction of failures in critical units of the plant.

Funder

European Union’s Horizon 2020 research and innovation program

Publisher

MDPI AG

Reference42 articles.

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