A systematic review of data analytics applications in above-ground geothermal energy operations

Paul Michael B. Abrasaldo, Sadiq J. Zarrouk and Andreas W. Kempa-Liehr

Renewable and Sustainable Energy Reviews, 2024, vol. 189, issue PB

Abstract: The advent of reliable and inexpensive sensors and advancements in general computing have made data-heavy algorithms feasible for operational, real-time decision-making applications in the geothermal energy industry. This systematic review aims to provide a starting point for researchers interested in developing data-driven systems, tools, and frameworks to enhance the performance and reliability of above-ground geothermal energy operations.

Keywords: Geothermal energy; Data analytics; Machine learning; Feature selection; Time-series; Data-quality (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.rser.2023.113998

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