Application of Data Science in the Sustainable Energy Industry

Abstract

The application of Data Science (DS) in engineering fields is presented from a broad approach, taking the basics and historical motivation to apply statistical tools into practical needs, from Health Sciences to structural monitoring, the latter linked to the sustainable energy context, like solar, wind, geothermal and nuclear. Moreover, brief bullets about the DS techniques and models are also covered, most in the Machine Learning branch, but with some indications of Artificial Intelligence applications. Math techniques like Kringing, Support Vector Machines, Cross-Validation, Data Regularization, Surrogate Models, for instance, also make part of the text, where the practical issues are evaluated in a brief technical manner. The chapter covers the structural reliability and its DS application too.