Data mining techniques applied to a building-integrated hybrid renewable energy system
Fait, Catherine (2018)
Fait, Catherine
Tampereen ammattikorkeakoulu
2018
All rights reserved
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2018060612793
https://urn.fi/URN:NBN:fi:amk-2018060612793
Tiivistelmä
There are many challenges associated with sustainable development, and one of the greatest resources available in modern times is data. On the other hand, one of the greatest challenges is producing sustainable energy that puts a stop to excessive energy-related carbon emissions. Uses of big data and data mining techniques have been showing promising results in the renewable sector and are gaining momentum. This paper explores the opportunities afforded and challenges encountered by incorporating a data-driven approach into renewable energy development at a small hybrid renewable energy facility. It takes a detailed look at wind energy generation data streams, and, through a case study, encapsulates the first steps of transforming the measurements into valued output and input of the power facility. The Cross Industry Standard Process for Data Mining is used as a framework to implement this study. Visualization results showed interesting patterns in the data and limitations to the planned analysis were uncovered during investigating the data. The data mining standard process proves to be an excellent framework in the scope of small power facilities for finding and documenting limitations, and building a foundation for innovation.