On-line electrical supply generation fuel mix data analysis using Python and TensorFlow

In this paper, the Python scripting language and TensorFlow open source platform for machine learning is used to create a software script that can automatically extract electricity supply generation data from an on-line resource and use machine learning techniques to analyze the available data for the creation of end-user information. An on-line resource was chosen where the data could be readily extracted and stored in multi-dimensional TensorFlow arrays for analysis. The usefulness of such generated end-user information is however based on the accuracy of the information and any biases introduced in the data collation, data presentation, data analysis and results presentation, along with the perceptions of the enduser. With these considerations in mind, this paper focuses on the aspects relating to the creation, operation and use of the Python and TensorFlow script.