Study level

  • PhD
  • Master of Philosophy
  • Honours

Faculty/School

Faculty of Science

School of Information Systems

Topic status

We're looking for students to study this topic.

Research centre

Centre for Data Science

Supervisors

Dr Kenan Degirmenci
Position
Lecturer in Information Systems
Division / Faculty
Faculty of Science

Overview

Artificial intelligence (AI) can play a significant role in analyzing and predicting energy consumption and production patterns from renewable sources such as solar and wind (Lyu & Liu 2021). This is particularly important due to the key challenge of intermittency, where major renewable sources for electricity, such as solar and wind, are subject to the inconsistencies of the weather (Watson et al., 2022).

In this project, we investigate how AI and machine learning algorithms can optimize smart grids and other components of the energy infrastructure to manage the variability and unpredictability associated with renewable energy sources, ultimately contributing to a more stable and reliable energy supply.

References

  • Lyu, W., & Liu, J. (2021). Artificial intelligence and emerging digital technologies in the energy sector. Applied Energy, 303, 1-15. https://doi.org/10.1016/j.apenergy.2021.117615
  • Watson, R. T., Ketter, W., Recker, J., & Seidel, S. (2022). Sustainable energy transition: Intermittency policy based on digital mirror actions. Journal of the Association for Information Systems, 23(3), 631-638. https://doi.org/10.17705/1jais.00752

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Contact

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