Developing Dynamic Line Rating Determination of Transmission Lines Using Artificial Intelligence Techniques

Transmission lines play a crucial role in ensuring the reliable and efficient transfer of electricity over long distances. However, their static rating limits often lead to underutilization or the risk of overloading during peak demands or under dynamic weather conditions.

This interdisciplinary research project brings together the fields of power engineering, AI, data science, and optimization to address the challenges associated with the conventional static line rating approach.

Through this project, the researcher aims to advance the state-of-the-art in dynamic transmission line rating determination using AI techniques and contribute to the transformation of power grid operations towards a more intelligent, efficient, and sustainable energy system. The findings of this research have the potential to shape the future of power transmission, paving the way for a greener and more reliable electricity grid.

Funding Notes

• Griffith University funds both domestic and international PhD candidates on a competitive basis and is one of few institutions to offer both a tuition fee waiver and a living stipend.
• To be eligible and competitive for a Griffith University Postgraduate Research Scholarship (domestic; View Website) or a Griffith University International Postgraduate Research Scholarship (international applicants; View Website) you need to have First Class Honours or equivalent research experience.
• First-author peer-reviewed publications in international journals are advantageous.
• Top-ranked candidates will be selected from among applicants to proceed to a formal PhD and scholarship application through Griffith University, with the support of the prospective supervisory team.
• Applications can be received and processed year-round for our four intakes. Click here for key dates.