Coordinated dynamic hosting capacity assessment using artificial intelligence-based techniques

Supervisors

A/Prof Jahangir Hossain and Dr Ibrahim Ibrahim (UTS)

Bill Tarlinton (Zepben) and Dr Carlos Macana (Essential Energy)

The project

This PhD project on dynamic hosting capacity aims to develop an effective decision support framework based on artificial intelligence (AI)-based algorithms for modelling, analysing, and coordinating the behaviours of photovoltaic systems, storage batteries and electric vehicles to increase their penetration levels without breaching the network constraints and any extra investments. It will allow the industry partner to integrate the proposed tool with their existing software platforms.

The intended outcome of the project is a flexible and scalable tool to accurately calculate and enhance to dynamic hosting capacity of distributed energy resources. End-users will benefit from the maximum return on their investment, reduced photovoltaic (PV) curtailment and higher reliability, with the added benefit of reduced CO2 emissions. The research community will benefit from new knowledge that will underpin international improvements in distributed energy resources modelling and hosting capacity.

The successful PhD applicant will work closely with the research partner on the PhD project and will undergo a 2 day commercialisation training

Eligibility

To be eligible for a RACE for 2030 scholarship:

1. Applicants should have a first-class honours or masters degree or equivalent in a related discipline, OR a combination of an upper second-class honour’s degree or equivalent in a related discipline together with a minimum of five years equivalent full-time professional work experience in a relevant field.
2. Applicants must be eligible for enrolment in their chosen course at UTS. It is recommended that students obtain relevant postgraduate information from the relevant university before pursuing a scholarship inquiry.
3. Applicants must be studying full time.