Faculty/School

Faculty of Engineering

School of Electrical Engineering and Robotics

Topic status

We're looking for students to study this topic.

Research centre

Primary Supervisor

Associate Professor Yateendra Mishra
Position
Associate Professor
Division / Faculty
Faculty of Engineering

Other QUT supervisors

Dr Kien Nguyen Thanh
Position
Senior Research Fellow
Division / Faculty
Faculty of Engineering
Dr Yuchen Zhang
Position
Lecturer
Division / Faculty
Faculty of Engineering

External supervisors

  • Sam Yang, CSIRO

Overview

Quantum optimization in wind farm cable design is an emerging research area where quantum computing techniques are used to solve complex layout and electrical design problems that are difficult for classical methods.

Research engagement

Quantum optimization in wind farms is still in early-stage research, and is used for Offshore wind farm layout optimization, and cable routing under uncertainty.  Student will be conducting initial literature review and be involved in lab-based work on the software coding aspect of this research.

Research activities

Student will be engaged in

  • Input Data
    • Turbine locations
    • Substation positions
    • Cable types and costs
  • Preprocessing
    • Distance matrix
    • Electrical load estimation
  • QUBO Formulation
    • Encode cost + constraints
  • Quantum Optimization
    • Run on D-Wave or simulate QAOA
  • Post-processing
    • Validate feasibility
    • Compute losses and reliability

Research skills

Understanding of the optimization framework for real-world engineering applications and coding of Quantum Optimization algorithms

Outcomes

In wind farms (especially offshore), one of the key challenges is designing the cable network that connects turbines to substations. The aims are:

  • Minimize total cable length
  • Minimize power losses (I²R losses)
  • Reduce installation and maintenance cost
  • Ensure reliability and redundancy
  • Respect technical constraints (current limits, voltage drop, seabed conditions)

This becomes a combinatorial optimization problem, similar to:

  • Minimum spanning tree (MST)
  • Capacitated network design
  • Vehicle routing problems

These problems become NP-hard as the number of turbines increases.

Quantum optimization reformulates wind farm cable design as a binary combinatorial problem (QUBO) and solves it using quantum algorithms to improve cost, efficiency, and scalability beyond classical methods.

Skills and experience

Student should have a good background on MATLAB Simulink and quantum optimization frameworks,  understanding of Python and  basic power systems knowledge.

Start date

2 November, 2026

End date

19 February, 2027

Location

GP-Campus

Keywords

Contact

Yateendra Mishra

0731382119

yateendra.mishra@qut.edu.au