Quantum Distributed Optimization for Generation Scheduling with Renewable Energy Integration

Project title: Quantum Distributed Optimization for Generation Scheduling with Renewable Energy Integration

Position: PhD candidate

Benefits:

100% tuition fee waiver
RM2,850 monthly stipend (up to 42 months)

Project Description:

Generation scheduling with renewable energy integration, in short, stochastic generation scheduling, is one of the most complicated mathematical problems in the field of electrical power systems. In general, the state-of-the-art problem formulation for stochastic generation scheduling is mixed integer linear programming (MILP) due to its computation tractability and efficiency. Still, it is very challenging to solve the day-ahead generation scheduling within 3 hours, especially for large-scale bus systems (100 buses and above). Distributed optimization capable to decompose the problem and solved with multiple nodes (computers) in a distributed fashion. Thus, in this project, a stochastic quantum computation-based distributed optimization, particularly, quantum alternating direction method of multipliers (QADMM), is proposed to gain multifold computation advantage compared to conventional optimization techniques. A quantum simulator will be used to run the QADMM model without the need for a quantum computer.

Requirements:

Open to Malaysians and International Students
Hold an excellent Bachelor degree with CGPA of at least 3.67 (First class) or equivalent in Electrical / Electronics Engineering, Mechatronics Engineering,Computer Engineering, or similar disciplines.
Students who are expected to graduate in the near future are also encouraged to apply.
Having prior journal publications is preferable
Strong analytical skills and mathematical background.
Fundamental knowledge in the areas of power systems and smart grid.
Strong skills in programming/ using tools, such as python, Matlab.
Excellent, motivated, and self-driven.

Please contact Dr. Tan Wen Shan via email : tan.wenshan@monash.edu