Authorised by Academic Registrar, April 1996
Objectives The student is expected to acquire a basic knowledge and understanding of optimisation in electrical systems and nonlinear programming, in particular dynamic programming. The student is also expected to undertake a given case study to acquire skills in implementation of theoretical knowledge to solve practical problems.
Synopsis Optimisation; formulation of objective functions; constraints; penalty functions; nonlinear programming; dynamic programming - optimal allocation processes; probabilistic optimisation; Monte Carlo simulation; optimising electrical systems.
Assessment Examination (1 hour): 30% + Case study: 70%