On the Application of Model-predictive Control Techniques for Power Management in Electric Ships

ABSTRACT

Management of the power system infrastructure is a challenge due to its complex dynamics, size, deregulated operation, quality of service demands, and stability concerns. Robustness and reliability of the power system can be enhanced with appropriate autonomic control action following the disturbances. This presentation discusses recent work on the applications of model-predictive control (MPC) techniques for power system management. Existing MPC approaches enable intelligent system adaptation and provide the capability to react in real time to undesired scenarios, maintain system specifications to avoid potential risks and recover rapidly. MPC approaches can handle the complex dynamics of most power systems including non-linear and even-driven dynamics. A novel model-based analysis and design framework tailored specifically for electric ships is also presented based on the concept of Model Integrated Computing (MIC). The proposed framework aims to provide a flexible and extensible integrated environment to facilitate rapid modelling and simulation of the electric ship power system as well as the implementation of other control, analysis and management applications.