Abstracts from the Energy Informatics.Academy Asia 2021 conference and PhD workshop

Abstract

Model predictive control (MPC) allows efficient use of energy systems and can provide considerable energy savings. However, finding a proper configuration of MPC in specific energy systems remains challenging. This doctoral project aims to develop methods of deriving the best combination of models and optimization schemes for a given energy system. The project goal will be achieved by testing different models and optimization techniques of MPC in a virtual testbed. An analysis of how to choose models and corresponding optimization techniques will be conducted based on test results. Three case studies will be carried out to evaluate the proposed methodology. It is expected to advance knowledge of setting up appropriate MPC configuration for energy systems and speed up MPC transition from academic research to wider industry implementation.